Guias, referências e documentação da API para as ferramentas da DeepAI
Conheça nossas ferramentas de inteligência artificial aqui na DeepAI
Converse, pesquise na internet e obtenha ajuda sobre qualquer assunto
Crie fotos legais com nossos diversos geradores de imagens
Edite suas próprias fotos incríveis com nosso editor de imagens com IA
Crie vídeos incríveis a partir de suas próprias imagens ou ideias
Descreva seu site e crie-o sem precisar escrever código
Música, remoção de fundo, colorização, aumento de resolução e muito mais
O que o DeepAI Pro inclui e quanto custa
Conheça as APIs que oferecemos lendo a documentação
O DeepAI é um espaço digital fantástico, repleto de ferramentas de IA. Tornamos a criação de conteúdo mais fácil e acessível a todos! Seja para trabalhar em um projeto escolar ou profissional, ou simplesmente para experimentar ideias criativas, você pode testar nossas ferramentas, incluindo o Chat com IA, a Geração de imagens com IA, o Editor de fotos com IA, os Personagens de IA e muito mais. O DeepAI também oferece recursos para ajudar você a aprender e se manter em dia com os últimos avanços nessa área.
O Chat com IA é um assistente que responde a prompts de texto.
Você pode usá-lo para criar histórias, redigir mensagens ou escrever código. É como conversar com um amigo de IA superinteligente, capaz de falar sobre qualquer assunto. Equipado com algoritmos avançados, o Chat com IA compreende e responde a uma ampla variedade de perguntas com conhecimento e raciocínio.
Quer uma interação por voz fácil de usar? Com o nosso Chat de voz com IA, isso é possível! Desde fazer perguntas e buscar orientação sobre assuntos que você precisa abordar até revisar documentos que deseja aprimorar, sem precisar digitar uma única palavra.
Com essa ferramenta, você pode experimentá-la com uma conta gratuita por 60 segundos por dia ou com uma assinatura do DeepAI Pro para ter acesso à melhor versão do nosso Chat de voz.
A pesquisa Online permite que você encontre informações na internet; é ótima para aprender coisas novas ou descobrir assuntos interessantes. Faça login na sua conta do DeepAI para acessar esse modo.
Esse modo é uma excelente opção para fazer pesquisas na internet em tempo real; com ele, você pode encontrar informações muito mais completas e detalhadas sobre eventos atuais e temas em destaque.
A ferramenta “Memória” ajuda o sistema de chat a coletar informações e definir critérios mais precisos para respostas mais exatas. Ela leva em consideração as informações que você já compartilhou para entender seus gostos, preferências e interesses. Todas essas informações se baseiam nas conversas que você teve com o sistema de chat desde que ativou essa opção. O sistema de chat tem acesso às informações que você forneceu anteriormente, e elas só ficam disponíveis enquanto a opção estiver ativada e você tiver um histórico de chat. Se você excluir seu histórico, o sistema não levará em conta nenhuma conversa anterior.
Deixe o chat navegar na internet em tempo real para encontrar informações mais precisas e atualizadas, além de dados completos sobre o que você está procurando.
A ferramenta "Criar imagem" permite que você gere imagens a partir do chat, de acordo com o modelo de chat que estiver usando: Standard, Genius Pro ou Super Genius Pro. Basta digitar o prompt do que deseja gerar e pronto!
Delegue tarefas do dia a dia ao chat; ele pode ser uma grande ajuda nas tarefas cotidianas. Quer comprar algo que você esqueceu de última hora? Está procurando os melhores preços para passagens aéreas? É só pedir, e ele fará isso por você.
Esta versão representa uma melhoria em relação ao Chat com IA Standard, com desempenho superior, respostas mais detalhadas e maior inteligência.
Este modelo foi projetado para superar o Modo Genius em tarefas que exigem raciocínio avançado, análise lógica e resolução de problemas matemáticos. Embora seu tempo estimado de resposta possa ser um pouco mais longo, ele oferece maior profundidade, compreensão contextual mais ampla e respostas mais abrangentes, resultando em uma experiência mais eficaz e confiável para tarefas complexas.
Com este complemento, você pode resolver problemas de matemática e ciências, incluindo equações, derivadas, problemas de texto, álgebra, cálculo e muito mais! Esse modo é excelente tanto para resolver problemas técnicos quanto para verificar uma tarefa sobre a qual você tenha dúvidas.
O Gerador de imagens com IA é nossa ferramenta de conversão de texto em imagem que permite que você explore sua criatividade e crie usando inteligência artificial. Tente descrever uma imagem do lugar dos seus sonhos ou de qualquer coisa que você desejar, e deixe que a IA cuide do resto!
Para gerar imagens de alta qualidade, escolha seu prompt e, em seguida, selecione entre mais de 100 estilos e formas.
Para obter mais detalhes, maior qualidade artística e imagens que atendam melhor às suas instruções do que as de HD, com resolução de até 1024x1024 px, com a possibilidade de utilizá-las nos formatos horizontal, quadrado ou vertical.
Para imagens 2K de altíssima resolução com detalhes impressionantes. Seja para apenas experimentar ou para criar algo épico, esta ferramenta oferece um modo adequado para cada necessidade. Esse formato funciona perfeitamente se você quiser imprimir a imagem.
O Editor de fotos com IA é uma ferramenta que permite que você dê asas à criatividade e recrie ou modifique qualquer imagem, seja ela nova ou antiga, usando uma descrição em texto das alterações que deseja fazer.
Você pode começar simplesmente enviando uma imagem ou um URL, digitando o comando com as informações que deseja editar ou adicionar, gerando a imagem, e pronto. Para obter melhores resultados, seja específico e conciso em suas instruções, como “torne o céu vermelho” ou “adicione flores ao fundo”.
Você também pode criar uma edição usando até 3 imagens de referência, indicando com exemplos como:
Nosso Gerador de vídeos com IA transforma suas imagens e textos em vídeos. Você pode usá-lo para criar vídeos educativos, de entretenimento ou baseados em contos.
Ao enviar o conteúdo para o gerador de vídeos, você concede à DeepAI o direito de compartilhar a imagem e o vídeo publicamente. Certifique-se de compreender como isso funciona lendo as informações a seguir.
Nossa assinatura do DeepAI Pro inclui 25 segundos de geração de vídeo em HD por mês. Segundos adicionais de vídeo em HD são deduzidos da sua carteira a uma taxa de US$ 0.20 por segundo. O Modo Hollywood (com resolução 2K) inclui 8 segundos de vídeo por mês, e os vídeos adicionais no Modo Hollywood são deduzidos dos seus créditos a uma taxa de US$ 0.30 por segundo.
Um modo de geração versátil, projetado para criar objetos do dia a dia, ambientes e cenas comuns de forma realista, com imagens nítidas e detalhes refinados. Ele apresenta um desempenho especialmente bom com temas práticos e familiares, como eletrodomésticos, móveis, quartos, cozinhas, escritórios, salas de estar e objetos do dia a dia. A melhor relação custo-benefício: US$ 0.20 por segundo.
Vídeos cinematográficos de alta qualidade, com áudio e imagens profissionais. Máxima qualidade criativa por US$ 0.30 por segundo.
Você pode gerar vídeos usando uma imagem como referência. Nosso Gerador de vídeos com IA utiliza a imagem como ponto de partida para a cena e compreende melhor seu prompt, a fim de apresentar um resultado o mais próximo possível da imagem, de acordo com o texto inserido.
Você tem alguma referência que gostaria de usar no seu projeto? Você pode adicioná-la, e o Gerador de vídeos com IA trabalhará com o seu prompt para criar o melhor resultado possível com base nela.
Transforme seu vídeo com inteligência artificial. Adicione, modifique ou remova elementos de suas cenas com instruções simples e dê ao seu conteúdo exatamente o resultado que você deseja.
O Website Builder é uma plataforma online desenvolvida para simplificar a criação, a personalização e o gerenciamento de sites, sem exigir conhecimentos técnicos avançados ou de programação.
Ele oferece aos usuários uma interface intuitiva e um conjunto de componentes configuráveis que lhes permitem criar sites responsivos, personalizar layouts e conteúdos, gerenciar páginas e ajustar a aparência visual de seus projetos.
Explore cada uma de nossas ferramentas e você vai descobrir que, com seu conhecimento e imaginação, é possível criar coisas incríveis!
Crie músicas exclusivas sem esforço com o gerador de música da DeepAI. Perfeito para Foley, efeitos sonoros e trilhas de fundo para seus vídeos. Transforme seus projetos com paisagens sonoras geradas sob medida, adaptadas às suas necessidades.
Se você tiver o DeepAI Pro, as primeiras 100 músicas do mês são gratuitas; as músicas adicionais custam US$ 0.10 cada.
Você tem uma imagem da qual precisa remover o fundo, ou simplesmente não gosta do fundo? Experimente esta ferramenta, e ela irá removê-lo sem esforço.
Gostaria de ver como ficaria uma foto antiga em preto e branco? Adicione suas fotos antigas de família e dê vida a elas com cores.
A ferramenta Super-resolução utiliza aprendizado de máquina para melhorar a clareza, aumentar a nitidez e ampliar a foto sem perder seu conteúdo e suas características distintivas. Infelizmente, imagens desfocadas são comuns e representam um problema tanto para profissionais quanto para amadores. A Super-resolução utiliza técnicas de aprendizado de máquina para ampliar imagens em uma fração de segundo.
Não gostou de algo na foto? Essa ferramenta permite que você altere objetos com facilidade; ao especificar exatamente o que deseja, você pode melhorar sua imagem.
Você não tem certeza se uma imagem é real? Envie uma imagem para estimar se ela foi gerada por IA ou manipulada digitalmente; os resultados são probabilísticos e não devem ser considerados como prova definitiva.
O DeepAI Pro é uma assinatura que oferece acesso ao conjunto completo de ferramentas do DeepAI por US$ 9.99 por mês ou US$ 89.99 por ano, com cotas renovadas mensalmente. Você também pode adicionar créditos para gerar mais conteúdo quando as cotas do seu ciclo atual se esgotarem. Veja mais informações em nossa página de preços, disponível em https://deepai.org/pricing.
Preços: As chamadas à API estão incluídas na sua assinatura do DeepAI Pro. Cada geração é descontada da sua cota mensal ou do saldo da sua carteira pré-paga.
A DeepAI oferece uma variedade de APIs de imagem. Cada uma delas é um endpoint HTTP simples que você pode chamar a partir de qualquer linguagem de programação, como:Cada API do DeepAI consiste em uma única solicitação POST. Envie as entradas do modelo como multipart/form-data e autentique-se com sua chave de API em um cabeçalho da solicitação.
Faça login e copie sua chave no painel da sua conta. O acesso à API requer uma assinatura do DeepAI Pro. Mantenha sua chave em sigilo — trate-a como uma senha e nunca a exponha no código do lado do cliente.
Passe sua chave no cabeçalho api-key e as entradas do modelo como campos de formulário. A URL do endpoint é https://api.deepai.org/api/<model>, onde <model> é o ID do modelo (indicado junto a cada modelo abaixo).
curl -X POST https://api.deepai.org/api/text2img \
-H 'api-key:YOUR_API_KEY' \
-F 'text=a serene mountain lake at sunrise'
Se a operação for bem-sucedida, você receberá uma resposta 200 OK com um corpo em JSON. O link output_url leva ao arquivo gerado e id é o identificador exclusivo do trabalho:
{
"id": "59a0e8a9-...",
"output_url": "https://api.deepai.org/job-view-file/.../output.jpg"
}
Os erros retornam um status diferente de 200 e um corpo JSON com uma mensagem err ou status:
Gere vídeos a partir de uma descrição de texto ou de uma imagem de origem. A geração do vídeo leva alguns minutos; portanto, ao contrário das APIs de imagem, esse processo é assíncrono: envie uma tarefa, receba um código de identificação da tarefa (id) e, em seguida, consulte o endpoint de status até que o vídeo esteja pronto.
Preços: a geração de vídeo requer o DeepAI Pro e é cobrada por segundo de vídeo gerado, deduzida primeiro da sua cota mensal (25 segundos Standard, 8 segundos no Modo Hollywood) e, em seguida, da sua carteira pré-paga (20¢ por segundo Standard, 30¢ por segundo no Modo Hollywood). Consulte a tabela de preços.
Texto para vídeo: POST https://api.deepai.org/video-api/text2video
Imagem para vídeo: POST https://api.deepai.org/video-api/img2video
Status da tarefa: GET https://api.deepai.org/video-api/status/<id>
Envie os parâmetros como multipart/form-data, form-urlencoded ou como um corpo application/json (com image como URL ou dados em base64), com sua chave no cabeçalho api-key, exatamente como nas APIs de imagem. O cabeçalho é obrigatório em todas as chamadas, incluindo consultas de status; uma sessão do navegador não autentica essas rotas.
| Parâmetro | Tipo | Obrigatório | Padrão |
|---|---|---|---|
prompt | string | text2video: Sim img2video: Não | — |
image | arquivo, URL ou base64 | Somente img2video: Sim | — |
mode | string | Não | hd |
duration | integer | Não | 5 |
shape | string | Não | auto |
prompt — o que gerar, até 3.000 caracteres (prompts mais longos são rejeitados com um 400). Opcional no img2video (a imagem de origem por si só já é suficiente).
image — a imagem de origem para o img2video: faça o upload como um campo de arquivo, forneça uma URL pública http(s) ou envie dados em base64 (na forma bruta ou como uma URL do tipo data:image/...;base64,). Máximo de 20 MB, e a imagem deve ser decodificada corretamente. Os redirecionamentos são seguidos.
mode — hd para vídeos Standard ou hollywood para vídeos com qualidade cinematográfica em 2K.
duration — duração do vídeo gerado em segundos, de 5 a 15. A cobrança é por segundo.
shape — square, landscape, standard, vertical, portrait ou auto. Com auto, o img2video segue a forma da imagem de origem e o text2video usa a orientação paisagem. No modo hollywood, o img2video sempre mantém a forma da imagem de origem; portanto, shape deve ser auto nesse caso.
curl -X POST https://api.deepai.org/video-api/text2video \
-H 'api-key:YOUR_API_KEY' \
-F 'prompt=a golden retriever surfing a wave at sunset' \
-F 'mode=hd' \
-F 'duration=5' \
-F 'shape=landscape'
Imagem para vídeo, a partir de um arquivo ou de uma URL:
curl -X POST https://api.deepai.org/video-api/img2video \
-H 'api-key:YOUR_API_KEY' \
-F 'image=@/path/to/photo.jpg' \
-F 'prompt=the camera slowly zooms in'
Um envio bem-sucedido retorna o ID da tarefa a ser consultado:
{
"id": "59a0e8a9-...",
"status": "processing"
}
Verifique o endpoint de status a cada poucos segundos. status é processing, completed ou failed:
curl https://api.deepai.org/video-api/status/59a0e8a9-... \
-H 'api-key:YOUR_API_KEY'
{"status": "processing"}
{"status": "completed", "output_url": "https://...mp4"}
{"status": "failed", "error": "..."}
Um exemplo completo em Python:
import time, requests
headers = {'api-key': 'YOUR_API_KEY'}
job = requests.post(
'https://api.deepai.org/video-api/text2video',
data={'prompt': 'a golden retriever surfing a wave at sunset',
'mode': 'hd', 'duration': 5, 'shape': 'landscape'},
headers=headers).json()
while True:
status = requests.get(
'https://api.deepai.org/video-api/status/' + job['id'],
headers=headers).json()
if status['status'] == 'completed':
print(status['output_url'])
break
if status['status'] == 'failed':
raise RuntimeError(status['error'])
time.sleep(5)
output_url) fica disponível por uma hora após a conclusão; depois disso, o endpoint de status retorna um código 404. Baixe o vídeo assim que ele estiver pronto.401 significa que o cabeçalho api-key está ausente ou é inválido. Um 403 significa que a conta não tem uma assinatura ativa do DeepAI Pro.402 no envio significa que o saldo da sua carteira não cobre o custo do vídeo (o corpo da resposta inclui o custo e o seu saldo) ou que sua conta está bloqueada após uma falha no pagamento. Adicione créditos ou ative a recarga automática no seu painel.400, e o conteúdo que o provedor de vídeo sinaliza durante a geração aparece como {"status": "failed", "error": "NSFW detected"}.Este é um gerador de imagens com IA. Ele cria uma imagem do zero a partir de uma descrição em texto.
Endpoint: POST https://api.deepai.org/api/text2img
| Parâmetro | Tipo | Obrigatório | Padrão |
|---|---|---|---|
text |
text | Sim | — |
text — uma sequência de caracteres que descreve o que deve ser gerado, por exemplo, “Uma noite estrelada sobre um lago sereno” ou “Um retrato de um velho pirata”.
width, height — passe uma string, por exemplo, “256” ou “768” (padrão: 512). Use valores entre 128 e 1536, em múltiplos de 32. Recomendado para imagens Standard: 1024x576, 1024x720, 512x512, 768x1024, 576x1024. Recomendado para imagens em HD: 1216x832, 1152x896, 1024x1024, 896x1152, 832x1216. Valores acima de ~700 ou abaixo de 256 podem produzir resultados anormais.
image_generator_version — "standard" (padrão), "hd", "genius" ou "super_genius".
resolution — "2k" (padrão) ou "4k". Usado apenas quando image_generator_version é "super_genius".
genius_preference — "anime", "photography", "graphic" ou "cinematic". Usado apenas quando image_generator_version é "genius".
negative_prompt — uma sequência de caracteres que descreve o que deve ser removido da imagem; útil para melhorar a qualidade e os detalhes. Exemplo: anatomia incorreta, desfocada, recortada, deformada, desfigurada, duplicada, membros extras, dedos fundidos, artefatos JPEG, baixa qualidade, baixa resolução, mãos mutantes, fora do quadro, assinatura, texto, marca d’água, pior qualidade.
Exemplos de Gerador de imagens com IA em cURL
# Example posting a text URL:
curl \
-F 'text=YOUR_TEXT_HERE' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/text2img
# Example posting a local text file:
curl \
-F 'text=YOUR_TEXT_HERE' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/text2img
# Example directly sending a text string:
curl \
-F 'text=YOUR_TEXT_HERE' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/text2img
Exemplos de Gerador de imagens com IA em Javascript
// Example posting a text URL:
(async function() {
const resp = await fetch('https://api.deepai.org/api/text2img', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
text: "YOUR_TEXT_HERE",
})
});
const data = await resp.json();
console.log(data);
})()
// Example posting file picker input text (Browser only):
document.getElementById('yourFileInputId').addEventListener('change', async function() {
const formData = new FormData();
formData.append('text', 'YOUR_TEXT_HERE');
const resp = await fetch('https://api.deepai.org/api/text2img', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example posting a local text file (Node.js only):
const fs = require('fs');
(async function() {
const formData = new FormData();
formData.append('text', 'YOUR_TEXT_HERE');
const resp = await fetch('https://api.deepai.org/api/text2img', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example directly sending a text string:
(async function() {
const resp = await fetch('https://api.deepai.org/api/text2img', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
text: "YOUR_TEXT_HERE",
})
});
const data = await resp.json();
console.log(data);
})()
Exemplos de Gerador de imagens com IA em Python
# Example posting a text URL:
import requests
r = requests.post(
"https://api.deepai.org/api/text2img",
data={
'text': 'YOUR_TEXT_HERE',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example posting a local text file:
import requests
r = requests.post(
"https://api.deepai.org/api/text2img",
data={
'text': 'YOUR_TEXT_HERE',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example directly sending a text string:
import requests
r = requests.post(
"https://api.deepai.org/api/text2img",
data={
'text': 'YOUR_TEXT_HERE',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
Exemplos de Gerador de imagens com IA em Ruby
# Example posting a text URL:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/text2img', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'text' => 'YOUR_TEXT_HERE',
}
)
puts r
# Example posting a local text file:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/text2img', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'text' => 'YOUR_TEXT_HERE',
}
)
puts r
# Example directly sending a text string:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/text2img', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'text' => 'YOUR_TEXT_HERE',
}
)
puts r
Exemplos de Gerador de imagens com IA em Php
// Example posting a text URL:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'text',
'contents' => 'YOUR_TEXT_HERE'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/text2img', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example posting a local text file:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'text',
'contents' => 'YOUR_TEXT_HERE'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/text2img', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example directly sending a text string:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'text',
'contents' => 'YOUR_TEXT_HERE'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/text2img', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
Exemplos de Gerador de imagens com IA em Go
// Example posting a text URL:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/text2img"
payload := map[string]string{
"text": "YOUR_TEXT_HERE",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example posting a local text file:
package main
import (
"bytes"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
url := "https://api.deepai.org/api/text2img"
var b bytes.Buffer
w := multipart.NewWriter(&b)
w.WriteField("text", "YOUR_TEXT_HERE")
if err := w.Close(); err != nil {
panic(err)
}
req, _ := http.NewRequest("POST", url, &b)
req.Header.Set("Content-Type", w.FormDataContentType())
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example directly sending a text string:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/text2img"
payload := map[string]string{
"text": "YOUR_TEXT_HERE",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
Exemplos de Gerador de imagens com IA em Java
// Example posting a text URL:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"text\": \"YOUR_TEXT_HERE\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/text2img"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
// Example posting a local text file:
// Add to build.gradle: implementation 'com.squareup.okhttp3:okhttp:4.12.0'
import okhttp3.*;
import java.io.File;
import java.io.IOException;
public class Main {
public static void main(String[] args) throws IOException {
OkHttpClient client = new OkHttpClient();
RequestBody requestBody = new MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("text", "YOUR_TEXT_HERE")
.build();
Request request = new Request.Builder()
.url("https://api.deepai.org/api/text2img")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}
}
}
// Example directly sending a text string:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"text\": \"YOUR_TEXT_HERE\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/text2img"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
Exemplos de Gerador de imagens com IA em C#
// Example posting a text URL:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
text = "YOUR_TEXT_HERE",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/text2img", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example posting a local text file:
using System;
using System.IO;
using System.Net.Http;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
using var form = new MultipartFormDataContent();
form.Add(new StringContent("YOUR_TEXT_HERE"), "text");
var response = await client.PostAsync("https://api.deepai.org/api/text2img", form);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example directly sending a text string:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
text = "YOUR_TEXT_HERE",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/text2img", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
Exemplos de Gerador de imagens com IA em Swift
// Example posting a text URL:
import Foundation
let url = URL(string: "https://api.deepai.org/api/text2img")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"text": "YOUR_TEXT_HERE",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
// Keep the program running for async request
RunLoop.main.run()
// Example posting a local text file:
import Foundation
let url = URL(string: "https://api.deepai.org/api/text2img")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let boundary = UUID().uuidString
request.setValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")
var body = Data()
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"text\"\r\n\r\n".data(using: .utf8)!)
body.append("YOUR_TEXT_HERE".data(using: .utf8)!)
body.append("\r\n".data(using: .utf8)!)
body.append("--\(boundary)--\r\n".data(using: .utf8)!)
request.httpBody = body
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
// Example directly sending a text string:
import Foundation
let url = URL(string: "https://api.deepai.org/api/text2img")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"text": "YOUR_TEXT_HERE",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
Exemplos de Gerador de imagens com IA em Kotlin
// Example posting a text URL:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"text": "YOUR_TEXT_HERE"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/text2img"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
// Example posting a local text file:
// Add to build.gradle.kts: implementation("com.squareup.okhttp3:okhttp:4.12.0")
import okhttp3.*
import okhttp3.MediaType.Companion.toMediaType
import okhttp3.RequestBody.Companion.asRequestBody
import java.io.File
fun main() {
val client = OkHttpClient()
val requestBody = MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("text", "YOUR_TEXT_HERE")
.build()
val request = Request.Builder()
.url("https://api.deepai.org/api/text2img")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build()
client.newCall(request).execute().use { response ->
println(response.body?.string())
}
}
// Example directly sending a text string:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"text": "YOUR_TEXT_HERE"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/text2img"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
Exemplos de Gerador de imagens com IA em Rust
// Example posting a text URL:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("text", "YOUR_TEXT_HERE");
let response = client
.post("https://api.deepai.org/api/text2img")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example posting a local text file:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
use reqwest::multipart;
use std::fs;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let form = multipart::Form::new()
.text("text", "YOUR_TEXT_HERE");
let response = client
.post("https://api.deepai.org/api/text2img")
.header("api-key", "YOUR_API_KEY")
.multipart(form)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example directly sending a text string:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("text", "YOUR_TEXT_HERE");
let response = client
.post("https://api.deepai.org/api/text2img")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
Exemplos de Gerador de imagens com IA em TypeScript
// Example posting a text URL:
interface ApiResponse {
// Define your response type here
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/text2img', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
text: 'YOUR_TEXT_HERE',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
// Example posting a local text file (Node.js with form-data package):
// npm install form-data
import * as fs from 'fs';
import FormData from 'form-data';
interface ApiResponse {
[key: string]: unknown;
}
async function uploadFile(): Promise<ApiResponse> {
const formData = new FormData();
formData.append('text', 'YOUR_TEXT_HERE');
const response = await fetch('https://api.deepai.org/api/text2img', {
method: 'POST',
headers: {
...formData.getHeaders(),
'api-key': 'YOUR_API_KEY'
},
body: formData as unknown as BodyInit
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
uploadFile();
// Example directly sending a text string:
interface ApiResponse {
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/text2img', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
text: 'YOUR_TEXT_HERE',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
Exemplos de Gerador de imagens com IA em Dart
// Example posting a text URL:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/text2img'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'text': 'YOUR_TEXT_HERE',
}),
);
print(response.body);
}
// Example posting a local text file:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:io';
import 'package:http/http.dart' as http;
Future<void> main() async {
var request = http.MultipartRequest(
'POST',
Uri.parse('https://api.deepai.org/api/text2img'),
);
request.headers['api-key'] = 'YOUR_API_KEY';
request.fields['text'] = 'YOUR_TEXT_HERE';
var response = await request.send();
var responseBody = await response.stream.bytesToString();
print(responseBody);
}
// Example directly sending a text string:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/text2img'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'text': 'YOUR_TEXT_HERE',
}),
);
print(response.body);
}
Exemplos de Gerador de imagens com IA em PowerShell
# Example posting a text URL:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/text2img `
-Method Post `
-Form @{
text='YOUR_TEXT_HERE'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example posting a local text file:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/text2img `
-Method Post `
-Form @{
text='YOUR_TEXT_HERE'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example directly sending a text string:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/text2img `
-Method Post `
-Form @{
text='YOUR_TEXT_HERE'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
Remova o fundo da imagem com IA.
Endpoint: POST https://api.deepai.org/api/background-remover
| Parâmetro | Tipo | Obrigatório | Padrão |
|---|---|---|---|
image |
image | Sim | — |
Exemplos de Removedor de fundo em cURL
# Example posting a image URL:
curl \
-F 'image=YOUR_IMAGE_URL' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/background-remover
# Example posting a local image file:
curl \
-F 'image=@/path/to/your/file.jpg' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/background-remover
Exemplos de Removedor de fundo em Javascript
// Example posting a image URL:
(async function() {
const resp = await fetch('https://api.deepai.org/api/background-remover', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: "YOUR_IMAGE_URL",
})
});
const data = await resp.json();
console.log(data);
})()
// Example posting file picker input image (Browser only):
document.getElementById('yourFileInputId').addEventListener('change', async function() {
const formData = new FormData();
formData.append('image', this.files[0]);
const resp = await fetch('https://api.deepai.org/api/background-remover', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example posting a local image file (Node.js only):
const fs = require('fs');
(async function() {
const formData = new FormData();
const jpgFileStream = fs.createReadStream("/path/to/your/file.jpg");
formData.append('image', jpgFileStream);
const resp = await fetch('https://api.deepai.org/api/background-remover', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
Exemplos de Removedor de fundo em Python
# Example posting a image URL:
import requests
r = requests.post(
"https://api.deepai.org/api/background-remover",
data={
'image': 'YOUR_IMAGE_URL',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example posting a local image file:
import requests
r = requests.post(
"https://api.deepai.org/api/background-remover",
files={
'image': open('/path/to/your/file.jpg', 'rb'),
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
Exemplos de Removedor de fundo em Ruby
# Example posting a image URL:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/background-remover', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => 'YOUR_IMAGE_URL',
}
)
puts r
# Example posting a local image file:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/background-remover', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => File.new('/path/to/your/file.jpg'),
}
)
puts r
Exemplos de Removedor de fundo em Php
// Example posting a image URL:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => 'YOUR_IMAGE_URL'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/background-remover', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example posting a local image file:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => Utils::tryFopen('/path/to/your/file.jpg', 'r')
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/background-remover', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
Exemplos de Removedor de fundo em Go
// Example posting a image URL:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/background-remover"
payload := map[string]string{
"image": "YOUR_IMAGE_URL",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example posting a local image file:
package main
import (
"bytes"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
url := "https://api.deepai.org/api/background-remover"
var b bytes.Buffer
w := multipart.NewWriter(&b)
imageFile, _ := os.Open("/path/to/your/file.jpg")
defer imageFile.Close()
imageWriter, _ := w.CreateFormFile("image", "file.jpg")
io.Copy(imageWriter, imageFile)
if err := w.Close(); err != nil {
panic(err)
}
req, _ := http.NewRequest("POST", url, &b)
req.Header.Set("Content-Type", w.FormDataContentType())
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
Exemplos de Removedor de fundo em Java
// Example posting a image URL:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"image\": \"YOUR_IMAGE_URL\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/background-remover"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
// Example posting a local image file:
// Add to build.gradle: implementation 'com.squareup.okhttp3:okhttp:4.12.0'
import okhttp3.*;
import java.io.File;
import java.io.IOException;
public class Main {
public static void main(String[] args) throws IOException {
OkHttpClient client = new OkHttpClient();
RequestBody requestBody = new MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", RequestBody.create(new File("/path/to/your/file.jpg"), MediaType.parse("application/octet-stream")))
.build();
Request request = new Request.Builder()
.url("https://api.deepai.org/api/background-remover")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}
}
}
Exemplos de Removedor de fundo em C#
// Example posting a image URL:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
image = "YOUR_IMAGE_URL",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/background-remover", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example posting a local image file:
using System;
using System.IO;
using System.Net.Http;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
using var form = new MultipartFormDataContent();
var imageStream = File.OpenRead("/path/to/your/file.jpg");
form.Add(new StreamContent(imageStream), "image", "file.jpg");
var response = await client.PostAsync("https://api.deepai.org/api/background-remover", form);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
Exemplos de Removedor de fundo em Swift
// Example posting a image URL:
import Foundation
let url = URL(string: "https://api.deepai.org/api/background-remover")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"image": "YOUR_IMAGE_URL",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
// Keep the program running for async request
RunLoop.main.run()
// Example posting a local image file:
import Foundation
let url = URL(string: "https://api.deepai.org/api/background-remover")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let boundary = UUID().uuidString
request.setValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")
var body = Data()
let imageData = try! Data(contentsOf: URL(fileURLWithPath: "/path/to/your/file.jpg"))
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"image\"; filename=\"file.jpg\"\r\n".data(using: .utf8)!)
body.append("Content-Type: application/octet-stream\r\n\r\n".data(using: .utf8)!)
body.append(imageData)
body.append("\r\n".data(using: .utf8)!)
body.append("--\(boundary)--\r\n".data(using: .utf8)!)
request.httpBody = body
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
Exemplos de Removedor de fundo em Kotlin
// Example posting a image URL:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"image": "YOUR_IMAGE_URL"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/background-remover"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
// Example posting a local image file:
// Add to build.gradle.kts: implementation("com.squareup.okhttp3:okhttp:4.12.0")
import okhttp3.*
import okhttp3.MediaType.Companion.toMediaType
import okhttp3.RequestBody.Companion.asRequestBody
import java.io.File
fun main() {
val client = OkHttpClient()
val requestBody = MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", File("/path/to/your/file.jpg").asRequestBody("application/octet-stream".toMediaType()))
.build()
val request = Request.Builder()
.url("https://api.deepai.org/api/background-remover")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build()
client.newCall(request).execute().use { response ->
println(response.body?.string())
}
}
Exemplos de Removedor de fundo em Rust
// Example posting a image URL:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("image", "YOUR_IMAGE_URL");
let response = client
.post("https://api.deepai.org/api/background-remover")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example posting a local image file:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
use reqwest::multipart;
use std::fs;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let form = multipart::Form::new()
.file("image", "/path/to/your/file.jpg")?;
let response = client
.post("https://api.deepai.org/api/background-remover")
.header("api-key", "YOUR_API_KEY")
.multipart(form)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
Exemplos de Removedor de fundo em TypeScript
// Example posting a image URL:
interface ApiResponse {
// Define your response type here
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/background-remover', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: 'YOUR_IMAGE_URL',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
// Example posting a local image file (Node.js with form-data package):
// npm install form-data
import * as fs from 'fs';
import FormData from 'form-data';
interface ApiResponse {
[key: string]: unknown;
}
async function uploadFile(): Promise<ApiResponse> {
const formData = new FormData();
formData.append('image', fs.createReadStream('/path/to/your/file.jpg'));
const response = await fetch('https://api.deepai.org/api/background-remover', {
method: 'POST',
headers: {
...formData.getHeaders(),
'api-key': 'YOUR_API_KEY'
},
body: formData as unknown as BodyInit
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
uploadFile();
Exemplos de Removedor de fundo em Dart
// Example posting a image URL:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/background-remover'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'image': 'YOUR_IMAGE_URL',
}),
);
print(response.body);
}
// Example posting a local image file:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:io';
import 'package:http/http.dart' as http;
Future<void> main() async {
var request = http.MultipartRequest(
'POST',
Uri.parse('https://api.deepai.org/api/background-remover'),
);
request.headers['api-key'] = 'YOUR_API_KEY';
request.files.add(
await http.MultipartFile.fromPath('image', '/path/to/your/file.jpg'),
);
var response = await request.send();
var responseBody = await response.stream.bytesToString();
print(responseBody);
}
Exemplos de Removedor de fundo em PowerShell
# Example posting a image URL:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/background-remover `
-Method Post `
-Form @{
image='YOUR_IMAGE_URL'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example posting a local image file:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/background-remover `
-Method Post `
-Form @{
image=Get-Item -Path '/path/to/your/file.jpg'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
Edite fotos e imagens com IA.
Endpoint: POST https://api.deepai.org/api/image-editor
| Parâmetro | Tipo | Obrigatório | Padrão |
|---|---|---|---|
image |
image | Sim | — |
text |
text | Sim | — |
image_generator_version — opcional. Passe "genius" ou "super_genius" para obter edições de maior qualidade e mais detalhadas. O padrão é o editor standard.
resolution — "2k" (padrão) ou "4k". Usado apenas quando image_generator_version é "super_genius".
Exemplos de Editor de fotos com IA em cURL
# Example posting a image URL:
curl \
-F 'image=YOUR_IMAGE_URL' \
-F 'text=YOUR_TEXT_HERE' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/image-editor
# Example posting a local image file:
curl \
-F 'image=@/path/to/your/file.jpg' \
-F 'text=YOUR_TEXT_HERE' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/image-editor
Exemplos de Editor de fotos com IA em Javascript
// Example posting a image URL:
(async function() {
const resp = await fetch('https://api.deepai.org/api/image-editor', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: "YOUR_IMAGE_URL",
text: "YOUR_TEXT_HERE",
})
});
const data = await resp.json();
console.log(data);
})()
// Example posting file picker input image (Browser only):
document.getElementById('yourFileInputId').addEventListener('change', async function() {
const formData = new FormData();
formData.append('image', this.files[0]);
formData.append('text', 'YOUR_TEXT_HERE');
const resp = await fetch('https://api.deepai.org/api/image-editor', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example posting a local image file (Node.js only):
const fs = require('fs');
(async function() {
const formData = new FormData();
const jpgFileStream = fs.createReadStream("/path/to/your/file.jpg");
formData.append('image', jpgFileStream);
formData.append('text', 'YOUR_TEXT_HERE');
const resp = await fetch('https://api.deepai.org/api/image-editor', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
Exemplos de Editor de fotos com IA em Python
# Example posting a image URL:
import requests
r = requests.post(
"https://api.deepai.org/api/image-editor",
data={
'image': 'YOUR_IMAGE_URL',
'text': 'YOUR_TEXT_HERE',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example posting a local image file:
import requests
r = requests.post(
"https://api.deepai.org/api/image-editor",
files={
'image': open('/path/to/your/file.jpg', 'rb'),
},
data={
'text': 'YOUR_TEXT_HERE',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
Exemplos de Editor de fotos com IA em Ruby
# Example posting a image URL:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/image-editor', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => 'YOUR_IMAGE_URL',
'text' => 'YOUR_TEXT_HERE',
}
)
puts r
# Example posting a local image file:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/image-editor', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => File.new('/path/to/your/file.jpg'),
'text' => 'YOUR_TEXT_HERE',
}
)
puts r
Exemplos de Editor de fotos com IA em Php
// Example posting a image URL:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => 'YOUR_IMAGE_URL'
],
[
'name' => 'text',
'contents' => 'YOUR_TEXT_HERE'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/image-editor', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example posting a local image file:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => Utils::tryFopen('/path/to/your/file.jpg', 'r')
],
[
'name' => 'text',
'contents' => 'YOUR_TEXT_HERE'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/image-editor', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
Exemplos de Editor de fotos com IA em Go
// Example posting a image URL:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/image-editor"
payload := map[string]string{
"image": "YOUR_IMAGE_URL",
"text": "YOUR_TEXT_HERE",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example posting a local image file:
package main
import (
"bytes"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
url := "https://api.deepai.org/api/image-editor"
var b bytes.Buffer
w := multipart.NewWriter(&b)
imageFile, _ := os.Open("/path/to/your/file.jpg")
defer imageFile.Close()
imageWriter, _ := w.CreateFormFile("image", "file.jpg")
io.Copy(imageWriter, imageFile)
w.WriteField("text", "YOUR_TEXT_HERE")
if err := w.Close(); err != nil {
panic(err)
}
req, _ := http.NewRequest("POST", url, &b)
req.Header.Set("Content-Type", w.FormDataContentType())
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
Exemplos de Editor de fotos com IA em Java
// Example posting a image URL:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"image\": \"YOUR_IMAGE_URL\"" +
"\"text\": \"YOUR_TEXT_HERE\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/image-editor"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
// Example posting a local image file:
// Add to build.gradle: implementation 'com.squareup.okhttp3:okhttp:4.12.0'
import okhttp3.*;
import java.io.File;
import java.io.IOException;
public class Main {
public static void main(String[] args) throws IOException {
OkHttpClient client = new OkHttpClient();
RequestBody requestBody = new MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", RequestBody.create(new File("/path/to/your/file.jpg"), MediaType.parse("application/octet-stream")))
.addFormDataPart("text", "YOUR_TEXT_HERE")
.build();
Request request = new Request.Builder()
.url("https://api.deepai.org/api/image-editor")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}
}
}
Exemplos de Editor de fotos com IA em C#
// Example posting a image URL:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
image = "YOUR_IMAGE_URL",
text = "YOUR_TEXT_HERE",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/image-editor", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example posting a local image file:
using System;
using System.IO;
using System.Net.Http;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
using var form = new MultipartFormDataContent();
var imageStream = File.OpenRead("/path/to/your/file.jpg");
form.Add(new StreamContent(imageStream), "image", "file.jpg");
form.Add(new StringContent("YOUR_TEXT_HERE"), "text");
var response = await client.PostAsync("https://api.deepai.org/api/image-editor", form);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
Exemplos de Editor de fotos com IA em Swift
// Example posting a image URL:
import Foundation
let url = URL(string: "https://api.deepai.org/api/image-editor")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"image": "YOUR_IMAGE_URL",
"text": "YOUR_TEXT_HERE",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
// Keep the program running for async request
RunLoop.main.run()
// Example posting a local image file:
import Foundation
let url = URL(string: "https://api.deepai.org/api/image-editor")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let boundary = UUID().uuidString
request.setValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")
var body = Data()
let imageData = try! Data(contentsOf: URL(fileURLWithPath: "/path/to/your/file.jpg"))
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"image\"; filename=\"file.jpg\"\r\n".data(using: .utf8)!)
body.append("Content-Type: application/octet-stream\r\n\r\n".data(using: .utf8)!)
body.append(imageData)
body.append("\r\n".data(using: .utf8)!)
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"text\"\r\n\r\n".data(using: .utf8)!)
body.append("YOUR_TEXT_HERE".data(using: .utf8)!)
body.append("\r\n".data(using: .utf8)!)
body.append("--\(boundary)--\r\n".data(using: .utf8)!)
request.httpBody = body
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
Exemplos de Editor de fotos com IA em Kotlin
// Example posting a image URL:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"image": "YOUR_IMAGE_URL",
"text": "YOUR_TEXT_HERE"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/image-editor"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
// Example posting a local image file:
// Add to build.gradle.kts: implementation("com.squareup.okhttp3:okhttp:4.12.0")
import okhttp3.*
import okhttp3.MediaType.Companion.toMediaType
import okhttp3.RequestBody.Companion.asRequestBody
import java.io.File
fun main() {
val client = OkHttpClient()
val requestBody = MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", File("/path/to/your/file.jpg").asRequestBody("application/octet-stream".toMediaType()))
.addFormDataPart("text", "YOUR_TEXT_HERE")
.build()
val request = Request.Builder()
.url("https://api.deepai.org/api/image-editor")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build()
client.newCall(request).execute().use { response ->
println(response.body?.string())
}
}
Exemplos de Editor de fotos com IA em Rust
// Example posting a image URL:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("image", "YOUR_IMAGE_URL");
payload.insert("text", "YOUR_TEXT_HERE");
let response = client
.post("https://api.deepai.org/api/image-editor")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example posting a local image file:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
use reqwest::multipart;
use std::fs;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let form = multipart::Form::new()
.file("image", "/path/to/your/file.jpg")?
.text("text", "YOUR_TEXT_HERE");
let response = client
.post("https://api.deepai.org/api/image-editor")
.header("api-key", "YOUR_API_KEY")
.multipart(form)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
Exemplos de Editor de fotos com IA em TypeScript
// Example posting a image URL:
interface ApiResponse {
// Define your response type here
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/image-editor', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: 'YOUR_IMAGE_URL',
text: 'YOUR_TEXT_HERE',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
// Example posting a local image file (Node.js with form-data package):
// npm install form-data
import * as fs from 'fs';
import FormData from 'form-data';
interface ApiResponse {
[key: string]: unknown;
}
async function uploadFile(): Promise<ApiResponse> {
const formData = new FormData();
formData.append('image', fs.createReadStream('/path/to/your/file.jpg'));
formData.append('text', 'YOUR_TEXT_HERE');
const response = await fetch('https://api.deepai.org/api/image-editor', {
method: 'POST',
headers: {
...formData.getHeaders(),
'api-key': 'YOUR_API_KEY'
},
body: formData as unknown as BodyInit
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
uploadFile();
Exemplos de Editor de fotos com IA em Dart
// Example posting a image URL:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/image-editor'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'image': 'YOUR_IMAGE_URL',
'text': 'YOUR_TEXT_HERE',
}),
);
print(response.body);
}
// Example posting a local image file:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:io';
import 'package:http/http.dart' as http;
Future<void> main() async {
var request = http.MultipartRequest(
'POST',
Uri.parse('https://api.deepai.org/api/image-editor'),
);
request.headers['api-key'] = 'YOUR_API_KEY';
request.files.add(
await http.MultipartFile.fromPath('image', '/path/to/your/file.jpg'),
);
request.fields['text'] = 'YOUR_TEXT_HERE';
var response = await request.send();
var responseBody = await response.stream.bytesToString();
print(responseBody);
}
Exemplos de Editor de fotos com IA em PowerShell
# Example posting a image URL:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/image-editor `
-Method Post `
-Form @{
image='YOUR_IMAGE_URL'
text='YOUR_TEXT_HERE'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example posting a local image file:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/image-editor `
-Method Post `
-Form @{
image=Get-Item -Path '/path/to/your/file.jpg'
text='YOUR_TEXT_HERE'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
Dê cor a fotos antigas de família e imagens históricas, ou dê uma nova vida a um filme antigo com a colorização.
Endpoint: POST https://api.deepai.org/api/colorizer
| Parâmetro | Tipo | Obrigatório | Padrão |
|---|---|---|---|
image |
image | Sim | — |
Exemplos de Colorizador de imagens em cURL
# Example posting a image URL:
curl \
-F 'image=YOUR_IMAGE_URL' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/colorizer
# Example posting a local image file:
curl \
-F 'image=@/path/to/your/file.jpg' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/colorizer
Exemplos de Colorizador de imagens em Javascript
// Example posting a image URL:
(async function() {
const resp = await fetch('https://api.deepai.org/api/colorizer', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: "YOUR_IMAGE_URL",
})
});
const data = await resp.json();
console.log(data);
})()
// Example posting file picker input image (Browser only):
document.getElementById('yourFileInputId').addEventListener('change', async function() {
const formData = new FormData();
formData.append('image', this.files[0]);
const resp = await fetch('https://api.deepai.org/api/colorizer', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example posting a local image file (Node.js only):
const fs = require('fs');
(async function() {
const formData = new FormData();
const jpgFileStream = fs.createReadStream("/path/to/your/file.jpg");
formData.append('image', jpgFileStream);
const resp = await fetch('https://api.deepai.org/api/colorizer', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
Exemplos de Colorizador de imagens em Python
# Example posting a image URL:
import requests
r = requests.post(
"https://api.deepai.org/api/colorizer",
data={
'image': 'YOUR_IMAGE_URL',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example posting a local image file:
import requests
r = requests.post(
"https://api.deepai.org/api/colorizer",
files={
'image': open('/path/to/your/file.jpg', 'rb'),
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
Exemplos de Colorizador de imagens em Ruby
# Example posting a image URL:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/colorizer', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => 'YOUR_IMAGE_URL',
}
)
puts r
# Example posting a local image file:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/colorizer', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => File.new('/path/to/your/file.jpg'),
}
)
puts r
Exemplos de Colorizador de imagens em Php
// Example posting a image URL:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => 'YOUR_IMAGE_URL'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/colorizer', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example posting a local image file:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => Utils::tryFopen('/path/to/your/file.jpg', 'r')
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/colorizer', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
Exemplos de Colorizador de imagens em Go
// Example posting a image URL:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/colorizer"
payload := map[string]string{
"image": "YOUR_IMAGE_URL",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example posting a local image file:
package main
import (
"bytes"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
url := "https://api.deepai.org/api/colorizer"
var b bytes.Buffer
w := multipart.NewWriter(&b)
imageFile, _ := os.Open("/path/to/your/file.jpg")
defer imageFile.Close()
imageWriter, _ := w.CreateFormFile("image", "file.jpg")
io.Copy(imageWriter, imageFile)
if err := w.Close(); err != nil {
panic(err)
}
req, _ := http.NewRequest("POST", url, &b)
req.Header.Set("Content-Type", w.FormDataContentType())
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
Exemplos de Colorizador de imagens em Java
// Example posting a image URL:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"image\": \"YOUR_IMAGE_URL\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/colorizer"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
// Example posting a local image file:
// Add to build.gradle: implementation 'com.squareup.okhttp3:okhttp:4.12.0'
import okhttp3.*;
import java.io.File;
import java.io.IOException;
public class Main {
public static void main(String[] args) throws IOException {
OkHttpClient client = new OkHttpClient();
RequestBody requestBody = new MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", RequestBody.create(new File("/path/to/your/file.jpg"), MediaType.parse("application/octet-stream")))
.build();
Request request = new Request.Builder()
.url("https://api.deepai.org/api/colorizer")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}
}
}
Exemplos de Colorizador de imagens em C#
// Example posting a image URL:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
image = "YOUR_IMAGE_URL",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/colorizer", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example posting a local image file:
using System;
using System.IO;
using System.Net.Http;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
using var form = new MultipartFormDataContent();
var imageStream = File.OpenRead("/path/to/your/file.jpg");
form.Add(new StreamContent(imageStream), "image", "file.jpg");
var response = await client.PostAsync("https://api.deepai.org/api/colorizer", form);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
Exemplos de Colorizador de imagens em Swift
// Example posting a image URL:
import Foundation
let url = URL(string: "https://api.deepai.org/api/colorizer")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"image": "YOUR_IMAGE_URL",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
// Keep the program running for async request
RunLoop.main.run()
// Example posting a local image file:
import Foundation
let url = URL(string: "https://api.deepai.org/api/colorizer")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let boundary = UUID().uuidString
request.setValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")
var body = Data()
let imageData = try! Data(contentsOf: URL(fileURLWithPath: "/path/to/your/file.jpg"))
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"image\"; filename=\"file.jpg\"\r\n".data(using: .utf8)!)
body.append("Content-Type: application/octet-stream\r\n\r\n".data(using: .utf8)!)
body.append(imageData)
body.append("\r\n".data(using: .utf8)!)
body.append("--\(boundary)--\r\n".data(using: .utf8)!)
request.httpBody = body
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
Exemplos de Colorizador de imagens em Kotlin
// Example posting a image URL:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"image": "YOUR_IMAGE_URL"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/colorizer"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
// Example posting a local image file:
// Add to build.gradle.kts: implementation("com.squareup.okhttp3:okhttp:4.12.0")
import okhttp3.*
import okhttp3.MediaType.Companion.toMediaType
import okhttp3.RequestBody.Companion.asRequestBody
import java.io.File
fun main() {
val client = OkHttpClient()
val requestBody = MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", File("/path/to/your/file.jpg").asRequestBody("application/octet-stream".toMediaType()))
.build()
val request = Request.Builder()
.url("https://api.deepai.org/api/colorizer")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build()
client.newCall(request).execute().use { response ->
println(response.body?.string())
}
}
Exemplos de Colorizador de imagens em Rust
// Example posting a image URL:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("image", "YOUR_IMAGE_URL");
let response = client
.post("https://api.deepai.org/api/colorizer")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example posting a local image file:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
use reqwest::multipart;
use std::fs;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let form = multipart::Form::new()
.file("image", "/path/to/your/file.jpg")?;
let response = client
.post("https://api.deepai.org/api/colorizer")
.header("api-key", "YOUR_API_KEY")
.multipart(form)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
Exemplos de Colorizador de imagens em TypeScript
// Example posting a image URL:
interface ApiResponse {
// Define your response type here
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/colorizer', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: 'YOUR_IMAGE_URL',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
// Example posting a local image file (Node.js with form-data package):
// npm install form-data
import * as fs from 'fs';
import FormData from 'form-data';
interface ApiResponse {
[key: string]: unknown;
}
async function uploadFile(): Promise<ApiResponse> {
const formData = new FormData();
formData.append('image', fs.createReadStream('/path/to/your/file.jpg'));
const response = await fetch('https://api.deepai.org/api/colorizer', {
method: 'POST',
headers: {
...formData.getHeaders(),
'api-key': 'YOUR_API_KEY'
},
body: formData as unknown as BodyInit
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
uploadFile();
Exemplos de Colorizador de imagens em Dart
// Example posting a image URL:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/colorizer'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'image': 'YOUR_IMAGE_URL',
}),
);
print(response.body);
}
// Example posting a local image file:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:io';
import 'package:http/http.dart' as http;
Future<void> main() async {
var request = http.MultipartRequest(
'POST',
Uri.parse('https://api.deepai.org/api/colorizer'),
);
request.headers['api-key'] = 'YOUR_API_KEY';
request.files.add(
await http.MultipartFile.fromPath('image', '/path/to/your/file.jpg'),
);
var response = await request.send();
var responseBody = await response.stream.bytesToString();
print(responseBody);
}
Exemplos de Colorizador de imagens em PowerShell
# Example posting a image URL:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/colorizer `
-Method Post `
-Form @{
image='YOUR_IMAGE_URL'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example posting a local image file:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/colorizer `
-Method Post `
-Form @{
image=Get-Item -Path '/path/to/your/file.jpg'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
A API de super-resolução utiliza aprendizado de máquina para clarear, aumentar a nitidez e ampliar a foto sem perder seu conteúdo e suas características distintivas. Infelizmente, imagens desfocadas são comuns e representam um problema tanto para profissionais quanto para amadores. A super-resolução utiliza técnicas de aprendizado de máquina para ampliar imagens em uma fração de segundo.
Endpoint: POST https://api.deepai.org/api/torch-srgan
| Parâmetro | Tipo | Obrigatório | Padrão |
|---|---|---|---|
image |
image | Sim | — |
Exemplos de Super-resolução em cURL
# Example posting a image URL:
curl \
-F 'image=YOUR_IMAGE_URL' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/torch-srgan
# Example posting a local image file:
curl \
-F 'image=@/path/to/your/file.jpg' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/torch-srgan
Exemplos de Super-resolução em Javascript
// Example posting a image URL:
(async function() {
const resp = await fetch('https://api.deepai.org/api/torch-srgan', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: "YOUR_IMAGE_URL",
})
});
const data = await resp.json();
console.log(data);
})()
// Example posting file picker input image (Browser only):
document.getElementById('yourFileInputId').addEventListener('change', async function() {
const formData = new FormData();
formData.append('image', this.files[0]);
const resp = await fetch('https://api.deepai.org/api/torch-srgan', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example posting a local image file (Node.js only):
const fs = require('fs');
(async function() {
const formData = new FormData();
const jpgFileStream = fs.createReadStream("/path/to/your/file.jpg");
formData.append('image', jpgFileStream);
const resp = await fetch('https://api.deepai.org/api/torch-srgan', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
Exemplos de Super-resolução em Python
# Example posting a image URL:
import requests
r = requests.post(
"https://api.deepai.org/api/torch-srgan",
data={
'image': 'YOUR_IMAGE_URL',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example posting a local image file:
import requests
r = requests.post(
"https://api.deepai.org/api/torch-srgan",
files={
'image': open('/path/to/your/file.jpg', 'rb'),
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
Exemplos de Super-resolução em Ruby
# Example posting a image URL:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/torch-srgan', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => 'YOUR_IMAGE_URL',
}
)
puts r
# Example posting a local image file:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/torch-srgan', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => File.new('/path/to/your/file.jpg'),
}
)
puts r
Exemplos de Super-resolução em Php
// Example posting a image URL:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => 'YOUR_IMAGE_URL'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/torch-srgan', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example posting a local image file:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => Utils::tryFopen('/path/to/your/file.jpg', 'r')
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/torch-srgan', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
Exemplos de Super-resolução em Go
// Example posting a image URL:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/torch-srgan"
payload := map[string]string{
"image": "YOUR_IMAGE_URL",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example posting a local image file:
package main
import (
"bytes"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
url := "https://api.deepai.org/api/torch-srgan"
var b bytes.Buffer
w := multipart.NewWriter(&b)
imageFile, _ := os.Open("/path/to/your/file.jpg")
defer imageFile.Close()
imageWriter, _ := w.CreateFormFile("image", "file.jpg")
io.Copy(imageWriter, imageFile)
if err := w.Close(); err != nil {
panic(err)
}
req, _ := http.NewRequest("POST", url, &b)
req.Header.Set("Content-Type", w.FormDataContentType())
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
Exemplos de Super-resolução em Java
// Example posting a image URL:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"image\": \"YOUR_IMAGE_URL\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/torch-srgan"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
// Example posting a local image file:
// Add to build.gradle: implementation 'com.squareup.okhttp3:okhttp:4.12.0'
import okhttp3.*;
import java.io.File;
import java.io.IOException;
public class Main {
public static void main(String[] args) throws IOException {
OkHttpClient client = new OkHttpClient();
RequestBody requestBody = new MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", RequestBody.create(new File("/path/to/your/file.jpg"), MediaType.parse("application/octet-stream")))
.build();
Request request = new Request.Builder()
.url("https://api.deepai.org/api/torch-srgan")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}
}
}
Exemplos de Super-resolução em C#
// Example posting a image URL:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
image = "YOUR_IMAGE_URL",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/torch-srgan", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example posting a local image file:
using System;
using System.IO;
using System.Net.Http;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
using var form = new MultipartFormDataContent();
var imageStream = File.OpenRead("/path/to/your/file.jpg");
form.Add(new StreamContent(imageStream), "image", "file.jpg");
var response = await client.PostAsync("https://api.deepai.org/api/torch-srgan", form);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
Exemplos de Super-resolução em Swift
// Example posting a image URL:
import Foundation
let url = URL(string: "https://api.deepai.org/api/torch-srgan")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"image": "YOUR_IMAGE_URL",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
// Keep the program running for async request
RunLoop.main.run()
// Example posting a local image file:
import Foundation
let url = URL(string: "https://api.deepai.org/api/torch-srgan")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let boundary = UUID().uuidString
request.setValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")
var body = Data()
let imageData = try! Data(contentsOf: URL(fileURLWithPath: "/path/to/your/file.jpg"))
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"image\"; filename=\"file.jpg\"\r\n".data(using: .utf8)!)
body.append("Content-Type: application/octet-stream\r\n\r\n".data(using: .utf8)!)
body.append(imageData)
body.append("\r\n".data(using: .utf8)!)
body.append("--\(boundary)--\r\n".data(using: .utf8)!)
request.httpBody = body
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
Exemplos de Super-resolução em Kotlin
// Example posting a image URL:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"image": "YOUR_IMAGE_URL"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/torch-srgan"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
// Example posting a local image file:
// Add to build.gradle.kts: implementation("com.squareup.okhttp3:okhttp:4.12.0")
import okhttp3.*
import okhttp3.MediaType.Companion.toMediaType
import okhttp3.RequestBody.Companion.asRequestBody
import java.io.File
fun main() {
val client = OkHttpClient()
val requestBody = MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", File("/path/to/your/file.jpg").asRequestBody("application/octet-stream".toMediaType()))
.build()
val request = Request.Builder()
.url("https://api.deepai.org/api/torch-srgan")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build()
client.newCall(request).execute().use { response ->
println(response.body?.string())
}
}
Exemplos de Super-resolução em Rust
// Example posting a image URL:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("image", "YOUR_IMAGE_URL");
let response = client
.post("https://api.deepai.org/api/torch-srgan")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example posting a local image file:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
use reqwest::multipart;
use std::fs;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let form = multipart::Form::new()
.file("image", "/path/to/your/file.jpg")?;
let response = client
.post("https://api.deepai.org/api/torch-srgan")
.header("api-key", "YOUR_API_KEY")
.multipart(form)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
Exemplos de Super-resolução em TypeScript
// Example posting a image URL:
interface ApiResponse {
// Define your response type here
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/torch-srgan', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: 'YOUR_IMAGE_URL',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
// Example posting a local image file (Node.js with form-data package):
// npm install form-data
import * as fs from 'fs';
import FormData from 'form-data';
interface ApiResponse {
[key: string]: unknown;
}
async function uploadFile(): Promise<ApiResponse> {
const formData = new FormData();
formData.append('image', fs.createReadStream('/path/to/your/file.jpg'));
const response = await fetch('https://api.deepai.org/api/torch-srgan', {
method: 'POST',
headers: {
...formData.getHeaders(),
'api-key': 'YOUR_API_KEY'
},
body: formData as unknown as BodyInit
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
uploadFile();
Exemplos de Super-resolução em Dart
// Example posting a image URL:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/torch-srgan'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'image': 'YOUR_IMAGE_URL',
}),
);
print(response.body);
}
// Example posting a local image file:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:io';
import 'package:http/http.dart' as http;
Future<void> main() async {
var request = http.MultipartRequest(
'POST',
Uri.parse('https://api.deepai.org/api/torch-srgan'),
);
request.headers['api-key'] = 'YOUR_API_KEY';
request.files.add(
await http.MultipartFile.fromPath('image', '/path/to/your/file.jpg'),
);
var response = await request.send();
var responseBody = await response.stream.bytesToString();
print(responseBody);
}
Exemplos de Super-resolução em PowerShell
# Example posting a image URL:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/torch-srgan `
-Method Post `
-Form @{
image='YOUR_IMAGE_URL'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example posting a local image file:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/torch-srgan `
-Method Post `
-Form @{
image=Get-Item -Path '/path/to/your/file.jpg'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
O Waifu2x é um algoritmo que amplia imagens ao mesmo tempo em que reduz o ruído nelas. Seu nome vem da arte no estilo anime conhecida como “waifu”, com a qual foi amplamente treinado. Embora os waifus tenham constituído a maior parte dos dados de treinamento, essa API do Waifu2x ainda apresenta bom desempenho em fotografias e outros tipos de imagens. Você pode usar o Waifu2x para dobrar o tamanho das suas imagens e, ao mesmo tempo, reduzir o ruído.
Endpoint: POST https://api.deepai.org/api/waifu2x
| Parâmetro | Tipo | Obrigatório | Padrão |
|---|---|---|---|
image |
image | Sim | — |
Exemplos de Waifu2x em cURL
# Example posting a image URL:
curl \
-F 'image=YOUR_IMAGE_URL' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/waifu2x
# Example posting a local image file:
curl \
-F 'image=@/path/to/your/file.jpg' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/waifu2x
Exemplos de Waifu2x em Javascript
// Example posting a image URL:
(async function() {
const resp = await fetch('https://api.deepai.org/api/waifu2x', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: "YOUR_IMAGE_URL",
})
});
const data = await resp.json();
console.log(data);
})()
// Example posting file picker input image (Browser only):
document.getElementById('yourFileInputId').addEventListener('change', async function() {
const formData = new FormData();
formData.append('image', this.files[0]);
const resp = await fetch('https://api.deepai.org/api/waifu2x', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example posting a local image file (Node.js only):
const fs = require('fs');
(async function() {
const formData = new FormData();
const jpgFileStream = fs.createReadStream("/path/to/your/file.jpg");
formData.append('image', jpgFileStream);
const resp = await fetch('https://api.deepai.org/api/waifu2x', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
Exemplos de Waifu2x em Python
# Example posting a image URL:
import requests
r = requests.post(
"https://api.deepai.org/api/waifu2x",
data={
'image': 'YOUR_IMAGE_URL',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example posting a local image file:
import requests
r = requests.post(
"https://api.deepai.org/api/waifu2x",
files={
'image': open('/path/to/your/file.jpg', 'rb'),
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
Exemplos de Waifu2x em Ruby
# Example posting a image URL:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/waifu2x', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => 'YOUR_IMAGE_URL',
}
)
puts r
# Example posting a local image file:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/waifu2x', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => File.new('/path/to/your/file.jpg'),
}
)
puts r
Exemplos de Waifu2x em Php
// Example posting a image URL:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => 'YOUR_IMAGE_URL'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/waifu2x', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example posting a local image file:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => Utils::tryFopen('/path/to/your/file.jpg', 'r')
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/waifu2x', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
Exemplos de Waifu2x em Go
// Example posting a image URL:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/waifu2x"
payload := map[string]string{
"image": "YOUR_IMAGE_URL",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example posting a local image file:
package main
import (
"bytes"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
url := "https://api.deepai.org/api/waifu2x"
var b bytes.Buffer
w := multipart.NewWriter(&b)
imageFile, _ := os.Open("/path/to/your/file.jpg")
defer imageFile.Close()
imageWriter, _ := w.CreateFormFile("image", "file.jpg")
io.Copy(imageWriter, imageFile)
if err := w.Close(); err != nil {
panic(err)
}
req, _ := http.NewRequest("POST", url, &b)
req.Header.Set("Content-Type", w.FormDataContentType())
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
Exemplos de Waifu2x em Java
// Example posting a image URL:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"image\": \"YOUR_IMAGE_URL\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/waifu2x"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
// Example posting a local image file:
// Add to build.gradle: implementation 'com.squareup.okhttp3:okhttp:4.12.0'
import okhttp3.*;
import java.io.File;
import java.io.IOException;
public class Main {
public static void main(String[] args) throws IOException {
OkHttpClient client = new OkHttpClient();
RequestBody requestBody = new MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", RequestBody.create(new File("/path/to/your/file.jpg"), MediaType.parse("application/octet-stream")))
.build();
Request request = new Request.Builder()
.url("https://api.deepai.org/api/waifu2x")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}
}
}
Exemplos de Waifu2x em C#
// Example posting a image URL:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
image = "YOUR_IMAGE_URL",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/waifu2x", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example posting a local image file:
using System;
using System.IO;
using System.Net.Http;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
using var form = new MultipartFormDataContent();
var imageStream = File.OpenRead("/path/to/your/file.jpg");
form.Add(new StreamContent(imageStream), "image", "file.jpg");
var response = await client.PostAsync("https://api.deepai.org/api/waifu2x", form);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
Exemplos de Waifu2x em Swift
// Example posting a image URL:
import Foundation
let url = URL(string: "https://api.deepai.org/api/waifu2x")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"image": "YOUR_IMAGE_URL",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
// Keep the program running for async request
RunLoop.main.run()
// Example posting a local image file:
import Foundation
let url = URL(string: "https://api.deepai.org/api/waifu2x")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let boundary = UUID().uuidString
request.setValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")
var body = Data()
let imageData = try! Data(contentsOf: URL(fileURLWithPath: "/path/to/your/file.jpg"))
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"image\"; filename=\"file.jpg\"\r\n".data(using: .utf8)!)
body.append("Content-Type: application/octet-stream\r\n\r\n".data(using: .utf8)!)
body.append(imageData)
body.append("\r\n".data(using: .utf8)!)
body.append("--\(boundary)--\r\n".data(using: .utf8)!)
request.httpBody = body
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
Exemplos de Waifu2x em Kotlin
// Example posting a image URL:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"image": "YOUR_IMAGE_URL"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/waifu2x"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
// Example posting a local image file:
// Add to build.gradle.kts: implementation("com.squareup.okhttp3:okhttp:4.12.0")
import okhttp3.*
import okhttp3.MediaType.Companion.toMediaType
import okhttp3.RequestBody.Companion.asRequestBody
import java.io.File
fun main() {
val client = OkHttpClient()
val requestBody = MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", File("/path/to/your/file.jpg").asRequestBody("application/octet-stream".toMediaType()))
.build()
val request = Request.Builder()
.url("https://api.deepai.org/api/waifu2x")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build()
client.newCall(request).execute().use { response ->
println(response.body?.string())
}
}
Exemplos de Waifu2x em Rust
// Example posting a image URL:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("image", "YOUR_IMAGE_URL");
let response = client
.post("https://api.deepai.org/api/waifu2x")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example posting a local image file:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
use reqwest::multipart;
use std::fs;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let form = multipart::Form::new()
.file("image", "/path/to/your/file.jpg")?;
let response = client
.post("https://api.deepai.org/api/waifu2x")
.header("api-key", "YOUR_API_KEY")
.multipart(form)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
Exemplos de Waifu2x em TypeScript
// Example posting a image URL:
interface ApiResponse {
// Define your response type here
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/waifu2x', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: 'YOUR_IMAGE_URL',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
// Example posting a local image file (Node.js with form-data package):
// npm install form-data
import * as fs from 'fs';
import FormData from 'form-data';
interface ApiResponse {
[key: string]: unknown;
}
async function uploadFile(): Promise<ApiResponse> {
const formData = new FormData();
formData.append('image', fs.createReadStream('/path/to/your/file.jpg'));
const response = await fetch('https://api.deepai.org/api/waifu2x', {
method: 'POST',
headers: {
...formData.getHeaders(),
'api-key': 'YOUR_API_KEY'
},
body: formData as unknown as BodyInit
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
uploadFile();
Exemplos de Waifu2x em Dart
// Example posting a image URL:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/waifu2x'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'image': 'YOUR_IMAGE_URL',
}),
);
print(response.body);
}
// Example posting a local image file:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:io';
import 'package:http/http.dart' as http;
Future<void> main() async {
var request = http.MultipartRequest(
'POST',
Uri.parse('https://api.deepai.org/api/waifu2x'),
);
request.headers['api-key'] = 'YOUR_API_KEY';
request.files.add(
await http.MultipartFile.fromPath('image', '/path/to/your/file.jpg'),
);
var response = await request.send();
var responseBody = await response.stream.bytesToString();
print(responseBody);
}
Exemplos de Waifu2x em PowerShell
# Example posting a image URL:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/waifu2x `
-Method Post `
-Form @{
image='YOUR_IMAGE_URL'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example posting a local image file:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/waifu2x `
-Method Post `
-Form @{
image=Get-Item -Path '/path/to/your/file.jpg'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
Endpoint: POST https://api.deepai.org/api/creative-upscale
| Parâmetro | Tipo | Obrigatório | Padrão |
|---|---|---|---|
image |
image | Sim | — |
Exemplos de Ampliação criativa em cURL
# Example posting a image URL:
curl \
-F 'image=YOUR_IMAGE_URL' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/creative-upscale
# Example posting a local image file:
curl \
-F 'image=@/path/to/your/file.jpg' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/creative-upscale
Exemplos de Ampliação criativa em Javascript
// Example posting a image URL:
(async function() {
const resp = await fetch('https://api.deepai.org/api/creative-upscale', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: "YOUR_IMAGE_URL",
})
});
const data = await resp.json();
console.log(data);
})()
// Example posting file picker input image (Browser only):
document.getElementById('yourFileInputId').addEventListener('change', async function() {
const formData = new FormData();
formData.append('image', this.files[0]);
const resp = await fetch('https://api.deepai.org/api/creative-upscale', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example posting a local image file (Node.js only):
const fs = require('fs');
(async function() {
const formData = new FormData();
const jpgFileStream = fs.createReadStream("/path/to/your/file.jpg");
formData.append('image', jpgFileStream);
const resp = await fetch('https://api.deepai.org/api/creative-upscale', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
Exemplos de Ampliação criativa em Python
# Example posting a image URL:
import requests
r = requests.post(
"https://api.deepai.org/api/creative-upscale",
data={
'image': 'YOUR_IMAGE_URL',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example posting a local image file:
import requests
r = requests.post(
"https://api.deepai.org/api/creative-upscale",
files={
'image': open('/path/to/your/file.jpg', 'rb'),
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
Exemplos de Ampliação criativa em Ruby
# Example posting a image URL:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/creative-upscale', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => 'YOUR_IMAGE_URL',
}
)
puts r
# Example posting a local image file:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/creative-upscale', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'image' => File.new('/path/to/your/file.jpg'),
}
)
puts r
Exemplos de Ampliação criativa em Php
// Example posting a image URL:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => 'YOUR_IMAGE_URL'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/creative-upscale', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example posting a local image file:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'image',
'contents' => Utils::tryFopen('/path/to/your/file.jpg', 'r')
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/creative-upscale', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
Exemplos de Ampliação criativa em Go
// Example posting a image URL:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/creative-upscale"
payload := map[string]string{
"image": "YOUR_IMAGE_URL",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example posting a local image file:
package main
import (
"bytes"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
url := "https://api.deepai.org/api/creative-upscale"
var b bytes.Buffer
w := multipart.NewWriter(&b)
imageFile, _ := os.Open("/path/to/your/file.jpg")
defer imageFile.Close()
imageWriter, _ := w.CreateFormFile("image", "file.jpg")
io.Copy(imageWriter, imageFile)
if err := w.Close(); err != nil {
panic(err)
}
req, _ := http.NewRequest("POST", url, &b)
req.Header.Set("Content-Type", w.FormDataContentType())
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
Exemplos de Ampliação criativa em Java
// Example posting a image URL:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"image\": \"YOUR_IMAGE_URL\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/creative-upscale"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
// Example posting a local image file:
// Add to build.gradle: implementation 'com.squareup.okhttp3:okhttp:4.12.0'
import okhttp3.*;
import java.io.File;
import java.io.IOException;
public class Main {
public static void main(String[] args) throws IOException {
OkHttpClient client = new OkHttpClient();
RequestBody requestBody = new MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", RequestBody.create(new File("/path/to/your/file.jpg"), MediaType.parse("application/octet-stream")))
.build();
Request request = new Request.Builder()
.url("https://api.deepai.org/api/creative-upscale")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}
}
}
Exemplos de Ampliação criativa em C#
// Example posting a image URL:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
image = "YOUR_IMAGE_URL",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/creative-upscale", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example posting a local image file:
using System;
using System.IO;
using System.Net.Http;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
using var form = new MultipartFormDataContent();
var imageStream = File.OpenRead("/path/to/your/file.jpg");
form.Add(new StreamContent(imageStream), "image", "file.jpg");
var response = await client.PostAsync("https://api.deepai.org/api/creative-upscale", form);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
Exemplos de Ampliação criativa em Swift
// Example posting a image URL:
import Foundation
let url = URL(string: "https://api.deepai.org/api/creative-upscale")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"image": "YOUR_IMAGE_URL",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
// Keep the program running for async request
RunLoop.main.run()
// Example posting a local image file:
import Foundation
let url = URL(string: "https://api.deepai.org/api/creative-upscale")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let boundary = UUID().uuidString
request.setValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")
var body = Data()
let imageData = try! Data(contentsOf: URL(fileURLWithPath: "/path/to/your/file.jpg"))
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"image\"; filename=\"file.jpg\"\r\n".data(using: .utf8)!)
body.append("Content-Type: application/octet-stream\r\n\r\n".data(using: .utf8)!)
body.append(imageData)
body.append("\r\n".data(using: .utf8)!)
body.append("--\(boundary)--\r\n".data(using: .utf8)!)
request.httpBody = body
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
Exemplos de Ampliação criativa em Kotlin
// Example posting a image URL:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"image": "YOUR_IMAGE_URL"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/creative-upscale"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
// Example posting a local image file:
// Add to build.gradle.kts: implementation("com.squareup.okhttp3:okhttp:4.12.0")
import okhttp3.*
import okhttp3.MediaType.Companion.toMediaType
import okhttp3.RequestBody.Companion.asRequestBody
import java.io.File
fun main() {
val client = OkHttpClient()
val requestBody = MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("image", "file.jpg", File("/path/to/your/file.jpg").asRequestBody("application/octet-stream".toMediaType()))
.build()
val request = Request.Builder()
.url("https://api.deepai.org/api/creative-upscale")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build()
client.newCall(request).execute().use { response ->
println(response.body?.string())
}
}
Exemplos de Ampliação criativa em Rust
// Example posting a image URL:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("image", "YOUR_IMAGE_URL");
let response = client
.post("https://api.deepai.org/api/creative-upscale")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example posting a local image file:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
use reqwest::multipart;
use std::fs;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let form = multipart::Form::new()
.file("image", "/path/to/your/file.jpg")?;
let response = client
.post("https://api.deepai.org/api/creative-upscale")
.header("api-key", "YOUR_API_KEY")
.multipart(form)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
Exemplos de Ampliação criativa em TypeScript
// Example posting a image URL:
interface ApiResponse {
// Define your response type here
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/creative-upscale', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
image: 'YOUR_IMAGE_URL',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
// Example posting a local image file (Node.js with form-data package):
// npm install form-data
import * as fs from 'fs';
import FormData from 'form-data';
interface ApiResponse {
[key: string]: unknown;
}
async function uploadFile(): Promise<ApiResponse> {
const formData = new FormData();
formData.append('image', fs.createReadStream('/path/to/your/file.jpg'));
const response = await fetch('https://api.deepai.org/api/creative-upscale', {
method: 'POST',
headers: {
...formData.getHeaders(),
'api-key': 'YOUR_API_KEY'
},
body: formData as unknown as BodyInit
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
uploadFile();
Exemplos de Ampliação criativa em Dart
// Example posting a image URL:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/creative-upscale'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'image': 'YOUR_IMAGE_URL',
}),
);
print(response.body);
}
// Example posting a local image file:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:io';
import 'package:http/http.dart' as http;
Future<void> main() async {
var request = http.MultipartRequest(
'POST',
Uri.parse('https://api.deepai.org/api/creative-upscale'),
);
request.headers['api-key'] = 'YOUR_API_KEY';
request.files.add(
await http.MultipartFile.fromPath('image', '/path/to/your/file.jpg'),
);
var response = await request.send();
var responseBody = await response.stream.bytesToString();
print(responseBody);
}
Exemplos de Ampliação criativa em PowerShell
# Example posting a image URL:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/creative-upscale `
-Method Post `
-Form @{
image='YOUR_IMAGE_URL'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example posting a local image file:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/creative-upscale `
-Method Post `
-Form @{
image=Get-Item -Path '/path/to/your/file.jpg'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
Substitua e edite objetos em imagens com IA.
Endpoint: POST https://api.deepai.org/api/image-replace
| Parâmetro | Tipo | Obrigatório | Padrão |
|---|---|---|---|
image |
image | Sim | — |
mask |
image | Sim | — |
text |
text | Sim | — |
Exemplos de Substituição de imagem em cURL
# Example posting a image URL:
curl \
-F 'text=YOUR_TEXT_HERE' \
-F 'mask=YOUR_IMAGE_URL' \
-F 'image=YOUR_IMAGE_URL' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/image-replace
# Example posting a local image file:
curl \
-F 'text=YOUR_TEXT_HERE' \
-F 'mask=@/path/to/your/file.jpg' \
-F 'image=@/path/to/your/file.jpg' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/image-replace
# Example directly sending a text string:
curl \
-F 'text=YOUR_TEXT_HERE' \
-F 'mask=YOUR_TEXT_HERE' \
-F 'image=YOUR_TEXT_HERE' \
-H 'api-key:YOUR_API_KEY' \
https://api.deepai.org/api/image-replace
Exemplos de Substituição de imagem em Javascript
// Example posting a image URL:
(async function() {
const resp = await fetch('https://api.deepai.org/api/image-replace', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
text: "YOUR_TEXT_HERE",
mask: "YOUR_IMAGE_URL",
image: "YOUR_IMAGE_URL",
})
});
const data = await resp.json();
console.log(data);
})()
// Example posting file picker input image (Browser only):
document.getElementById('yourFileInputId').addEventListener('change', async function() {
const formData = new FormData();
formData.append('text', 'YOUR_TEXT_HERE');
formData.append('mask', this.files[0]);
formData.append('image', this.files[1]);
const resp = await fetch('https://api.deepai.org/api/image-replace', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example posting a local image file (Node.js only):
const fs = require('fs');
(async function() {
const formData = new FormData();
formData.append('text', 'YOUR_TEXT_HERE');
const jpgFileStream = fs.createReadStream("/path/to/your/file.jpg");
formData.append('mask', jpgFileStream);
const jpgFileStream = fs.createReadStream("/path/to/your/file.jpg");
formData.append('image', jpgFileStream);
const resp = await fetch('https://api.deepai.org/api/image-replace', {
method: 'POST',
headers: {
'api-key': 'YOUR_API_KEY'
},
body: formData
});
const data = await resp.json();
console.log(data);
});
// Example directly sending a text string:
(async function() {
const resp = await fetch('https://api.deepai.org/api/image-replace', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
text: "YOUR_TEXT_HERE",
mask: "YOUR_TEXT_HERE",
image: "YOUR_TEXT_HERE",
})
});
const data = await resp.json();
console.log(data);
})()
Exemplos de Substituição de imagem em Python
# Example posting a image URL:
import requests
r = requests.post(
"https://api.deepai.org/api/image-replace",
data={
'text': 'YOUR_TEXT_HERE',
'mask': 'YOUR_IMAGE_URL',
'image': 'YOUR_IMAGE_URL',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example posting a local image file:
import requests
r = requests.post(
"https://api.deepai.org/api/image-replace",
files={
'mask': open('/path/to/your/file.jpg', 'rb'),
'image': open('/path/to/your/file.jpg', 'rb'),
},
data={
'text': 'YOUR_TEXT_HERE',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
# Example directly sending a text string:
import requests
r = requests.post(
"https://api.deepai.org/api/image-replace",
data={
'text': 'YOUR_TEXT_HERE',
'mask': 'YOUR_TEXT_HERE',
'image': 'YOUR_TEXT_HERE',
},
headers={'api-key': 'YOUR_API_KEY'}
)
print(r.json())
Exemplos de Substituição de imagem em Ruby
# Example posting a image URL:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/image-replace', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'text' => 'YOUR_TEXT_HERE',
'mask' => 'YOUR_IMAGE_URL',
'image' => 'YOUR_IMAGE_URL',
}
)
puts r
# Example posting a local image file:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/image-replace', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'text' => 'YOUR_TEXT_HERE',
'mask' => File.new('/path/to/your/file.jpg'),
'image' => File.new('/path/to/your/file.jpg'),
}
)
puts r
# Example directly sending a text string:
require 'rest_client'
r = RestClient::Request.execute(method: :post, url: 'https://api.deepai.org/api/image-replace', timeout: 600,
headers: {'api-key' => 'YOUR_API_KEY'},
payload: {
'text' => 'YOUR_TEXT_HERE',
'mask' => 'YOUR_TEXT_HERE',
'image' => 'YOUR_TEXT_HERE',
}
)
puts r
Exemplos de Substituição de imagem em Php
// Example posting a image URL:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'text',
'contents' => 'YOUR_TEXT_HERE'
],
[
'name' => 'mask',
'contents' => 'YOUR_IMAGE_URL'
],
[
'name' => 'image',
'contents' => 'YOUR_IMAGE_URL'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/image-replace', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example posting a local image file:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'text',
'contents' => 'YOUR_TEXT_HERE'
],
[
'name' => 'mask',
'contents' => Utils::tryFopen('/path/to/your/file.jpg', 'r')
],
[
'name' => 'image',
'contents' => Utils::tryFopen('/path/to/your/file.jpg', 'r')
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/image-replace', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
// Example directly sending a text string:
<?php
require 'vendor/autoload.php'; // Ensure you have Guzzle installed (composer require guzzlehttp/guzzle)
use GuzzleHttp\Client;
use GuzzleHttp\Psr7\Utils;
$client = new Client();
$headers = [
'api-key' => 'YOUR_API_KEY'
];
$options = [
'multipart' => [
[
'name' => 'text',
'contents' => 'YOUR_TEXT_HERE'
],
[
'name' => 'mask',
'contents' => 'YOUR_TEXT_HERE'
],
[
'name' => 'image',
'contents' => 'YOUR_TEXT_HERE'
],
]
];
$request = new GuzzleHttp\Psr7\Request('POST', 'https://api.deepai.org/api/image-replace', $headers);
try {
$res = $client->sendAsync($request, $options)->wait();
echo $res->getBody();
} catch (Exception $e) {
echo 'Error: ' . $e->getMessage();
}
?>
Exemplos de Substituição de imagem em Go
// Example posting a image URL:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/image-replace"
payload := map[string]string{
"text": "YOUR_TEXT_HERE",
"mask": "YOUR_IMAGE_URL",
"image": "YOUR_IMAGE_URL",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example posting a local image file:
package main
import (
"bytes"
"fmt"
"io"
"mime/multipart"
"net/http"
"os"
)
func main() {
url := "https://api.deepai.org/api/image-replace"
var b bytes.Buffer
w := multipart.NewWriter(&b)
w.WriteField("text", "YOUR_TEXT_HERE")
maskFile, _ := os.Open("/path/to/your/file.jpg")
defer maskFile.Close()
maskWriter, _ := w.CreateFormFile("mask", "file.jpg")
io.Copy(maskWriter, maskFile)
imageFile, _ := os.Open("/path/to/your/file.jpg")
defer imageFile.Close()
imageWriter, _ := w.CreateFormFile("image", "file.jpg")
io.Copy(imageWriter, imageFile)
if err := w.Close(); err != nil {
panic(err)
}
req, _ := http.NewRequest("POST", url, &b)
req.Header.Set("Content-Type", w.FormDataContentType())
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
// Example directly sending a text string:
package main
import (
"bytes"
"encoding/json"
"fmt"
"io"
"net/http"
)
func main() {
url := "https://api.deepai.org/api/image-replace"
payload := map[string]string{
"text": "YOUR_TEXT_HERE",
"mask": "YOUR_TEXT_HERE",
"image": "YOUR_TEXT_HERE",
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Content-Type", "application/json")
req.Header.Set("api-key", "YOUR_API_KEY")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := io.ReadAll(resp.Body)
fmt.Println(string(body))
}
Exemplos de Substituição de imagem em Java
// Example posting a image URL:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"text\": \"YOUR_TEXT_HERE\"" +
"\"mask\": \"YOUR_IMAGE_URL\"" +
"\"image\": \"YOUR_IMAGE_URL\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/image-replace"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
// Example posting a local image file:
// Add to build.gradle: implementation 'com.squareup.okhttp3:okhttp:4.12.0'
import okhttp3.*;
import java.io.File;
import java.io.IOException;
public class Main {
public static void main(String[] args) throws IOException {
OkHttpClient client = new OkHttpClient();
RequestBody requestBody = new MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("text", "YOUR_TEXT_HERE")
.addFormDataPart("mask", "file.jpg", RequestBody.create(new File("/path/to/your/file.jpg"), MediaType.parse("application/octet-stream")))
.addFormDataPart("image", "file.jpg", RequestBody.create(new File("/path/to/your/file.jpg"), MediaType.parse("application/octet-stream")))
.build();
Request request = new Request.Builder()
.url("https://api.deepai.org/api/image-replace")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build();
try (Response response = client.newCall(request).execute()) {
System.out.println(response.body().string());
}
}
}
// Example directly sending a text string:
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
HttpClient client = HttpClient.newHttpClient();
String json = "{" +
"\"text\": \"YOUR_TEXT_HERE\"" +
"\"mask\": \"YOUR_TEXT_HERE\"" +
"\"image\": \"YOUR_TEXT_HERE\"" +
"}";
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/image-replace"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
Exemplos de Substituição de imagem em C#
// Example posting a image URL:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
text = "YOUR_TEXT_HERE",
mask = "YOUR_IMAGE_URL",
image = "YOUR_IMAGE_URL",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/image-replace", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example posting a local image file:
using System;
using System.IO;
using System.Net.Http;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
using var form = new MultipartFormDataContent();
form.Add(new StringContent("YOUR_TEXT_HERE"), "text");
var maskStream = File.OpenRead("/path/to/your/file.jpg");
form.Add(new StreamContent(maskStream), "mask", "file.jpg");
var imageStream = File.OpenRead("/path/to/your/file.jpg");
form.Add(new StreamContent(imageStream), "image", "file.jpg");
var response = await client.PostAsync("https://api.deepai.org/api/image-replace", form);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
// Example directly sending a text string:
using System;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Threading.Tasks;
class Program
{
static async Task Main()
{
using var client = new HttpClient();
client.DefaultRequestHeaders.Add("api-key", "YOUR_API_KEY");
var payload = new
{
text = "YOUR_TEXT_HERE",
mask = "YOUR_TEXT_HERE",
image = "YOUR_TEXT_HERE",
};
var json = JsonSerializer.Serialize(payload);
var content = new StringContent(json, Encoding.UTF8, "application/json");
var response = await client.PostAsync("https://api.deepai.org/api/image-replace", content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
}
}
Exemplos de Substituição de imagem em Swift
// Example posting a image URL:
import Foundation
let url = URL(string: "https://api.deepai.org/api/image-replace")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"text": "YOUR_TEXT_HERE",
"mask": "YOUR_IMAGE_URL",
"image": "YOUR_IMAGE_URL",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
// Keep the program running for async request
RunLoop.main.run()
// Example posting a local image file:
import Foundation
let url = URL(string: "https://api.deepai.org/api/image-replace")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let boundary = UUID().uuidString
request.setValue("multipart/form-data; boundary=\(boundary)", forHTTPHeaderField: "Content-Type")
var body = Data()
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"text\"\r\n\r\n".data(using: .utf8)!)
body.append("YOUR_TEXT_HERE".data(using: .utf8)!)
body.append("\r\n".data(using: .utf8)!)
let maskData = try! Data(contentsOf: URL(fileURLWithPath: "/path/to/your/file.jpg"))
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"mask\"; filename=\"file.jpg\"\r\n".data(using: .utf8)!)
body.append("Content-Type: application/octet-stream\r\n\r\n".data(using: .utf8)!)
body.append(maskData)
body.append("\r\n".data(using: .utf8)!)
let imageData = try! Data(contentsOf: URL(fileURLWithPath: "/path/to/your/file.jpg"))
body.append("--\(boundary)\r\n".data(using: .utf8)!)
body.append("Content-Disposition: form-data; name=\"image\"; filename=\"file.jpg\"\r\n".data(using: .utf8)!)
body.append("Content-Type: application/octet-stream\r\n\r\n".data(using: .utf8)!)
body.append(imageData)
body.append("\r\n".data(using: .utf8)!)
body.append("--\(boundary)--\r\n".data(using: .utf8)!)
request.httpBody = body
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
// Example directly sending a text string:
import Foundation
let url = URL(string: "https://api.deepai.org/api/image-replace")!
var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.setValue("YOUR_API_KEY", forHTTPHeaderField: "api-key")
let payload: [String: Any] = [
"text": "YOUR_TEXT_HERE",
"mask": "YOUR_TEXT_HERE",
"image": "YOUR_TEXT_HERE",
]
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)
let task = URLSession.shared.dataTask(with: request) { data, response, error in
if let data = data {
print(String(data: data, encoding: .utf8) ?? "")
}
}
task.resume()
RunLoop.main.run()
Exemplos de Substituição de imagem em Kotlin
// Example posting a image URL:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"text": "YOUR_TEXT_HERE",
"mask": "YOUR_IMAGE_URL",
"image": "YOUR_IMAGE_URL"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/image-replace"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
// Example posting a local image file:
// Add to build.gradle.kts: implementation("com.squareup.okhttp3:okhttp:4.12.0")
import okhttp3.*
import okhttp3.MediaType.Companion.toMediaType
import okhttp3.RequestBody.Companion.asRequestBody
import java.io.File
fun main() {
val client = OkHttpClient()
val requestBody = MultipartBody.Builder()
.setType(MultipartBody.FORM)
.addFormDataPart("text", "YOUR_TEXT_HERE")
.addFormDataPart("mask", "file.jpg", File("/path/to/your/file.jpg").asRequestBody("application/octet-stream".toMediaType()))
.addFormDataPart("image", "file.jpg", File("/path/to/your/file.jpg").asRequestBody("application/octet-stream".toMediaType()))
.build()
val request = Request.Builder()
.url("https://api.deepai.org/api/image-replace")
.addHeader("api-key", "YOUR_API_KEY")
.post(requestBody)
.build()
client.newCall(request).execute().use { response ->
println(response.body?.string())
}
}
// Example directly sending a text string:
import java.net.URI
import java.net.http.HttpClient
import java.net.http.HttpRequest
import java.net.http.HttpResponse
fun main() {
val client = HttpClient.newHttpClient()
val json = """{
"text": "YOUR_TEXT_HERE",
"mask": "YOUR_TEXT_HERE",
"image": "YOUR_TEXT_HERE"
}"""
val request = HttpRequest.newBuilder()
.uri(URI.create("https://api.deepai.org/api/image-replace"))
.header("Content-Type", "application/json")
.header("api-key", "YOUR_API_KEY")
.POST(HttpRequest.BodyPublishers.ofString(json))
.build()
val response = client.send(request, HttpResponse.BodyHandlers.ofString())
println(response.body())
}
Exemplos de Substituição de imagem em Rust
// Example posting a image URL:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("text", "YOUR_TEXT_HERE");
payload.insert("mask", "YOUR_IMAGE_URL");
payload.insert("image", "YOUR_IMAGE_URL");
let response = client
.post("https://api.deepai.org/api/image-replace")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example posting a local image file:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
use reqwest::multipart;
use std::fs;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let form = multipart::Form::new()
.text("text", "YOUR_TEXT_HERE")
.file("mask", "/path/to/your/file.jpg")?
.file("image", "/path/to/your/file.jpg")?;
let response = client
.post("https://api.deepai.org/api/image-replace")
.header("api-key", "YOUR_API_KEY")
.multipart(form)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
// Example directly sending a text string:
// Add to Cargo.toml: reqwest = { version = "0.11", features = ["json", "multipart"] }
// tokio = { version = "1", features = ["full"] }
// serde_json = "1"
use reqwest::header::HeaderMap;
use std::collections::HashMap;
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let client = reqwest::Client::new();
let mut headers = HeaderMap::new();
headers.insert("api-key", "YOUR_API_KEY".parse()?);
let mut payload = HashMap::new();
payload.insert("text", "YOUR_TEXT_HERE");
payload.insert("mask", "YOUR_TEXT_HERE");
payload.insert("image", "YOUR_TEXT_HERE");
let response = client
.post("https://api.deepai.org/api/image-replace")
.headers(headers)
.json(&payload)
.send()
.await?;
println!("{}", response.text().await?);
Ok(())
}
Exemplos de Substituição de imagem em TypeScript
// Example posting a image URL:
interface ApiResponse {
// Define your response type here
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/image-replace', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
text: 'YOUR_TEXT_HERE',
mask: 'YOUR_IMAGE_URL',
image: 'YOUR_IMAGE_URL',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
// Example posting a local image file (Node.js with form-data package):
// npm install form-data
import * as fs from 'fs';
import FormData from 'form-data';
interface ApiResponse {
[key: string]: unknown;
}
async function uploadFile(): Promise<ApiResponse> {
const formData = new FormData();
formData.append('text', 'YOUR_TEXT_HERE');
formData.append('mask', fs.createReadStream('/path/to/your/file.jpg'));
formData.append('image', fs.createReadStream('/path/to/your/file.jpg'));
const response = await fetch('https://api.deepai.org/api/image-replace', {
method: 'POST',
headers: {
...formData.getHeaders(),
'api-key': 'YOUR_API_KEY'
},
body: formData as unknown as BodyInit
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
uploadFile();
// Example directly sending a text string:
interface ApiResponse {
[key: string]: unknown;
}
async function callApi(): Promise<ApiResponse> {
const response = await fetch('https://api.deepai.org/api/image-replace', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY'
},
body: JSON.stringify({
text: 'YOUR_TEXT_HERE',
mask: 'YOUR_TEXT_HERE',
image: 'YOUR_TEXT_HERE',
})
});
const data: ApiResponse = await response.json();
console.log(data);
return data;
}
callApi();
Exemplos de Substituição de imagem em Dart
// Example posting a image URL:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/image-replace'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'text': 'YOUR_TEXT_HERE',
'mask': 'YOUR_IMAGE_URL',
'image': 'YOUR_IMAGE_URL',
}),
);
print(response.body);
}
// Example posting a local image file:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:io';
import 'package:http/http.dart' as http;
Future<void> main() async {
var request = http.MultipartRequest(
'POST',
Uri.parse('https://api.deepai.org/api/image-replace'),
);
request.headers['api-key'] = 'YOUR_API_KEY';
request.fields['text'] = 'YOUR_TEXT_HERE';
request.files.add(
await http.MultipartFile.fromPath('mask', '/path/to/your/file.jpg'),
);
request.files.add(
await http.MultipartFile.fromPath('image', '/path/to/your/file.jpg'),
);
var response = await request.send();
var responseBody = await response.stream.bytesToString();
print(responseBody);
}
// Example directly sending a text string:
// Add to pubspec.yaml: http: ^1.1.0
import 'dart:convert';
import 'package:http/http.dart' as http;
Future<void> main() async {
final response = await http.post(
Uri.parse('https://api.deepai.org/api/image-replace'),
headers: {
'Content-Type': 'application/json',
'api-key': 'YOUR_API_KEY',
},
body: jsonEncode({
'text': 'YOUR_TEXT_HERE',
'mask': 'YOUR_TEXT_HERE',
'image': 'YOUR_TEXT_HERE',
}),
);
print(response.body);
}
Exemplos de Substituição de imagem em PowerShell
# Example posting a image URL:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/image-replace `
-Method Post `
-Form @{
text='YOUR_TEXT_HERE'
mask='YOUR_IMAGE_URL'
image='YOUR_IMAGE_URL'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example posting a local image file:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/image-replace `
-Method Post `
-Form @{
text='YOUR_TEXT_HERE'
mask=Get-Item -Path '/path/to/your/file.jpg'
image=Get-Item -Path '/path/to/your/file.jpg'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
# Example directly sending a text string:
$r = Invoke-WebRequest `
-Uri https://api.deepai.org/api/image-replace `
-Method Post `
-Form @{
text='YOUR_TEXT_HERE'
mask='YOUR_TEXT_HERE'
image='YOUR_TEXT_HERE'
} `
-Headers @{
'api-key'='YOUR_API_KEY'
}
$r.Content
Use sua Conta do Google para fazer login no DeepAI