openai/gpt-image-1/edit

gambar-ke-gambar

Openai GPT Image 1 Edit API by OpenAI

openai/gpt-image-1/edit

Edit

OpenAI's gpt-image-1 enables image generation and image editing via OpenAI's image API, ideal for creating and refining images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

INPUT

Memuat konfigurasi parameter...

OUTPUT

Menunggu

Gambar yang dihasilkan akan muncul di sini

Konfigurasikan pengaturan Anda dan klik Jalankan untuk memulai

Permintaan Anda akan dikenakan biaya $0.009 per eksekusi. Dengan $10 Anda dapat menjalankan model ini sekitar 1111 kali.

Berikut yang dapat Anda lakukan selanjutnya:

Gambar ke Video Gambar ke Gambar

Parameter

Contoh kode
import requests
import time

# Step 1: Start image generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "openai/gpt-image-1/edit",
    "prompt": "A beautiful landscape with mountains and lake",
    "width": 512,
    "height": 512,
    "steps": 20,
    "guidance_scale": 7.5,
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] == "completed":
            print("Generated image:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

image_url = check_status()

Instalasi

Instal paket yang diperlukan untuk bahasa pemrograman Anda.

bash

pip install requests

Autentikasi

Semua permintaan API memerlukan autentikasi melalui API key. Anda bisa mendapatkan API key dari dasbor Atlas Cloud.

bash

export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP Headers

python

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Jaga keamanan API key Anda

Jangan pernah mengekspos API key Anda di kode sisi klien atau repositori publik. Gunakan variabel lingkungan atau proxy backend sebagai gantinya.

Kirim permintaan

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Kirim Permintaan

Kirim permintaan pembuatan asinkron. API mengembalikan prediction ID yang dapat Anda gunakan untuk memeriksa status dan mengambil hasil.

POST/api/v1/model/generateImage

Isi Permintaan

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateImage"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "openai/gpt-image-1/edit",
    "input": {
        "prompt": "A beautiful landscape with mountains and lake"
    }
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['id']}")
print(f"Status: {result['status']}")

Respons

{
  "id": "pred_abc123",
  "status": "processing",
  "model": "model-name",
  "created_at": "2025-01-01T00:00:00Z"
}

Periksa Status

Polling prediction endpoint untuk memeriksa status permintaan Anda saat ini.

GET/api/v1/model/prediction/{prediction_id}

Contoh Polling

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Nilai Status

processingPermintaan masih diproses.

completedPembuatan selesai. Output tersedia.

succeededPembuatan berhasil. Output tersedia.

failedPembuatan gagal. Periksa field error.

Respons Selesai

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.png"
    ],
    "metrics": {
      "predict_time": 8.3
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Unggah File

Unggah file ke penyimpanan Atlas Cloud dan dapatkan URL yang dapat Anda gunakan dalam permintaan API Anda. Gunakan multipart/form-data untuk mengunggah.

POST/api/v1/model/uploadMedia

Contoh Unggah

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Respons

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

Parameter berikut diterima di isi permintaan.

Total: 0Wajib: 0Opsional: 0

Tidak ada parameter yang tersedia.

Contoh Isi Permintaan

json

{
  "model": "openai/gpt-image-1/edit"
}

Output Schema

API mengembalikan respons prediction dengan URL output yang dihasilkan.

idstringrequired

Unique identifier for the prediction.

statusstringrequired

Current status of the prediction.

processingcompletedsucceededfailed

modelstringrequired

The model used for generation.

outputsarray[string]

Array of output URLs. Available when status is "completed".

errorstring

Error message if status is "failed".

metricsobject

Performance metrics.

predict_timenumber

Time taken for image generation in seconds.

created_atstringrequired

ISO 8601 timestamp when the prediction was created.

Format: date-time

completed_atstring

ISO 8601 timestamp when the prediction was completed.

Format: date-time

Contoh Respons

json

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.png"
  ],
  "metrics": {
    "predict_time": 8.3
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills mengintegrasikan 300+ model AI langsung ke asisten pengkodean AI Anda. Satu perintah untuk menginstal, lalu gunakan bahasa alami untuk menghasilkan gambar, video, dan mengobrol dengan LLM.

Klien yang Didukung

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ klien yang didukung

Instalasi

bash

npx skills add AtlasCloudAI/atlas-cloud-skills

Atur API Key

Dapatkan API key dari dasbor Atlas Cloud dan atur sebagai variabel lingkungan.

bash

export ATLASCLOUD_API_KEY="your-api-key-here"

Kemampuan

Setelah diinstal, Anda dapat menggunakan bahasa alami di asisten AI Anda untuk mengakses semua model Atlas Cloud.

Pembuatan GambarBuat gambar dengan model seperti Nano Banana 2, Z-Image, dan lainnya.

Pembuatan VideoBuat video dari teks atau gambar dengan Kling, Vidu, Veo, dll.

Obrolan LLMMengobrol dengan Qwen, DeepSeek, dan model bahasa besar lainnya.

Unggah MediaUnggah file lokal untuk pengeditan gambar dan alur kerja gambar-ke-video.

Pelajari lebih lanjut

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server menghubungkan IDE Anda dengan 300+ model AI melalui Model Context Protocol. Berfungsi dengan klien apa pun yang kompatibel dengan MCP.

Klien yang Didukung

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ klien yang didukung

Instalasi

bash

npx -y atlascloud-mcp

Konfigurasi

Tambahkan konfigurasi berikut ke file pengaturan MCP di IDE Anda.

json

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Alat yang Tersedia

atlas_generate_imageBuat gambar dari prompt teks.

atlas_generate_videoBuat video dari teks atau gambar.

atlas_chatMengobrol dengan model bahasa besar.

atlas_list_modelsJelajahi 300+ model AI yang tersedia.

atlas_quick_generatePembuatan konten satu langkah dengan pemilihan model otomatis.

atlas_upload_mediaUnggah file lokal untuk alur kerja API.

Pelajari lebih lanjut

github.com/AtlasCloudAI/mcp-server

Schema API

Schema tidak tersedia

Tidak ada contoh yang tersedia

Silakan masuk untuk melihat riwayat permintaan

Anda perlu masuk untuk mengakses riwayat permintaan model Anda.

Masuk

OpenAI GPT-Image-1-Edit

Edit and transform images with natural language using OpenAI's GPT-Image-1-Edit. This versatile model understands your instructions to apply style changes, modifications, and creative transformations — with optional mask support for precise regional editing and multiple quality tiers to match your needs and budget.

Why It Looks Great

Natural language editing: Describe transformations in plain text — style changes, modifications, enhancements.
Mask support: Use mask images for precise control over which areas to edit.
Quality tiers: Choose from low, medium, or high quality based on your needs.
Multiple sizes: Output in square (1024x1024) or rectangular (1024x1536, 1536x1024) formats.
Style transformation: Excels at converting images to different artistic styles.
OpenAI quality: Powered by advanced vision-language understanding.

Parameters

Parameter	Required	Description
`prompt`	Yes	Text instruction describing the edit or transformation you want.
`image`	Yes	Source image to edit (upload or public URL).
`quality`	No	Output quality: `low`, `medium`, or `high`. Default: `medium`.
`mask_image`	No	Optional mask to specify edit regions (upload or URL).
`size`	No	Output dimensions: `1024x1024`, `1024x1536`, or `1536x1024`.
`enable_sync_mode`	No	API only: Waits for result and returns it directly.
`enable_base64_output`	No	API only: Returns base64 string instead of URL.

How to Use

Write your edit instruction — describe the transformation you want (e.g. "Become a comic style").
Upload your image — drag and drop or paste a public URL.
Choose quality — select low, medium, or high based on your needs.
Add mask (optional) — upload a mask image to limit edits to specific areas.
Select size — choose your desired output dimensions.
Run — click the button to apply the edit.
Download — preview and save your transformed image.

Quick Reference

Quality	1024x1024	1024x1536 / 1536x1024
Low	$0.011	$0.016
Medium	$0.042	$0.063
High	$0.167	$0.250

Best Use Cases

Style Transfer — Convert photos to comic, cartoon, painting, or other artistic styles.
Creative Transformation — Reimagine images with different aesthetics or themes.
Regional Editing — Use masks to edit specific areas while preserving the rest.
Content Enhancement — Improve or modify specific aspects of images.
Artistic Interpretation — Transform photos into various art forms.

Example Prompts

"Become a comic style"
"Transform into a watercolor painting"
"Make it look like a vintage photograph from the 1950s"
"Convert to anime style illustration"
"Apply a cyberpunk neon aesthetic"
"Turn into a pencil sketch"

Quality Guide

Quality	Best For	Trade-off
Low	Quick previews, testing concepts, high-volume processing	Fastest, most affordable, lower detail
Medium	General use, social media, balanced needs	Good quality/cost balance
High	Professional work, final deliverables, maximum detail	Highest quality, premium price

Pro Tips for Best Results

Start with medium quality to test your prompt, then upgrade to high for final output.
Use masks when you want to preserve specific areas untouched.
Be specific about the target style — "comic style", "oil painting", "anime".
For style transfers, simpler source images often produce cleaner results.
Rectangular sizes work well for portraits (1024x1536) or landscapes (1536x1024).
The model interprets style instructions creatively — embrace the artistic interpretation.

Notes

If using URLs for images or masks, ensure they are publicly accessible.
The enable_sync_mode and enable_base64_output options are only available through the API.
Mask images should be black and white, where white indicates areas to edit.
Processing time varies by quality level — higher quality takes longer.

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Openai GPT Image 1 Edit API by OpenAI

INPUT

OUTPUT

Parameter

Contoh kode

Instalasi

Autentikasi

HTTP Headers

Kirim permintaan

Kirim Permintaan

Isi Permintaan

Respons

Periksa Status

Contoh Polling

Nilai Status

Respons Selesai

Unggah File

Contoh Unggah

Respons

Input Schema

Contoh Isi Permintaan

Output Schema

Contoh Respons

Atlas Cloud Skills

Klien yang Didukung

Instalasi

Atur API Key

Kemampuan

MCP Server

Klien yang Didukung

Instalasi

Konfigurasi

Alat yang Tersedia

Schema API

Silakan masuk untuk melihat riwayat permintaan

OpenAI GPT-Image-1-Edit

Why It Looks Great

Parameters

How to Use

Quick Reference

Best Use Cases

Example Prompts

Quality Guide

Pro Tips for Best Results

Notes

Jelajahi Model Serupa

Openai GPT Image-1.5 Text-to-image

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Openai GPT Image-1 Mini Text-to-image

Mulai dari 300+ Model,

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