bytedance/seedream-v4/edit-sequential

gambar-ke-gambar

Seedream v4 Edit Sequential API by ByteDance

bytedance/seedream-v4/edit-sequential

Edit-sequential

Open and Advanced Large-Scale Image Generative Models.

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 $0.027 per eksekusi. Dengan $10 Anda dapat menjalankan model ini sekitar 370 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": "bytedance/seedream-v4/edit-sequential",
    "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 dependensi yang diperlukan.

pip install requests

Autentikasi

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

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

HTTP Headers

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": "bytedance/seedream-v4/edit-sequential",
    "prompt": "A beautiful landscape with mountains and lake"
}

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

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

Respons

{
  "code": 200,
  "data": {
    "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

{
  "model": "bytedance/seedream-v4/edit-sequential"
}

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

{
  "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

npx skills add AtlasCloudAI/atlas-cloud-skills

Atur API Key

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

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

npx -y atlascloud-mcp

Konfigurasi

Tambahkan konfigurasi berikut ke file pengaturan MCP di IDE Anda.

{
  "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 terbaik 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

Memuat...

Sorotan Model

Dilengkapi lima kemampuan inti: Pengeditan Instruksi Presisi, Preservasi Fitur Tinggi, Pemahaman Niat Mendalam, Multi-Image I/O, dan Resolusi Ultra HD. Mencakup beragam skenario kreatif, menghadirkan setiap inspirasi secara instan dengan kualitas tinggi.

Pengeditan Instruksi Presisi

Cukup deskripsikan kebutuhan Anda dalam bahasa sehari-hari untuk menjalankan operasi tambah, hapus, ubah, dan ganti secara akurat. Mendukung aplikasi di desain komersial, kreasi seni, dan hiburan.

Preservasi Fitur Tinggi

Konsistensi Karakter:Mempertahankan fitur karakter secara konsisten di berbagai gaya kreasi (ilustrasi/3D/fotografi), menjaga kreasi selalu terkendali

Preservasi Adegan:Memaksimalkan detail gambar asli, tanpa khawatir rasa "AI berminyak" setelah pengeditan, menghasilkan pengeditan tanpa kehilangan kualitas

Pemahaman Niat Mendalam

Peningkatan Pengetahuan:Basis pengetahuan tingkat ahli, membawa pemahaman teks ke level berikutnya

Materialisasi Inspirasi:Dari abstrak ke konkret, mewujudkan inspirasi "liar" menjadi kenyataan

Penalaran Prediktif:Kemampuan penalaran yang lebih kuat, mensimulasikan prediksi lintas waktu dan ruang, membuat yang tak terlihat menjadi terlihat

Rasio Adaptif:Saat diaktifkan, secara otomatis mencocokkan rasio aspek terbaik untuk gambar Anda

Input/Output Multi-Gambar

Masukkan beberapa gambar sekaligus, mendukung operasi pengeditan kompleks seperti kombinasi, migrasi, penggantian, dan derivasi, untuk menghasilkan sintesis tingkat tinggi

Resolusi Ultra HD

Resolusi kembali ditingkatkan, mendukung output ultra-definisi tinggi untuk kualitas gambar tingkat profesional

Skenario Aplikasi

🎨

Desain Komersial

🖼️

Kreasi Seni

📸

Pengeditan Foto

🎮

Aset Game

👤

Desain Karakter

🏗️

Visualisasi Arsitektur

📱

Media Sosial

🎬

Film & Animasi

Precision Editing

Perspective & Composition Control

Transform camera angles, adjust scene distance, and modify aspect ratios with precision

Prompt Template

Change the camera angle from eye-level to bird's-eye view, adjust the scene from close-up to medium shot, and convert the image aspect ratio to 16:9. Maintain all original elements and lighting while adapting the composition for the new perspective and format.

Text & Formula Generation

Mathematical Whiteboard Creation

Generate clean whiteboard with precise mathematical formulas and equations

Prompt Template

Create a clean white whiteboard with the following mathematical equations written in clear, professional handwriting: E=mc², √(9)=3, and the quadratic formula (-b±√(b²-4ac))/2a. Use black or dark blue marker style, with proper spacing and mathematical notation.

Deep Intent Understanding

Sketch to Reality Transformation

Transform rough sketches into detailed realistic objects - bringing wild imagination to life

Prompt Template

Based on this rough sketch, generate a vintage television set from the 1950s-60s era. Transform the abstract lines and shapes into a realistic, detailed old-style TV with wooden cabinet, rounded screen, control knobs, and period-appropriate design elements. Make the vague concept concrete and lifelike.

High Feature Preservation

Lossless Detail Enhancement

Maximize original image detail retention, avoiding AI-generated artifacts for truly lossless editing

Prompt Template

Enhance this image while maximizing the preservation of original details. Avoid any AI-generated 'plastic' or 'oily' artifacts. Maintain authentic textures, natural lighting, and original image characteristics. Focus on clean, lossless enhancement that respects the source material's integrity.

Text Transformation

Creative Font Styling

Transform plain text into artistic, creative typography while maintaining readability

Prompt Template

Transform all the text in this image into creative, artistic fonts. Replace the standard typography with stylized lettering that matches the image's aesthetic - use decorative fonts, calligraphy styles, or artistic text treatments. Maintain the same text content and layout while making the typography more visually appealing and creative.

Kemampuan Inti

Pembuatan

Kreasi Teks-ke-Gambar

Kemampuan pemahaman teks dan pembuatan gambar yang canggih, mendukung berbagai gaya artistik dan kebutuhan profesional, dari konsep hingga karya akhir dalam satu langkah.

Pengeditan

Pengeditan Gambar Cerdas

Perintah pengeditan berbasis bahasa natural, mendukung penambahan/penghapusan objek, transfer gaya, penggantian latar belakang, dan operasi pengeditan kompleks lainnya.

Sintesis

Komposisi Multi-Gambar

Kemampuan input multi-gambar yang revolusioner, memungkinkan sintesis gambar kompleks, migrasi gaya, dan kombinasi kreatif dengan kontrol yang belum pernah ada sebelumnya.

Mengapa Memilih Seedream 4.0?

🚀

Solusi All-in-One

Satu model menangani pembuatan, pengeditan, dan komposisi - tidak perlu berpindah antara berbagai alat

🎯

Kualitas Profesional

Kualitas output tingkat komersial dengan kontrol presisi atas setiap detail

🔄

Gaya yang Konsisten

Mempertahankan konsistensi karakter dan gaya di berbagai generasi dan pengeditan

Spesifikasi Teknis

Arsitektur Model:Didukung oleh ByteDance Doubao AI

Fitur Inti:Integrasi Generasi + Pengeditan

Dukungan Resolusi:Output Ultra HD

Dukungan Input:Teks, Gambar Tunggal/Multi-Gambar

Format Output:PNG, JPEG, WebP

Integrasi API:RESTful API dengan Dukungan SDK

Rasakan Kekuatan Seedream 4.0

Bergabunglah dengan para kreator di seluruh dunia untuk merevolusi kreasi konten visual dengan model AI gambar terintegrasi paling canggih dari ByteDance.

✨Alat Profesional

⚡Sangat Cepat

🌐Platform All-in-One

Seedream 4: A next-generation multimodal image generation system developed by ByteDance Seed

Model Card Overview

Field	Description
Model Name	Seedream 4
Developed by	ByteDance Seed Team
Release Date	September 9, 2025
Model Type	Multimodal Image Generation
Related Links	Official Website, Technical Report (arXiv), GitHub Organization (ByteDance-Seed)

Introduction

Seedream 4 is a powerful, efficient, and high-performance multimodal image generation system that unifies text-to-image (T2I) synthesis, image editing, and multi-image composition within a single, integrated framework. Engineered for scalability and efficiency, the model introduces a novel diffusion transformer (DiT) architecture combined with a powerful Variational Autoencoder (VAE). This design enables the fast generation of native high-resolution images up to 4K, while significantly reducing computational requirements compared to its predecessors.

The primary goal of Seedream 4 is to extend traditional T2I systems into a more interactive and multidimensional creative tool. It is designed to handle complex tasks involving precise image editing, in-context reasoning, and multi-image referencing, pushing the boundaries of generative AI for both creative and professional applications.

Key Features & Innovations

Seedream 4 introduces several key advancements in image generation technology:

Unified Multimodal Architecture: It integrates T2I generation, image editing, and multi-image composition into a single model, allowing for seamless transitions between different creative workflows.
Efficient and Scalable Design: The model features a highly efficient DiT backbone and a high-compression VAE, achieving over 10x inference acceleration compared to Seedream 3.0 while delivering superior performance. This architecture is hardware-friendly and easily scalable.
Ultra-Fast, High-Resolution Output: Seedream 4 can generate native high-resolution images (from 1K to 4K) in as little as 1.4 to 1.8 seconds for a 2K image, greatly enhancing user interaction and production efficiency.
Advanced Multimodal Capabilities: The model excels at complex tasks such as precise, instruction-based image editing, in-context reasoning, and generating new images by blending elements from multiple reference images.
Professional and Knowledge-Based Content Generation: Beyond artistic imagery, Seedream 4 can generate structured and knowledge-based content, including charts, mathematical formulas, and professional design materials, bridging the gap between creative expression and practical application.
Advanced Training and Acceleration: The model is pre-trained on billions of text-image pairs and utilizes a multi-stage post-training process (CT, SFT, RLHF) to enhance its capabilities. Inference is accelerated through a combination of adversarial distillation, quantization, and speculative decoding.

Model Architecture & Technical Details

Seedream 4's architecture is a significant leap forward, focusing on efficiency and power. The core components are a diffusion transformer (DiT) and a Variational Autoencoder (VAE).

Pre-training Data: Billions of text-image pairs, including a specialized pipeline for knowledge-related data like instructional images and formulas.
Training Strategy: A multi-stage approach, starting at a 512x512 resolution and fine-tuning at higher resolutions up to 4K.
Post-training: A joint multi-task process involving Continuing Training (CT), Supervised Fine-Tuning (SFT), and Reinforcement Learning from Human Feedback (RLHF) to enhance instruction following and alignment.
Inference Acceleration: A holistic system combining an adversarial learning framework, hardware-aware quantization (adaptive 4/8-bit), and speculative decoding.

Intended Use & Applications

Seedream 4 is designed for a wide range of creative and professional applications, moving beyond simple image generation to become a comprehensive visual content creation tool.

Creative Content Generation: Creating high-quality, artistic images, illustrations, and concept art from text prompts.
Advanced Image Editing: Performing complex edits on existing images using natural language instructions, such as adding or removing objects, changing styles, and modifying backgrounds.
Design and Marketing: Generating professional design materials, product mockups, and marketing visuals with precise control over text and branding elements.
Educational and Technical Content: Creating structured, knowledge-based visuals like diagrams, charts, and mathematical formulas for educational or technical documentation.
Multi-Image Composition: Blending elements from multiple source images to create new compositions, such as virtual try-ons for fashion or combining characters with new scenes.

Performance

Seedream 4 has demonstrated state-of-the-art performance on both internal and public benchmarks as of September 18, often outperforming other leading models in text-to-image and image editing tasks.

MagicBench (Internal Benchmark)

Task	Performance Summary
Text-to-Image	Achieved high scores in prompt following, aesthetics, and text-rendering.
Single-Image Editing	Showed a good balance between prompt following and alignment with the source image.

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Satu API untuk semua AI multimedia.

Jelajahi semua model

Seedream v4 Edit Sequential API by ByteDance

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

Seedream 4.0 - Model Kreasi Visual All-in-One ByteDance

Sorotan Model

Pengeditan Instruksi Presisi

Preservasi Fitur Tinggi

Pemahaman Niat Mendalam

Input/Output Multi-Gambar

Resolusi Ultra HD

Skenario Aplikasi

Prompt Examples & Creative Templates

Perspective & Composition Control

Mathematical Whiteboard Creation

Sketch to Reality Transformation

Lossless Detail Enhancement

Creative Font Styling

Kemampuan Inti

Mengapa Memilih Seedream 4.0?

Solusi All-in-One

Kualitas Profesional

Gaya yang Konsisten

Spesifikasi Teknis

Rasakan Kekuatan Seedream 4.0

Seedream 4: A next-generation multimodal image generation system developed by ByteDance Seed

Model Card Overview

Introduction

Key Features & Innovations

Model Architecture & Technical Details

Intended Use & Applications

Performance

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Seedream v4.5 Sequential

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Seedream v4

Seedream v4 Sequential

Seedream v4 Edit

Openai GPT Image 2 Text-to-Image

Openai GPT Image 2 Edit

GPT Image 2 Developer Edit

GPT Image 2 Developer Text-to-Image

Satu API untuk semua AI multimedia.