JoyAI-Image-Ed

About

What JoyAI-Image-Ed is

[](https://joyai-image.s3.cn-north-1.jdcloud-oss.com/JoyAI-Image.pdf) [](https://github.com/jd-opensource/JoyAI-Image) [](https://huggingface.co/jdopensource/JoyAI-Image-Edit-Diffusers)&#160; [](https://modelscope.cn/models/jd-opensource/JoyAI-Image-Edit-Diffusers)&#160; [](https://huggingface.co/spaces/stevengrove/JoyAI-Image-Edit-Space)&#160; [](LICENSE) 🐶 JoyAI-Image-Edit JoyAI-Image-Edit is a multimodal foundation model specialized in instruction-guided image editing. It enables precise and controllable edits by leveraging strong spatial understanding, including scene parsing, relational grounding, and instruction decomposition, allowing complex modifications to be applied accurately to specified regions. 🚀 Quick Start Requirements: Python = 3.10, CUDA-capable GPU Install Note: JoyImageEditPipeline will be included in the next official diffusers release (0.38.0). Until then, install from source as shown above. Running with Diffusers More Usages Spatial Editing Reference JoyAI-Image supports three spatial editing prompt patterns: Object Move, Object Rotation, and Camera Control. For the most stable behavior, we recommend following the prompt templates below as closely as possible. 1. Object Move Use this pattern when you want to move a target object into a specified region. Prompt template: Rules: Replace <object with a clear description of the target object to be moved. The red box indicates the target destination in the image. The phrase "finally remove the red box" means the guidance box should not appear in the final edited result. Example: 2. Object Rotation Use this pattern when you want to rotate an object to a specific canonical view. Prompt template: Supported <view values: front right left rear front right front left rear right rear left Rules: Replace <object with a clear description of the object to rotate. Replace <view with one of the supported directions above. This instruction is intended to change the object orientation, while keeping the object identity and surrounding scene as consistent as possible. Examples: 3. Camera Control Use this pattern when you want to change only the camera viewpoint while keeping the 3D scene itself unchanged. Pr

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

How image models work

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys joyai-image-ed for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (joyai-image-ed below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"joyai-image-ed","prompt":"a red bicycle","size":"1024x1024"}'

Details

Languages, data & research

Licence

Open weights

Sources

Weights & code

Explore

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