yolo-world资料（源码+文档）

<div align="center"> <img src="./assets/yolo_logo.png" width=60%> <br> <a href="https://scholar.google.com/citations?hl=zh-CN&user=PH8rJHYAAAAJ">Tianheng Cheng</a>^{<span>2,3,*</span>}, <a href="https://linsong.info/">Lin Song</a>^{<span>1,📧,*</span>}, <a href="https://yxgeee.github.io/">Yixiao Ge</a>^{<span>1,🌟,2</span>}, <a href="http://eic.hust.edu.cn/professor/liuwenyu/"> Wenyu Liu</a>^{<span>3</span>}, <a href="https://xwcv.github.io/">Xinggang Wang</a>^{<span>3,📧</span>}, <a href="https://scholar.google.com/citations?user=4oXBp9UAAAAJ&hl=en">Ying Shan</a>^{<span>1,2</span>} </br> \* Equal contribution 🌟 Project lead 📧 Corresponding author ¹ Tencent AI Lab, ² ARC Lab, Tencent PCG ³ Huazhong University of Science and Technology <br> <div> [](https://wondervictor.github.io/) [](https://arxiv.org/abs/2401.17270) <a href="https://colab.research.google.com/github/AILab-CVC/YOLO-World/blob/master/inference.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> [](https://huggingface.co/spaces/stevengrove/YOLO-World) [](https://replicate.com/zsxkib/yolo-world) [](https://huggingface.co/papers/2401.17270) [](LICENSE) [](https://huggingface.co/spaces/SkalskiP/YOLO-World) [](https://supervision.roboflow.com/develop/notebooks/zero-shot-object-detection-with-yolo-world) [](https://inference.roboflow.com/foundation/yolo_world/) </div> </div> ## Notice We recommend that everyone **use English to communicate on issues**, as this helps developers from around the world discuss, share experiences, and answer questions together. For business licensing and other related inquiries, don't hesitate to contact `yixiaoge@tencent.com`. ## 🔥 Updates `[2024-7-8]`: YOLO-World now has been integrated into [ComfyUI](https://github.com/StevenGrove/ComfyUI-YOLOWorld)! Come and try adding YOLO-World to your workflow now! You can access it at [StevenGrove/ComfyUI-YOLOWorld](https://github.com/StevenGrove/ComfyUI-YOLOWorld)! `[2024-5-18]:` YOLO-World models have been [integrated with the FiftyOne computer vision toolkit](https://docs.voxel51.com/integrations/ultralytics.html#open-vocabulary-detection) for streamlined open-vocabulary inference across image and video datasets. `[2024-5-16]:` Hey guys! Long time no see! This update contains (1) [fine-tuning guide](https://github.com/AILab-CVC/YOLO-World?#highlights--introduction) and (2) [TFLite Export](./docs/tflite_deploy.md) with INT8 Quantization. `[2024-5-9]:` This update contains the real [`reparameterization`](./docs/reparameterize.md) 🪄, and it's better for fine-tuning on custom datasets and improves the training/inference efficiency 🚀! `[2024-4-28]:` Long time no see! This update contains bugfixs and improvements: (1) ONNX demo; (2) image demo (support tensor input); (2) new pre-trained models; (3) image prompts; (4) simple version for fine-tuning / deployment; (5) guide for installation (include a `requirements.txt`). `[2024-3-28]:` We provide: (1) more high-resolution pre-trained models (e.g., S, M, X) ([#142](https://github.com/AILab-CVC/YOLO-World/issues/142)); (2) pre-trained models with CLIP-Large text encoders. Most importantly, we preliminarily fix the **fine-tuning without `mask-refine`** and explore a new fine-tuning setting ([#160](https://github.com/AILab-CVC/YOLO-World/issues/160),[#76](https://github.com/AILab-CVC/YOLO-World/issues/76)). In addition, fine-tuning YOLO-World with `mask-refine` also obtains significant improvements, check more details in [configs/finetune_coco](./configs/finetune_coco/). `[2024-3-16]:` We fix the bugs about the demo ([#110](https://github.com/AILab-CVC/YOLO-World/issues/110),[#94](https://github.com/AILab-CVC/YOLO-World/issues/94),[#129](https://github.com/AILab-CVC/YOLO-World/issues/129), [#125](https://github.com/AILab-CVC/YOLO-World/issues/125)) with visualizations of segmentation masks, and release [**YOLO-World with Embeddings**](./docs/prompt_yolo_world.md), which supports prompt tuning, text prompts and image prompts. `[2024-3-3]:` We add the **high-resolution YOLO-World**, which supports `1280x1280` resolution with higher accuracy and better performance for small objects! `[2024-2-29]:` We release the newest version of [ **YOLO-World-v2**](./docs/updates.md) with higher accuracy and faster speed! We hope the community can join us to improve YOLO-World! `[2024-2-28]:` Excited to announce that YOLO-World has been accepted by **CVPR 2024**! We're continuing to make YOLO-World faster and stronger, as well as making it better to use for all. `[2024-2-22]:` We sincerely thank [RoboFlow](https://roboflow.com/) and [@Skalskip92](https://twitter.com/skalskip92) for the [**Video Guide**](https://www.youtube.com/watch?v=X7gKBGVz4vs) about YOLO-World, nice work! `[2024-2-18]:` We thank [@Skalskip92](https://twitter.com/skalskip92) for developing the wonderful segmentation demo via connecting YOLO-World and EfficientSAM. You can try it now at the [🤗 HuggingFace Spaces](https://huggingface.co/spaces/SkalskiP/YOLO-World). `[2024-2-17]:` The largest model **X** of YOLO-World is released, which achieves better zero-shot performance! `[2024-2-17]:` We release the code & models for **YOLO-World-Seg** now! YOLO-World now supports open-vocabulary / zero-shot object segmentation! `[2024-2-15]:` The pre-traind YOLO-World-L with CC3M-Lite is released! `[2024-2-14]:` We provide the [`image_demo`](demo.py) for inference on images or directories. `[2024-2-10]:` We provide the [fine-tuning](./docs/finetuning.md) and [data](./docs/data.md) details for fine-tuning YOLO-World on the COCO dataset or the custom datasets! `[2024-2-3]:` We support the `Gradio` demo now in the repo and you can build the YOLO-World demo on your own device! `[2024-2-1]:` We've released the code and weights of YOLO-World now! `[2024-2-1]:` We deploy the YOLO-World demo on [HuggingFace 🤗](https://huggingface.co/spaces/stevengrove/YOLO-World), you can try it now! `[2024-1-31]:` We are excited to launch **YOLO-World**, a cutting-edge real-time open-vocabulary object detector. ## TODO YOLO-World is under active development and please stay tuned ☕️! If you have suggestions📃 or ideas💡,**we would love for you to bring them up in the [Roadmap](https://github.com/AILab-CVC/YOLO-World/issues/109)** ❤️! > YOLO-World 目前正在积极开发中📃，如果你有建议或者想法💡，**我们非常希望您在 [Roadmap](https://github.com/AILab-CVC/YOLO-World/issues/109) 中提出来** ❤️！ ## [FAQ (Frequently Asked Questions)](https://github.com/AILab-CVC/YOLO-World/discussions/149) We have set up an FAQ about YOLO-World in the discussion on GitHub. We hope everyone can raise issues or solutions during use here, and we also hope that everyone can quickly find solutions from it. > 我们在GitHub的discussion中建立了关于YOLO-World的常见问答，这里将收集一些常见问题，同时大家可以在此提出使用中的问题或者解决方案，也希望大家能够从中快速寻找到解决方案 ## Highlights & Introduction This repo contains the PyTorch implementation, pre-trained weights, and pre-training/fine-tuning code for YOLO-World. * YOLO-World is pre-trained on large-scale datasets, including dete