python cli tracking machine-learning computer-vision deep-learning hub pytorch yolo image-classification object-detection pose-estimation instance-segmentation ultralytics rotated-object-detection yolov8 segment-anything yolo-world yolov10 yolo11 Updated Apr 10, 2025 Python NickSwardh / YoloDotNet Star...
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中提出来 ️! FAQ (Frequently Asked Questions) 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 everyo...
python tools/reparameterize_yoloworld.py \ --model path/to/checkpoint \ --out-dir path/to/save/re-parameterized/ \ --text-embed path/to/text/embeddings \ --conv-neck 3. Prepare the model config Please see the sample config:finetune_coco/yolo_world_v2_s_rep_vlpan_bn_2e-4_80e_8gpus...
论文代码:github.com/AILab-CVC/YO 在线体验:huggingface.co/spaces/s 亮点解读:开放词汇对象检测(支持任意英文文本,检测出目标框) 一句话速读:YOLO-World通过引入RepVL-PAN和区域-文本对比损失,实现了高效的零样本开放词汇对象检测,并在LVIS数据集上达到了35.4 AP和52.0 FPS的性能。 图1. 速度与精度曲线。我们在...
#install key dependenciespip install mmdetection==3.0.0 mmengine transformers#clone the repogit clone https://xxxx.YOLO-World.gitcdYOLO-World#install mmyolomkdir third_party git clone https://github.com/open-mmlab/mmyolo.gitcd.. 2. Preparing Data ...
YOLO-World is developed based ontorch==1.11.0mmyolo==0.6.0andmmdetection==3.0.0. #install key dependenciespip install mmdetection==3.0.0 mmengine transformers#clone the repogit clone https://xxxx.YOLO-World.gitcdYOLO-World#install mmyolomkdir third_party git clone https://github.com/open-mm...
🍊 Jupyter Notebook ColabInfo YOLO_World_gradio_jupyter 🧬 Code https://github.com/AILab-CVC/YOLO-World 📄 Paper https://arxiv.org/abs/2401.17270 🌐 Page https://www.yoloworld.cc/ 🖼 Output 🏢 Sponsor https://replicate.comAbout...
Export YOLO-World to ONNX models You can also useexport_onnx.pyto obtain the ONNX model. You might specify the--custom-textwith your ownText JSONfor your custom prompts. The format ofText JSONcan be found indocs/data. PYTHONPATH=./ python deploy/export_onnx.py path/to/config path/to...
2024年1月31日,腾讯人工智能实验室发布了其突破性模型,名为YOLO-World,这是一款先进的工具,能够在实时环境中跨越开放词汇表识别对象,无需先前的训练。 YOLO-World通过简单的提示输入,实现对任何对象的识别。要访问该模型,请访问YOLO-World的GitHub页面。
YOLO-Worldgithub.com/AILab-CVC/YOLO-World 该代码中包含submodule,需要使用下述命令下载,如果你使用的是下载zip包,那么需要在网页端进入third_party/mmyolo下载对应commit的压缩包,然后解压到本地对应路径。如果是git clone可以用下面命令: git clone --recursive https://github.com/AILab-CVC/YOLO-World.git...