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Update model_zoo and replace css log
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@ -72,7 +72,7 @@ The master branch works with **PyTorch 1.6+**.
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## What's New
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**v0.1.0** was released on 20/9/2022:
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**v0.1.0** was released on 21/9/2022:
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- Unified component interfaces based on [OpenMMLab 2.0](https://github.com/open-mmlab) and [MMDetection 3.0](https://github.com/open-mmlab/mmdetection/tree/3.x)
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- Support for YOLOv5/YOLOX training and deployment, support for YOLOv6 inference and deployment
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@ -72,7 +72,7 @@ MMYOLO 是一个基于 PyTorch 的 YOLO 系列算法开源工具箱。它是 [Op
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## 最新进展
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**v0.1.0** 版本已经在 2022.9.20 发布:
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**v0.1.0** 版本已经在 2022.9.21 发布:
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- 基于 [OpenMMLab 2.0](https://github.com/open-mmlab) 和 [MMDetection 3.0](https://github.com/open-mmlab/mmdetection/tree/3.x) 统一了各组件接口。
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- 支持 YOLOv5/YOLOX 训练和部署,支持 YOLOv6 推理和部署
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.header-logo {
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background-image: url("../image/mmdet-logo.png");
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background-image: url("../image/mmyolo-logo.png");
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background-size: 156px 40px;
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height: 40px;
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width: 156px;
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# Benchmark and Model Zoo
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## Common settings
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- All models were trained on `coco_2017_train`, and tested on the `coco_2017_val`.
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- We use distributed training.
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## Baselines
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### YOLOv5
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Please refer to [YOLOv5](https://github.com/open-mmlab/mmyolo/blob/main/configs/yolov5)。
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### YOLOv6
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Please refer to [YOLOv6](https://github.com/open-mmlab/mmyolo/blob/main/configs/yolov6)。
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### YOLOX
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Please refer to [YOLOX](https://github.com/open-mmlab/mmyolo/blob/main/configs/yolox)。
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# Changelog
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## v0.1.0(20/9/2022)
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## v0.1.0(21/9/2022)
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We have released MMYOLO open source library, which is based on MMEngine, MMCV 2.x and MMDetection 3.x libraries. At present, the object detection has been realized, and it will be expanded to multi-task in the future.
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.header-logo {
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background-image: url("../image/mmdet-logo.png");
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background-image: url("../image/mmyolo-logo.png");
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background-size: 156px 40px;
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height: 40px;
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width: 156px;
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# 更新日志
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## v0.1.0(20/9/2022)
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## v0.1.0(21/9/2022)
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我们发布了 MMYOLO 开源库,其基于 MMEngine, MMCV 2.x 和 MMDetection 3.x 库. 目前实现了目标检测功能,后续会扩展为多任务。
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