Feng Wang
commited on
Commit
·
c6a8f30
1
Parent(s):
00c03e1
chore(docs): provide github download (#84)
Browse files- README.md +8 -7
- demo/ONNXRuntime/README.md +7 -7
- demo/OpenVINO/cpp/README.md +7 -7
- demo/OpenVINO/python/README.md +7 -7
- demo/ncnn/android/README.md +1 -1
README.md
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@@ -21,17 +21,17 @@ For more details, please refer to our [report on Arxiv](https://arxiv.org/abs/21
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#### Standard Models.
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|Model |size |mAP<sup>test<br>0.5:0.95 | Speed V100<br>(ms) | Params<br>(M) |FLOPs<br>(G)| weights |
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| ------ |:---: | :---: |:---: |:---: | :---: | :----: |
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|[YOLOX-s](./exps/default/yolox_s.py) |640 |39.6 |9.8 |9.0 | 26.8 | [
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|[YOLOX-m](./exps/default/yolox_m.py) |640 |46.4 |12.3 |25.3 |73.8| [
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|[YOLOX-l](./exps/default/yolox_l.py) |640 |50.0 |14.5 |54.2| 155.6 | [
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|[YOLOX-x](./exps/default/yolox_x.py) |640 |**51.2** | 17.3 |99.1 |281.9 | [
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|[YOLOX-Darknet53](./exps/default/yolov3.py) |640 | 47.4 | 11.1 |63.7 | 185.3 | [
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#### Light Models.
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|Model |size |mAP<sup>val<br>0.5:0.95 | Params<br>(M) |FLOPs<br>(G)| weights |
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| ------ |:---: | :---: |:---: |:---: | :---: |
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|[YOLOX-Nano](./exps/default/nano.py) |416 |25.3 | 0.91 |1.08 | [
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|[YOLOX-Tiny](./exps/default/yolox_tiny.py) |416 |31.7 | 5.06 |6.45 | [
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## Quick Start
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@@ -48,6 +48,7 @@ pip3 install -v -e . # or python3 setup.py develop
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Step2. Install [apex](https://github.com/NVIDIA/apex).
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```shell
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git clone https://github.com/NVIDIA/apex
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cd apex
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pip3 install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./
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#### Standard Models.
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|Model |size |mAP<sup>test<br>0.5:0.95 | Speed V100<br>(ms) | Params<br>(M) |FLOPs<br>(G)| weights |
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| ------ |:---: | :---: |:---: |:---: | :---: | :----: |
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|[YOLOX-s](./exps/default/yolox_s.py) |640 |39.6 |9.8 |9.0 | 26.8 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EW62gmO2vnNNs5npxjzunVwB9p307qqygaCkXdTO88BLUg?e=NMTQYw)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_s.pth) |
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|[YOLOX-m](./exps/default/yolox_m.py) |640 |46.4 |12.3 |25.3 |73.8| [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ERMTP7VFqrVBrXKMU7Vl4TcBQs0SUeCT7kvc-JdIbej4tQ?e=1MDo9y)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_m.pth) |
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|[YOLOX-l](./exps/default/yolox_l.py) |640 |50.0 |14.5 |54.2| 155.6 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EWA8w_IEOzBKvuueBqfaZh0BeoG5sVzR-XYbOJO4YlOkRw?e=wHWOBE)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_l.pth) |
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|[YOLOX-x](./exps/default/yolox_x.py) |640 |**51.2** | 17.3 |99.1 |281.9 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EdgVPHBziOVBtGAXHfeHI5kBza0q9yyueMGdT0wXZfI1rQ?e=tABO5u)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_x.pth) |
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|[YOLOX-Darknet53](./exps/default/yolov3.py) |640 | 47.4 | 11.1 |63.7 | 185.3 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EZ-MV1r_fMFPkPrNjvbJEMoBLOLAnXH-XKEB77w8LhXL6Q?e=mf6wOc)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_darknet53.pth) |
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#### Light Models.
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|Model |size |mAP<sup>val<br>0.5:0.95 | Params<br>(M) |FLOPs<br>(G)| weights |
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| ------ |:---: | :---: |:---: |:---: | :---: |
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+
|[YOLOX-Nano](./exps/default/nano.py) |416 |25.3 | 0.91 |1.08 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EdcREey-krhLtdtSnxolxiUBjWMy6EFdiaO9bdOwZ5ygCQ?e=yQpdds)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_nano.pth) |
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|[YOLOX-Tiny](./exps/default/yolox_tiny.py) |416 |31.7 | 5.06 |6.45 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EYtjNFPqvZBBrQ-VowLcSr4B6Z5TdTflUsr_gO2CwhC3bQ?e=SBTwXj)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_tiny.pth) |
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## Quick Start
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Step2. Install [apex](https://github.com/NVIDIA/apex).
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```shell
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# skip this step if you don't want to train model.
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git clone https://github.com/NVIDIA/apex
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cd apex
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pip3 install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./
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demo/ONNXRuntime/README.md
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@@ -5,13 +5,13 @@ This doc introduces how to convert your pytorch model into onnx, and how to run
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### Download ONNX models.
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| Model | Parameters | GFLOPs | Test Size | mAP | Weights |
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|:------| :----: | :----: | :---: | :---: | :---: |
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| YOLOX-Nano | 0.91M | 1.08 | 416x416 | 25.3 | [
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| YOLOX-Tiny | 5.06M | 6.45 | 416x416 |31.7 | [
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| YOLOX-S | 9.0M | 26.8 | 640x640 |39.6 | [
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| YOLOX-M | 25.3M | 73.8 | 640x640 |46.4 | [
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| YOLOX-L | 54.2M | 155.6 | 640x640 |50.0 | [
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| YOLOX-Darknet53| 63.72M | 185.3 | 640x640 |47.3 | [
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| YOLOX-X | 99.1M | 281.9 | 640x640 |51.2 | [
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### Convert Your Model to ONNX
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### Download ONNX models.
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| Model | Parameters | GFLOPs | Test Size | mAP | Weights |
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|:------| :----: | :----: | :---: | :---: | :---: |
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| YOLOX-Nano | 0.91M | 1.08 | 416x416 | 25.3 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EfAGwvevU-lNhW5OqFAyHbwBJdI_7EaKu5yU04fgF5BU7w?e=gvq4hf)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_nano.onnx) |
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| YOLOX-Tiny | 5.06M | 6.45 | 416x416 |31.7 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EVigCszU1ilDn-MwLwHCF1ABsgTy06xFdVgZ04Yyo4lHVA?e=hVKiCw)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_tiny.onnx) |
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| YOLOX-S | 9.0M | 26.8 | 640x640 |39.6 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/Ec0L1d1x2UtIpbfiahgxhtgBZVjb1NCXbotO8SCOdMqpQQ?e=siyIsK)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_s.onnx) |
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| YOLOX-M | 25.3M | 73.8 | 640x640 |46.4 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ERUKlQe-nlxBoTKPy1ynbxsBmAZ_h-VBEV-nnfPdzUIkZQ?e=hyQQtl)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_m.onnx) |
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| YOLOX-L | 54.2M | 155.6 | 640x640 |50.0 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ET5w926jCA5GlVfg9ixB4KEBiW0HYl7SzaHNRaRG9dYO_A?e=ISmCYX)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_l.onnx) |
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| YOLOX-Darknet53| 63.72M | 185.3 | 640x640 |47.3 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ESArloSW-MlPlLuemLh9zKkBdovgweKbfu4zkvzKAp7pPQ?e=f81Ikw)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_darknet53.onnx) |
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| YOLOX-X | 99.1M | 281.9 | 640x640 |51.2 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ERjqoeMJlFdGuM3tQfXQmhABmGHlIHydWCwhlugeWLE9AA)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox.onnx) |
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### Convert Your Model to ONNX
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demo/OpenVINO/cpp/README.md
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### Download OpenVINO models.
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| Model | Parameters | GFLOPs | Test Size | mAP | Weights |
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|:------| :----: | :----: | :---: | :---: | :---: |
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| [YOLOX-Nano](../../../exps/nano.py) | 0.91M | 1.08 | 416x416 | 25.3 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EeWY57o5wQZFtXYd1KJw6Z8B4vxZru649XxQHYIFgio3Qw?e=ZS81ce) |
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| [YOLOX-Tiny](../../../exps/yolox_tiny.py) | 5.06M | 6.45 | 416x416 |31.7 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ETfvOoCXdVZNinoSpKA_sEYBIQVqfjjF5_M6VvHRnLVcsA?e=STL1pi) |
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| [YOLOX-S](../../../exps/yolox_s.py) | 9.0M | 26.8 | 640x640 |39.6 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EXUjf3PQnbBLrxNrXPueqaIBzVZOrYQOnJpLK1Fytj5ssA?e=GK0LOM) |
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| [YOLOX-M](../../../exps/yolox_m.py) | 25.3M | 73.8 | 640x640 |46.4 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EcoT1BPpeRpLvE_4c441zn8BVNCQ2naxDH3rho7WqdlgLQ?e=95VaM9) |
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| [YOLOX-L](../../../exps/yolox_l.py) | 54.2M | 155.6 | 640x640 |50.0 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EZvmn-YLRuVPh0GAP_w3xHMB2VGvrKqQXyK_Cv5yi_DXUg?e=YRh6Eq) |
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| [YOLOX-Darknet53](../../../exps/yolov3.py) | 63.72M | 185.3 | 640x640 |47.3 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EQP8LSroikFHuwX0jFRetmcBOCDWSFmylHxolV7ezUPXGw?e=bEw5iq) |
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| [YOLOX-X](../../../exps/yolox_x.py) | 99.1M | 281.9 | 640x640 |51.2 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EZFPnLqiD-xIlt7rcZYDjQgB4YXE9wnq1qaSXQwJrsKbdg?e=83nwEz) |
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## Install OpenVINO Toolkit
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### Download OpenVINO models.
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| Model | Parameters | GFLOPs | Test Size | mAP | Weights |
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|:------| :----: | :----: | :---: | :---: | :---: |
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| [YOLOX-Nano](../../../exps/nano.py) | 0.91M | 1.08 | 416x416 | 25.3 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EeWY57o5wQZFtXYd1KJw6Z8B4vxZru649XxQHYIFgio3Qw?e=ZS81ce)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_nano_openvino.tar.gz) |
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| [YOLOX-Tiny](../../../exps/yolox_tiny.py) | 5.06M | 6.45 | 416x416 |31.7 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ETfvOoCXdVZNinoSpKA_sEYBIQVqfjjF5_M6VvHRnLVcsA?e=STL1pi)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_tiny_openvino.tar.gz) |
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| [YOLOX-S](../../../exps/yolox_s.py) | 9.0M | 26.8 | 640x640 |39.6 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EXUjf3PQnbBLrxNrXPueqaIBzVZOrYQOnJpLK1Fytj5ssA?e=GK0LOM)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_s_openvino.tar.gz) |
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| [YOLOX-M](../../../exps/yolox_m.py) | 25.3M | 73.8 | 640x640 |46.4 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EcoT1BPpeRpLvE_4c441zn8BVNCQ2naxDH3rho7WqdlgLQ?e=95VaM9)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_m_openvino.tar.gz) |
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| [YOLOX-L](../../../exps/yolox_l.py) | 54.2M | 155.6 | 640x640 |50.0 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EZvmn-YLRuVPh0GAP_w3xHMB2VGvrKqQXyK_Cv5yi_DXUg?e=YRh6Eq)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_l_openvino.tar.gz) |
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| [YOLOX-Darknet53](../../../exps/yolov3.py) | 63.72M | 185.3 | 640x640 |47.3 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EQP8LSroikFHuwX0jFRetmcBOCDWSFmylHxolV7ezUPXGw?e=bEw5iq)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_darknet53_openvino.tar.gz) |
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| [YOLOX-X](../../../exps/yolox_x.py) | 99.1M | 281.9 | 640x640 |51.2 | [Download](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EZFPnLqiD-xIlt7rcZYDjQgB4YXE9wnq1qaSXQwJrsKbdg?e=83nwEz)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_x_openvino.tar.gz) |
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## Install OpenVINO Toolkit
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demo/OpenVINO/python/README.md
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### Download OpenVINO models.
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| Model | Parameters | GFLOPs | Test Size | mAP | Weights |
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|:------| :----: | :----: | :---: | :---: | :---: |
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| [YOLOX-Nano](../../../exps/default/nano.py) | 0.91M | 1.08 | 416x416 | 25.3 | [
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| [YOLOX-Tiny](../../../exps/default/yolox_tiny.py) | 5.06M | 6.45 | 416x416 |31.7 | [
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| [YOLOX-S](../../../exps/default/yolox_s.py) | 9.0M | 26.8 | 640x640 |39.6 | [
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| [YOLOX-M](../../../exps/default/yolox_m.py) | 25.3M | 73.8 | 640x640 |46.4 | [
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| [YOLOX-L](../../../exps/default/yolox_l.py) | 54.2M | 155.6 | 640x640 |50.0 | [
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| [YOLOX-Darknet53](../../../exps/default/yolov3.py) | 63.72M | 185.3 | 640x640 |47.3 | [
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| [YOLOX-X](../../../exps/default/yolox_x.py) | 99.1M | 281.9 | 640x640 |51.2 | [
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## Install OpenVINO Toolkit
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### Download OpenVINO models.
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| Model | Parameters | GFLOPs | Test Size | mAP | Weights |
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|:------| :----: | :----: | :---: | :---: | :---: |
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| 8 |
+
| [YOLOX-Nano](../../../exps/default/nano.py) | 0.91M | 1.08 | 416x416 | 25.3 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EeWY57o5wQZFtXYd1KJw6Z8B4vxZru649XxQHYIFgio3Qw?e=ZS81ce)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_nano_openvino.tar.gz) |
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| 9 |
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| [YOLOX-Tiny](../../../exps/default/yolox_tiny.py) | 5.06M | 6.45 | 416x416 |31.7 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ETfvOoCXdVZNinoSpKA_sEYBIQVqfjjF5_M6VvHRnLVcsA?e=STL1pi)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_tiny_openvino.tar.gz) |
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| 10 |
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| [YOLOX-S](../../../exps/default/yolox_s.py) | 9.0M | 26.8 | 640x640 |39.6 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EXUjf3PQnbBLrxNrXPueqaIBzVZOrYQOnJpLK1Fytj5ssA?e=GK0LOM)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_s_openvino.tar.gz) |
|
| 11 |
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| [YOLOX-M](../../../exps/default/yolox_m.py) | 25.3M | 73.8 | 640x640 |46.4 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EcoT1BPpeRpLvE_4c441zn8BVNCQ2naxDH3rho7WqdlgLQ?e=95VaM9)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_m_openvino.tar.gz) |
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| 12 |
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| [YOLOX-L](../../../exps/default/yolox_l.py) | 54.2M | 155.6 | 640x640 |50.0 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EZvmn-YLRuVPh0GAP_w3xHMB2VGvrKqQXyK_Cv5yi_DXUg?e=YRh6Eq)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_l_openvino.tar.gz) |
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| 13 |
+
| [YOLOX-Darknet53](../../../exps/default/yolov3.py) | 63.72M | 185.3 | 640x640 |47.3 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EQP8LSroikFHuwX0jFRetmcBOCDWSFmylHxolV7ezUPXGw?e=bEw5iq)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_darknet53_openvino.tar.gz) |
|
| 14 |
+
| [YOLOX-X](../../../exps/default/yolox_x.py) | 99.1M | 281.9 | 640x640 |51.2 | [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/EZFPnLqiD-xIlt7rcZYDjQgB4YXE9wnq1qaSXQwJrsKbdg?e=83nwEz)/[github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_x_openvino.tar.gz) |
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| 15 |
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| 16 |
## Install OpenVINO Toolkit
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| 17 |
|
demo/ncnn/android/README.md
CHANGED
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@@ -17,7 +17,7 @@ After downloading, please extract your zip file. Then, there are two ways to fin
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| 17 |
* change the ncnn_DIR path in app/src/main/jni/CMakeLists.txt to your extracted directory.
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| 19 |
### Step3
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| 20 |
-
Download example param and bin file from [
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| 21 |
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| 22 |
### Step4
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| 23 |
Open this project with Android Studio, build it and enjoy!
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|
|
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| 17 |
* change the ncnn_DIR path in app/src/main/jni/CMakeLists.txt to your extracted directory.
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| 18 |
|
| 19 |
### Step3
|
| 20 |
+
Download example param and bin file from [onedrive](https://megvii-my.sharepoint.cn/:u:/g/personal/gezheng_megvii_com/ESXBH_GSSmFMszWJ6YG2VkQB5cWDfqVWXgk0D996jH0rpQ?e=qzEqUh) or [github](https://github.com/Megvii-BaseDetection/storage/releases/download/0.0.1/yolox_s_ncnn.tar.gz). Unzip the file to app/src/main/assets.
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| 21 |
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| 22 |
### Step4
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| 23 |
Open this project with Android Studio, build it and enjoy!
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