未验证 提交 f0bf5be8 编写于 作者: F Feng Ni 提交者: GitHub

add bias test doc for yolo ppyolo pafnet(#2675)

上级 edd24ca1
......@@ -132,7 +132,27 @@ CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c configs/ppyolo/ppyolo_test.yml -o
Evaluation results will be saved in `bbox.json`, compress it into a `zip` package and upload to [COCO dataset evaluation](https://competitions.codalab.org/competitions/20794#participate) to evaluate.
**NOTE:** `configs/ppyolo/ppyolo_test.yml` is only used for evaluation on COCO test-dev2017 dataset, could not be used for training or COCO val2017 dataset evaluating.
**NOTE 1:** `configs/ppyolo/ppyolo_test.yml` is only used for evaluation on COCO test-dev2017 dataset, could not be used for training or COCO val2017 dataset evaluating.
**NOTE 2:** Due to the overall upgrade of the dynamic graph framework, the following weight models published by paddledetection need to be evaluated by adding the -- bias field, such as
```bash
# use weights released in PaddleDetection model zoo
CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams --bias
```
These models are:
1.ppyolo_r50vd_dcn_1x_coco
2.ppyolo_r50vd_dcn_voc
3.ppyolo_r18vd_coco
4.ppyolo_mbv3_large_coco
5.ppyolo_mbv3_small_coco
6.ppyolo_tiny_650e_coco
### 3. Inference
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......@@ -116,7 +116,27 @@ CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c configs/ppyolo/ppyolo_test.yml -o
评估结果保存于`bbox.json`中,将其压缩为zip包后通过[COCO数据集评估页](https://competitions.codalab.org/competitions/20794#participate)提交评估。
**注意:** `configs/ppyolo/ppyolo_test.yml`仅用于评估COCO test-dev数据集,不用于训练和评估COCO val2017数据集。
**注意1:** `configs/ppyolo/ppyolo_test.yml`仅用于评估COCO test-dev数据集,不用于训练和评估COCO val2017数据集。
**注意2:** 由于动态图框架整体升级,以下几个PaddleDetection发布的权重模型评估时需要添加--bias字段, 例如
```bash
# 使用PaddleDetection发布的权重
CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams --bias
```
主要有:
1.ppyolo_r50vd_dcn_1x_coco
2.ppyolo_r50vd_dcn_voc
3.ppyolo_r18vd_coco
4.ppyolo_mbv3_large_coco
5.ppyolo_mbv3_small_coco
6.ppyolo_tiny_650e_coco
### 3. 推理
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......@@ -40,7 +40,7 @@ PAFNet系列模型从如下方面优化TTFNet模型:
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 |
| :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
| ResNet50vd | PAFNet | 18 | 10x | ---- | 42.2 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_10x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/pafnet_10x_coco.yml) |
| ResNet50vd | PAFNet | 18 | 10x | ---- | 39.8 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_10x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/pafnet_10x_coco.yml) |
......@@ -50,7 +50,12 @@ PAFNet系列模型从如下方面优化TTFNet模型:
| :-------------- | :------------- | :-----: | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
| MobileNetv3 | PAFNet-Lite | 12 | 20x | 23.9 | 26.00 | 14 | [下载链接](https://paddledet.bj.bcebos.com/models/pafnet_lite_mobilenet_v3_20x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/ttfnet/pafnet_lite_mobilenet_v3_20x_coco.yml) |
**注意:** 由于动态图框架整体升级,PAFNet的PaddleDetection发布的权重模型评估时需要添加--bias字段, 例如
```bash
# 使用PaddleDetection发布的权重
CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c configs/ppyolo/pafnet_10x_coco.yml -o weights=https://paddledet.bj.bcebos.com/models/pafnet_10x_coco.pdparams --bias
```
## Citations
```
......
......@@ -45,8 +45,17 @@
| MobileNet-V3-SSLD | 416 | 8 | 270e | - | 79.2 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
| MobileNet-V3-SSLD | 320 | 8 | 270e | - | 77.3 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/yolov3/yolov3_mobilenet_v3_large_ssld_270e_voc.yml) |
**注意:** YOLOv3均使用8GPU训练,训练270个epoch
**注意:** YOLOv3均使用8GPU训练,训练270个epoch。由于动态图框架整体升级,以下几个PaddleDetection发布的权重模型评估时需要添加--bias字段, 例如
```bash
# 使用PaddleDetection发布的权重
CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c configs/ppyolo/yolov3_darknet53_270e_coco.yml -o weights=https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams --bias
```
主要有:
1.yolov3_darknet53_270e_coco
2.yolov3_r50vd_dcn_270e_coco
## Citations
```
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