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add eval result

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fluid/PaddleCV/yolov3/README.md
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......@@ -117,21 +117,11 @@ Evaluation is to evaluate the performance of a trained model. This sample provid
Evalutaion result is shown as below:
```text
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.377
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.598
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.408
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.244
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.408
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.489
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.308
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.481
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.504
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.351
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.534
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.632
```
| mAP |IoU=0.50:0.95 | IoU=0.50 | IoU=0.75 |
| :------: | :------: | :------: | :------: |
| input size=608x608| 37.7 | 59.8 | 40.8 |
| input size=416x416 | 36.5 | 58.2 | 39.1 |
| input size=320x320 | 34.1 | 55.4 | 36.3 |
## Inference and Visualization
......
fluid/PaddleCV/yolov3/README_cn.md
浏览文件 @ 30717188
......@@ -118,22 +118,11 @@ Train Loss
模型评估结果：
```text
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.377
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.598
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.408
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.244
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.408
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.489
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.308
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.481
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.504
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.351
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.534
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.632
```
| mAP |IoU=0.50:0.95 | IoU=0.50 | IoU=0.75 |
| :------: | :------: | :------: | :------: |
| input size=608x608| 37.7 | 59.8 | 40.8 |
| input size=416x416 | 36.5 | 58.2 | 39.1 |
| input size=320x320 | 34.1 | 55.4 | 36.3 |
## 模型推断及可视化
......
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