Expected accuracy for YOLOv7-tiny leakyRelu

[atangfan]

What is the expected accuracy for YOLOv7-tiny leakyRelu? I got a very low AP @ 0.75 by using COCO2017-val

 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.458
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.007

Should this be the same as SILU version? Could you share experiments for YOLOv7 with leakyRelu if you have? Thanks!

[WongKinYiu]

YOLOv7-tiny 416: 35.2% AP, 52.8% AP50, 37.3% AP75. 320: 30.8% AP, 47.3% AP50, 32.2% AP75.

python train.py --workers 8 --device 0 --batch-size 64 --data data/coco.yaml --img 512 512 --cfg cfg/training/yolov7-tiny.yaml --weights '' --name yolov7-tiny --hyp data/hyp.scratch.tiny.yaml

[chjej202]

Hi, @WongKinYiu

what is the coco 2017 val accuracy with yolov7-tiny leaky?

I got the following mAP with your uploaded yolov7-tiny.pt (val2017) python test.py --data data/coco.yaml --img 416 --batch 32 --conf 0.001 --iou 0.5 --device 0 --weights yolov7-tiny.pt --name yolov7tiny_416_val

Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.331 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.505 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.345 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.117 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.359 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.541 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.291 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.457 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.489 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.227 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.553 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.724

I also tested with the darknet with your uploaded yolov7-tiny.cfg and yolov7-tiny.weights (val2017) ./darknet detector map ./cfg/coco.data ./cfg/yolov7-tiny.cfg yolov7-tiny.weights mean average precision (mAP@0.50) = 0.558828, or 55.88 %

I got different results from your yolov7-tiny.weights and yolov7-tiny.pt, and my results are not equal to your accuracy mentioned on the above comment.

what is the expected accuracy should I get?

[WongKinYiu]

The yolov7-tiny.pt is uploaded for someone who want to use it for onnx/tensorrt testing. That is the reason why yolov7-tiny is not included in readme of main branch.

We develop tiny models on darknet compatible branch, you could use yolor or pytorch yolov4 to get expected accuracy.