yjh0410 264112178f build a new YOLO-Tutorial project for my book		1 an în urmă
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README.md	264112178f build a new YOLO-Tutorial project for my book	1 an în urmă
build.py	264112178f build a new YOLO-Tutorial project for my book	1 an în urmă
criterion.py	264112178f build a new YOLO-Tutorial project for my book	1 an în urmă
fcos.py	264112178f build a new YOLO-Tutorial project for my book	1 an în urmă
matcher.py	264112178f build a new YOLO-Tutorial project for my book	1 an în urmă

FCOS: Fully Convolutional One-Stage Object Detector

Our FCOS-R50-1x baseline on COCO-val:

 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.391
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.579
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.422
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.236
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.428
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.501
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.326
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.559
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.625
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.450
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.685
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.758

FCOS

Real-time FCOS

Model	scale	FPS	AP^val 0.5:0.95	AP^val 0.5	Weight	Logs
FCOS_R18_1x	800,1333		34.1	52.2	ckpt	Logs
FCOS_R50_1x	800,1333		39.1	57.9	ckpt	Logs

Train FCOS

Single GPU

Taking training FCOS_R18_1x on COCO as the example,

python main.py --cuda -d coco --root path/to/coco -m fcos_r18_1x --batch_size 16 --eval_epoch 2

Multi GPU

Taking training FCOS_R18_1x on COCO as the example,

python -m torch.distributed.run --nproc_per_node=8 train.py --cuda -dist -d coco --root path/to/coco -m fcos_r18_1x --batch_size 16 --eval_epoch 2

Test FCOS

Taking testing FCOS_R18_1x on COCO-val as the example,

python test.py --cuda -d coco --root path/to/coco -m fcos_r18_1x --weight path/to/fcos_r18_1x.pth -vt 0.4 --show

Evaluate FCOS

Taking evaluating FCOS_R18_1x on COCO-val as the example,

python main.py --cuda -d coco --root path/to/coco -m fcos_r18_1x --resume path/to/fcos_r18_1x.pth --eval_first

Demo

Detect with Image

python demo.py --mode image --path_to_img path/to/image_dirs/ --cuda -m fcos_r18_1x --weight path/to/weight -vt 0.4 --show

Detect with Video

python demo.py --mode video --path_to_vid path/to/video --cuda -m fcos_r18_1x --weight path/to/weight -vt 0.4 --show --gif

Detect with Camera

python demo.py --mode camera --cuda -m fcos_r18_1x --weight path/to/weight -vt 0.4 --show --gif

Model	scale	FPS	AP^val 0.5:0.95	AP^val 0.5	Weight	Logs
FCOS_RT_R18_4x	512,736
FCOS_RT_R50_4x	512,736		43.9	60.2

README.md