Benchmark graph interpretation

[joangog]

I have a question regarding the benchmark graph here.
What do the multiple points for a specific model mean? For example for YOLOv5s6 we can see that it is a line of 8 points instead of just one point. What adjustments to the model have been made to get the different values?
Thanks.

[glenn-jocher]

@joangog Figure Notes provide commands to reproduce this plot.

[joangog]

I understand how to reproduce it but can someone provide a quick explanation of what those points mean for each model?

[glenn-jocher]

@joangog evaluations over image size. See relevant region of val.py:

yolov5/val.py

Lines 336 to 350 in 2da6444

	elif opt.task == 'study': # run over a range of settings and save/plot
	# python val.py --task study --data coco.yaml --iou 0.7 --weights yolov5s.pt yolov5m.pt yolov5l.pt yolov5x.pt
	x = list(range(256, 1536 + 128, 128)) # x axis (image sizes)
	for w in opt.weights if isinstance(opt.weights, list) else [opt.weights]:
	f = f'study_{Path(opt.data).stem}_{Path(w).stem}.txt' # filename to save to
	y = [] # y axis
	for i in x: # img-size
	print(f'\nRunning {f} point {i}...')
	r, _, t = run(opt.data, weights=w, batch_size=opt.batch_size, imgsz=i, conf_thres=opt.conf_thres,
	iou_thres=opt.iou_thres, save_json=opt.save_json, plots=False)
	y.append(r + t) # results and times
	np.savetxt(f, y, fmt='%10.4g') # save
	os.system('zip -r study.zip study_*.txt')
	plot_study_txt(x=x) # plot

[joangog]

Thank you very much!