|
|
@@ -234,7 +234,7 @@ if __name__ == '__main__': |
|
|
|
parser = argparse.ArgumentParser(prog='test.py') |
|
|
|
parser.add_argument('--weights', type=str, default='weights/yolov5s.pt', help='model.pt path') |
|
|
|
parser.add_argument('--data', type=str, default='data/coco.yaml', help='*.data path') |
|
|
|
parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch') |
|
|
|
parser.add_argument('--batch-size', type=int, default=32, help='size of each image batch') |
|
|
|
parser.add_argument('--img-size', type=int, default=640, help='inference size (pixels)') |
|
|
|
parser.add_argument('--conf-thres', type=float, default=0.001, help='object confidence threshold') |
|
|
|
parser.add_argument('--iou-thres', type=float, default=0.65, help='IOU threshold for NMS') |
|
|
@@ -262,13 +262,14 @@ if __name__ == '__main__': |
|
|
|
opt.augment) |
|
|
|
|
|
|
|
elif opt.task == 'study': # run over a range of settings and save/plot |
|
|
|
for weights in ['yolov5s.pt', 'yolov5m.pt', 'yolov5l.pt', 'yolov5x.pt', 'yolov3-spp.pt']: |
|
|
|
for weights in ['yolov5s.pt', 'yolov5m.pt', 'yolov5l.pt', 'yolov5x.pt']: |
|
|
|
f = 'study_%s_%s.txt' % (Path(opt.data).stem, Path(weights).stem) # filename to save to |
|
|
|
x = list(range(256, 1024, 64)) # x axis |
|
|
|
x = list(range(288, 896, 64)) # x axis |
|
|
|
y = [] # y axis |
|
|
|
for i in x: # img-size |
|
|
|
print('\nRunning %s point %s...' % (f, i)) |
|
|
|
r, _, t = test(opt.data, weights, opt.batch_size, i, opt.conf_thres, opt.iou_thres, opt.save_json) |
|
|
|
y.append(r + t) # results and times |
|
|
|
np.savetxt(f, y, fmt='%10.4g') # save |
|
|
|
plot_study_txt(f, x) # plot |
|
|
|
os.system('zip -r study.zip study_*.txt') |
|
|
|
# plot_study_txt(f, x) # plot |