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Code Issues Projects Releases Wiki Activity

Explicit opt function arguments (#2817)

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* more explicit function arguments

* fix typo in detect.py

* revert import order

* revert import order

* remove default value
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fcakyon 2021-04-22 19:17:30 +03:00 committed by GitHub
parent 264d860f8d
commit b40dd99167
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2 changed files with 8 additions and 6 deletions
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6
detect.py
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@ -15,7 +15,7 @@ from utils.plots import plot_one_box
from utils.torch_utils import select_device, load_classifier, time_synchronized
def detect():
def detect(opt):
source, weights, view_img, save_txt, imgsz = opt.source, opt.weights, opt.view_img, opt.save_txt, opt.img_size
save_img = not opt.nosave and not source.endswith('.txt') # save inference images
webcam = source.isnumeric() or source.endswith('.txt') or source.lower().startswith(
@ -176,7 +176,7 @@ if __name__ == '__main__':
with torch.no_grad():
if opt.update: # update all models (to fix SourceChangeWarning)
for opt.weights in ['yolov5s.pt', 'yolov5m.pt', 'yolov5l.pt', 'yolov5x.pt']:
detect()
detect(opt=opt)
strip_optimizer(opt.weights)
else:
detect()
detect(opt=opt)

8
test.py
View File

@ -38,7 +38,8 @@ def test(data,
wandb_logger=None,
compute_loss=None,
half_precision=True,
is_coco=False):
is_coco=False,
opt=None):
# Initialize/load model and set device
training = model is not None
if training: # called by train.py
@ -323,11 +324,12 @@ if __name__ == '__main__':
save_txt=opt.save_txt | opt.save_hybrid,
save_hybrid=opt.save_hybrid,
save_conf=opt.save_conf,
opt=opt
)
elif opt.task == 'speed': # speed benchmarks
for w in opt.weights:
test(opt.data, w, opt.batch_size, opt.img_size, 0.25, 0.45, save_json=False, plots=False)
test(opt.data, w, opt.batch_size, opt.img_size, 0.25, 0.45, save_json=False, plots=False, opt=opt)
elif opt.task == 'study': # run over a range of settings and save/plot
# python test.py --task study --data coco.yaml --iou 0.7 --weights yolov5s.pt yolov5m.pt yolov5l.pt yolov5x.pt
@ -338,7 +340,7 @@ if __name__ == '__main__':
for i in x: # img-size
print(f'\nRunning {f} point {i}...')
r, _, t = test(opt.data, w, opt.batch_size, i, opt.conf_thres, opt.iou_thres, opt.save_json,
plots=False)
plots=False, opt=opt)
y.append(r + t) # results and times
np.savetxt(f, y, fmt='%10.4g') # save
os.system('zip -r study.zip study_*.txt')