Save crops of inference in order of occurrence over the x-axis

[Fritskee]

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Question

When using python detect.py --weights yolo5l.onnx --source <my_image.png> --save-crop I get a folder with the cropped objects perfectly.

However, the order of how the objects occur in the image (which is always over the x-axis) is of utmost important to me. What I noticed is that the naming of the files (and thus the order) are rather random order. Is there a way to have the filenames increment, depending on how the objects occur in the image?

As an example: the most left crop would be <file_name>_0.jpg and the most right crop would be <file_name>_09.jpg

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[github-actions]

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[glenn-jocher]

@Fritskee crops are ordered by confidence, but you can insert your own sorting logic on L384 here:

yolov5/models/common.py

Lines 384 to 389 in 79bca2b

	for *box, conf, cls in reversed(pred): # xyxy, confidence, class
	label = f'{self.names[int(cls)]} {conf:.2f}'
	if crop:
	file = save_dir / 'crops' / self.names[int(cls)] / self.files[i] if save else None
	crops.append({'box': box, 'conf': conf, 'cls': cls, 'label': label,
	'im': save_one_box(box, im, file=file, save=save)})

You can also return crops and handle them however you'd like:

crops = results.crop()

[Fritskee]

@Fritskee crops are ordered by confidence, but you can insert your own sorting logic on L384 here:

yolov5/models/common.py

Lines 384 to 389 in 79bca2b

	for *box, conf, cls in reversed(pred): # xyxy, confidence, class
	label = f'{self.names[int(cls)]} {conf:.2f}'
	if crop:
	file = save_dir / 'crops' / self.names[int(cls)] / self.files[i] if save else None
	crops.append({'box': box, 'conf': conf, 'cls': cls, 'label': label,
	'im': save_one_box(box, im, file=file, save=save)})

You can also return crops and handle them however you'd like:

crops = results.crop()

That's amazing! Thanks so much for the help!!