dev(narugo): update classify (3e2f04a2) · Commits · git-mirror / Imgutils

imgutils/generic/classify.py

+12 −8

Original line number	Diff line number	Diff line
		@@ -37,6 +37,7 @@ __all__ = [
		'ClassifyModel',
		'classify_predict_score',
		'classify_predict',
		'classify_predict_fmt',
		]


		@@ -390,14 +391,8 @@ class ClassifyModel:
		for vname in vnames(fmt, str_only=True):
		matching = re.fullmatch(r'^scores(-top(?P<topk>\d+))?(-(?P<label_group>[a-zA-Z\d_]+))?$', vname)
		if matching:
		if matching.group('topk'):
		topk = int(matching.group('topk'))
		else:
		topk = None
		if matching.group('label_group'):
		group_label = matching.group('label_group')
		else:
		group_label = 'default'
		topk = int(matching.group('topk')) if matching.group('topk') else None
		group_label = matching.group('label_group') if matching.group('label_group') else 'default'
		vname_to_spair[vname] = (topk, group_label)
		if (topk, group_label) not in d_scores:
		d_scores[(topk, group_label)] = _labels_scores_to_topk(
		@@ -621,3 +616,12 @@ def classify_predict(image: ImageTyping, repo_id: str, model_name: str, label_gr
		model_name=model_name,
		label_group=label_group,
		)


		def classify_predict_fmt(image: ImageTyping, repo_id: str, model_name: str, fmt='scores-top5',
		hf_token: Optional[str] = None):
		return _open_models_for_repo_id(repo_id, hf_token=hf_token).predict_fmt(
		image=image,
		model_name=model_name,
		fmt=fmt,
		)

test/generic/test_classify.py

+68 −1

Original line number	Diff line number	Diff line
		@@ -2,7 +2,7 @@ import pytest
		from PIL import Image

		from imgutils.generic import classify_predict_score
		from imgutils.generic.classify import _open_models_for_repo_id
		from imgutils.generic.classify import _open_models_for_repo_id, classify_predict_fmt
		from test.testings import get_testfile


		@@ -139,3 +139,70 @@ class TestGenericClassify:
		'screwdriver': 0.029927952215075493,
		'chain saw, chainsaw': 0.02070867270231247,
		}, abs=1e-3)

		def test_classify_predict_fmt(self):
		image = Image.open(get_testfile('png_640.png'))
		results = classify_predict_fmt(
		image,
		repo_id='deepghs/timms_mobilenet',
		model_name='mobilenetv4_hybrid_medium.ix_e550_r384_in1k',
		)
		assert results == pytest.approx({
		'n02966687': 0.48493319749832153,
		'n03481172': 0.1228410005569458,
		'n04482393': 0.07170269638299942,
		'n04154565': 0.029927952215075493,
		'n03000684': 0.02070867270231247
		}, abs=1e-3)

		def test_classify_predict_fmt_complex(self):
		image = Image.open(get_testfile('png_640.png'))
		results = classify_predict_fmt(
		image,
		repo_id='deepghs/timms_mobilenet',
		model_name='mobilenetv4_hybrid_medium.ix_e550_r384_in1k',
		fmt={
		'scores-top10': 'scores-top10',
		'scores-top10-descriptions': 'scores-top10-descriptions',
		'scores-top5-definitions': 'scores-top5-definitions',
		'scores-top5-descriptions': 'scores-top5-descriptions',
		}
		)
		assert results['scores-top10'] == pytest.approx({
		'n02966687': 0.48493319749832153,
		'n03481172': 0.1228410005569458,
		'n04482393': 0.07170269638299942,
		'n04154565': 0.029927952215075493,
		'n03000684': 0.02070867270231247,
		'n03498962': 0.019339734688401222,
		'n03444034': 0.013918918557465076,
		'n03995372': 0.009074677713215351,
		'n03794056': 0.00785701535642147,
		'n03384352': 0.007194260135293007
		}, abs=1e-3)
		assert results['scores-top10-descriptions'] == pytest.approx({
		"carpenter's kit, tool kit": 0.48493319749832153,
		'hammer': 0.1228410005569458,
		'tricycle, trike, velocipede': 0.07170269638299942,
		'screwdriver': 0.029927952215075493,
		'chain saw, chainsaw': 0.02070867270231247,
		'hatchet': 0.019339734688401222,
		'go-kart': 0.013918918557465076,
		'power drill': 0.009074677713215351,
		'mousetrap': 0.00785701535642147,
		'forklift': 0.007194260135293007
		}, abs=1e-3)
		assert results['scores-top5-definitions'] == pytest.approx({
		"a set of carpenter's tools": 0.48493319749832153,
		'a hand tool with a heavy rigid head and a handle; used to deliver an impulsive force by striking': 0.1228410005569458,
		'a vehicle with three wheels that is moved by foot pedals': 0.07170269638299942,
		'a hand tool for driving screws; has a tip that fits into the head of a screw': 0.029927952215075493,
		'portable power saw; teeth linked to form an endless chain': 0.02070867270231247
		}, abs=1e-3)
		assert results['scores-top5-descriptions'] == pytest.approx({
		"carpenter's kit, tool kit": 0.48493319749832153,
		'hammer': 0.1228410005569458,
		'tricycle, trike, velocipede': 0.07170269638299942,
		'screwdriver': 0.029927952215075493,
		'chain saw, chainsaw': 0.02070867270231247
		}, abs=1e-3)