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add more models and detector-specific rtol

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galthran-wq 2025-02-18 09:18:33 +00:00
parent f3d05ef2d5
commit 1c825e8803
1 changed files with 25 additions and 8 deletions
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27
tests/test_extract_faces.py
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@ -81,9 +81,18 @@ def test_different_detectors():
@pytest.mark.parametrize("detector_backend", [ @pytest.mark.parametrize("detector_backend", [
"opencv", "opencv",
"ssd" "ssd",
"mtcnn",
"retinaface",
]) ])
def test_batch_extract_faces(detector_backend): def test_batch_extract_faces(detector_backend):
detector_backend_to_rtol = {
"opencv": 0.1,
"ssd": 0.01,
"mtcnn": 0.2,
"retinaface": 0.01,
}
rtol = detector_backend_to_rtol[detector_backend]
img_paths = [ img_paths = [
"dataset/img2.jpg", "dataset/img2.jpg",
"dataset/img3.jpg", "dataset/img3.jpg",
@ -123,16 +132,24 @@ def test_batch_extract_faces(detector_backend):
) )
for img_obj_individual, img_obj_batch in zip(img_objs_individual, img_objs_batch): for img_obj_individual, img_obj_batch in zip(img_objs_individual, img_objs_batch):
for key in img_obj_individual["facial_area"]: for key in img_obj_individual["facial_area"]:
if key == "left_eye" or key == "right_eye": if isinstance(img_obj_individual["facial_area"][key], tuple):
continue for ind_val, batch_val in zip(
img_obj_individual["facial_area"][key],
img_obj_batch["facial_area"][key]
):
assert abs(ind_val - batch_val) <= rtol * ind_val
elif (
isinstance(img_obj_individual["facial_area"][key], int) or
isinstance(img_obj_individual["facial_area"][key], float)
):
assert abs( assert abs(
img_obj_individual["facial_area"][key] - img_obj_individual["facial_area"][key] -
img_obj_batch["facial_area"][key] img_obj_batch["facial_area"][key]
) <= 0.03 * img_obj_individual["facial_area"][key] ) <= rtol * img_obj_individual["facial_area"][key]
assert abs( assert abs(
img_obj_individual["confidence"] - img_obj_individual["confidence"] -
img_obj_batch["confidence"] img_obj_batch["confidence"]
) <= 0.03 * img_obj_individual["confidence"] ) <= rtol * img_obj_individual["confidence"]
def test_backends_for_enforced_detection_with_non_facial_inputs(): def test_backends_for_enforced_detection_with_non_facial_inputs():