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@ -88,20 +88,25 @@ def test_predict_img(): |
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def test_predict_grey_and_4ch(): |
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# Convert SOURCE to greyscale and 4-ch |
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im = Image.open(SOURCE) |
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source_greyscale = Path(f'{SOURCE.parent / SOURCE.stem}_greyscale.jpg') |
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source_rgba = Path(f'{SOURCE.parent / SOURCE.stem}_4ch.png') |
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stem = SOURCE.parent / SOURCE.stem |
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source_greyscale = Path(f'{stem}_greyscale.jpg') |
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source_rgba = Path(f'{stem}_4ch.png') |
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source_non_utf = Path(f'{stem}_veículo.jpg') |
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source_spaces = Path(f'{stem} with spaces.jpg') |
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im.convert('L').save(source_greyscale) # greyscale |
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im.convert('RGBA').save(source_rgba) # 4-ch PNG with alpha |
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im.save(source_non_utf) # non-UTF characters in filename |
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im.save(source_spaces) # spaces in filename |
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# Inference |
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model = YOLO(MODEL) |
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for f in source_rgba, source_greyscale: |
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for f in source_rgba, source_greyscale, source_non_utf, source_spaces: |
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for source in Image.open(f), cv2.imread(str(f)), f: |
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model(source, save=True, verbose=True, imgsz=32) |
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# Cleanup |
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source_greyscale.unlink() |
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source_rgba.unlink() |
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results = model(source, save=True, verbose=True, imgsz=32) |
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assert len(results) == 1 # verify that an image was run |
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f.unlink() # cleanup |
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@pytest.mark.skipif(not ONLINE, reason='environment is offline') |
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