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46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
import time
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import numpy as np
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from PIL import Image
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def assert_image_similar_to_expectation(img, img_path, threshold=100):
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img.save(img_path)
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expected_img_path = img_path.replace("/test_output/", "/expected_output/")
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expected_img = Image.open(expected_img_path)
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norm_sum_sq_diff = calc_norm_sum_sq_diff(img, expected_img)
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if norm_sum_sq_diff > threshold:
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diff_img = Image.fromarray(np.asarray(img) - np.asarray(expected_img))
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diff_img.save(img_path + f"_diff_{norm_sum_sq_diff:.1f}.png")
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expected_img.save(img_path + "_expected.png")
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assert (
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norm_sum_sq_diff < threshold
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), f"{norm_sum_sq_diff:.3f} is bigger than threshold {threshold}"
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def calc_norm_sum_sq_diff(img, img2):
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sum_sq_diff = np.sum(
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(np.asarray(img).astype("float") - np.asarray(img2).astype("float")) ** 2
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)
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norm_sum_sq_diff = sum_sq_diff / np.sqrt(sum_sq_diff)
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return norm_sum_sq_diff
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class Timer:
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def __init__(self, name):
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self.name = name
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self.start = None
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self.elapsed = None
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self.end = None
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def __enter__(self):
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self.start = time.perf_counter()
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return self
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def __exit__(self, *args):
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self.end = time.perf_counter()
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self.elapsed = self.end - self.start
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print(f"{self.name} took {self.elapsed*1000:.2f} ms")
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