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remove LPR denoising (#17412)
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@ -634,37 +634,13 @@ class LicensePlateProcessingMixin:
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else:
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gray = image
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# detect noise with Laplacian variance
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laplacian = cv2.Laplacian(gray, cv2.CV_64F)
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noise_variance = np.var(laplacian)
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brightness = cv2.mean(gray)[0]
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noise_threshold = 70
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brightness_threshold = 150
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is_noisy = (
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noise_variance > noise_threshold and brightness < brightness_threshold
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)
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# apply bilateral filter and sharpening only if noisy
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if is_noisy:
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logger.debug(
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f"Noise detected (variance: {noise_variance:.1f}, brightness: {brightness:.1f}) - denoising"
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)
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smoothed = cv2.bilateralFilter(gray, d=15, sigmaColor=100, sigmaSpace=100)
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sharpening_kernel = np.array([[-1, -1, -1], [-1, 9, -1], [-1, -1, -1]])
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processed = cv2.filter2D(smoothed, -1, sharpening_kernel)
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else:
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logger.debug(
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f"No noise detected (variance: {noise_variance:.1f}, brightness: {brightness:.1f}) - skipping denoising and sharpening"
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)
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processed = gray
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# apply CLAHE for contrast enhancement
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grid_size = (
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max(4, input_w // 40),
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max(4, input_h // 40),
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)
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clahe = cv2.createCLAHE(clipLimit=1.5, tileGridSize=grid_size)
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enhanced = clahe.apply(processed)
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enhanced = clahe.apply(gray)
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# Convert back to 3-channel for model compatibility
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image = cv2.cvtColor(enhanced, cv2.COLOR_GRAY2RGB)
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