Add backend-workflow folder

Author: Arham-Tahir64

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+venv/
+env/
+ENV/
+.venv
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db
+

backend-workflow/blurry.py

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+import cv2
+import numpy as np
+
+def is_blurry(img_path):
+    img = cv2.imread(img_path)
+    if img is None:
+        return False
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    laplacian = cv2.Laplacian(gray, cv2.CV_64F)
+    cv2.imshow("img", img)
+    cv2.imshow("gray", gray)
+    cv2.imshow("laplacian", laplacian)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+    score = laplacian.var()
+    return score < 100
+
+def check_contrast_brightness(img_path, min_contrast=40.0, min_brightness=30.0, max_brightness=230.0):
+    img = cv2.imread(img_path)
+    if img is None:
+        return {
+            'has_sufficient_contrast': False,
+            'has_good_brightness': False,
+            'contrast_score': 0.0,
+            'brightness_score': 0.0,
+            'is_acceptable': False
+        }
+    
+    # Convert to grayscale for analysis
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    
+    # Calculate contrast (standard deviation of pixel intensities)
+    # Higher std dev = more contrast between different regions
+    contrast_score = float(gray.std())
+    has_sufficient_contrast = contrast_score >= min_contrast
+    
+    # Calculate brightness (mean pixel intensity)
+    # Values range from 0 (black) to 255 (white)
+    brightness_score = float(gray.mean())
+    has_good_brightness = min_brightness <= brightness_score <= max_brightness
+    
+    is_acceptable = has_sufficient_contrast and has_good_brightness
+    
+    return {
+        'has_sufficient_contrast': has_sufficient_contrast,
+        'has_good_brightness': has_good_brightness,
+        'contrast_score': contrast_score,
+        'brightness_score': brightness_score,
+        'is_acceptable': is_acceptable
+    }
+
+def check_aspect_ratio(img_path, min_ratio=0.7, max_ratio=1.4):
+    img = cv2.imread(img_path)
+    if img is None:
+        return {
+            'has_valid_aspect_ratio': False,
+            'aspect_ratio': 0.0,
+            'width': 0,
+            'height': 0,
+            'ratio_description': 'invalid'
+        }
+    
+    height, width = img.shape[:2]
+    
+    # Calculate min(width, height) / max(width, height)
+    # This gives a value between 0 and 1, where 1 means square
+    min_dim = min(width, height)
+    max_dim = max(width, height)
+    aspect_ratio = float(min_dim) / float(max_dim)
+    
+    # Check if ratio is within valid range: 0.7 ≤ ratio ≤ 1.4
+    # Note: Since min/max ratio is always ≤ 1.0, the effective range is 0.7 to 1.0
+    has_valid_aspect_ratio = min_ratio <= aspect_ratio <= max_ratio
+    
+    # Calculate traditional width:height ratio for description
+    width_height_ratio = float(width) / float(height)
+    
+    # Create a readable description of the ratio
+    if 0.95 <= width_height_ratio <= 1.05:
+        ratio_description = "1:1 (square)"
+    elif width_height_ratio < 1.0:
+        # Portrait orientation (height > width)
+        simplified_ratio = f"1:{1/width_height_ratio:.2f}"
+        ratio_description = f"{simplified_ratio} (portrait)"
+    else:
+        # Landscape orientation (width > height)
+        simplified_ratio = f"{width_height_ratio:.2f}:1"
+        ratio_description = f"{simplified_ratio} (landscape)"
+    
+    return {
+        'has_valid_aspect_ratio': has_valid_aspect_ratio,
+        'aspect_ratio': aspect_ratio,  # This is min/max ratio
+        'width_height_ratio': width_height_ratio,  # Traditional width:height ratio
+        'width': width,
+        'height': height,
+        'ratio_description': ratio_description
+    }
+
+if __name__ == "__main__":
+    img_path = "test5.png"  # Relative path for cross-platform compatibility
+    
+    # Blurriness check
+    blurry = is_blurry(img_path)
+    print("blurry" if blurry else "not blurry")
+    
+    # Contrast/Brightness check
+    result = check_contrast_brightness(img_path)
+    print("bright/contrasted enough" if result['is_acceptable'] else "not bright/contrasted enough")
+    
+    # Aspect Ratio check
+    aspect_result = check_aspect_ratio(img_path)
+    print("valid aspect ratio" if aspect_result['has_valid_aspect_ratio'] else "invalid aspect ratio")