Resized images smaller for faster loading + changed how mask is computed

app.py

@@ -52,7 +52,7 @@ def update_rankings_table():
 
 def select_new_image():
     """Select a new image and its segmented versions."""
-    image_paths = load_images_from_directory("data/resized-original-images")
+    image_paths = load_images_from_directory("data/web-original-images")
     last_image_path = None
     max_attempts = 10
     
@@ -70,10 +70,10 @@ def select_new_image():
         
         image_filename = os.path.splitext(os.path.basename(random_image_path))[0] + ".png"
         segmented_image_paths = {
-            "Photoroom": os.path.join("data/processed/photoroom", image_filename),
+            "Photoroom": os.path.join("data/resized/photoroom", image_filename),
             #"Clipdrop": os.path.join("data/processed/clipdrop", image_filename),
-            "RemoveBG": os.path.join("data/processed/removebg", image_filename),
-            "BRIA RMBG 2.0": os.path.join("data/processed/bria", image_filename)
+            "RemoveBG": os.path.join("data/resized/removebg", image_filename),
+            "BRIA RMBG 2.0": os.path.join("data/resized/bria", image_filename)
         }
         
         try:
@@ -107,14 +107,15 @@ def get_notice_markdown():
 
     ## 👇 Test now!
     """
+
 def compute_mask_difference(segmented_a, segmented_b):
     """Compute the absolute difference between two image masks."""
     mask_a = np.asarray(segmented_a)
     mask_b = np.asarray(segmented_b)
 
-    # Set transparent pixels to zero and compute the sum in one step
-    mask_a_1d = np.where(mask_a[..., 3] == 0, 0, np.sum(mask_a[..., :3], axis=-1))
-    mask_b_1d = np.where(mask_b[..., 3] == 0, 0, np.sum(mask_b[..., :3], axis=-1))
+    # Create a binary mask where non-transparent pixels are marked as 1
+    mask_a_1d = np.where(mask_a[..., 3] != 0, 1, 0)
+    mask_b_1d = np.where(mask_b[..., 3] != 0, 1, 0)
 
     # Compute the absolute difference between the masks
     return np.abs(mask_a_1d - mask_b_1d)

requirements.txt

@@ -7,4 +7,5 @@ pillow==11.0.0
 python-dotenv==1.0.1
 requests==2.32.3
 SQLAlchemy==2.0.36
-uvicorn==0.30.1
+uvicorn==0.30.1
+py-spy

utils/resize_processed_images.py

@@ -0,0 +1,62 @@
+from PIL import Image
+import os
+
+def create_directory(path):
+    """Create a directory if it doesn't exist."""
+    os.makedirs(path, exist_ok=True)
+
+def resize_image(input_path, output_path, target_width):
+    """Resize an image to the target width while maintaining aspect ratio."""
+    with Image.open(input_path) as img:
+        # Calculate the new height to maintain the aspect ratio
+        width_percent = target_width / img.width
+        target_height = int(img.height * width_percent)
+        
+        # Resize the image
+        img = img.resize((target_width, target_height), Image.LANCZOS)
+        
+        # Save the resized image in the same format as the input
+        img.save(output_path, format=img.format)
+
+def process_images(input_directory, output_directory, target_width):
+    """Process and resize images from the input directory to the output directory."""
+    create_directory(output_directory)
+    
+    for root, _, files in os.walk(input_directory):
+        for file in files:
+            if file.lower().endswith(('.png', '.jpg', '.jpeg', '.webp', '.heic')):
+                file_path = os.path.join(root, file)
+                result_file_name = os.path.splitext(file)[0] + os.path.splitext(file)[1]
+                result_path = os.path.join(output_directory, result_file_name)
+                
+                # Check if the output file already exists
+                if not os.path.exists(result_path):
+                    print(f"Resizing {file_path} to {result_path}")
+                    resize_image(file_path, result_path, target_width)
+                else:
+                    print(f"Skipped {file_path}, already resized.")
+
+def main():
+    """Main function to resize images in specified subdirectories."""
+    # Process images in the processed directory
+    base_input_directory = "../data/processed"
+    base_output_directory = "../data/resized"
+    target_width = 800  # Set the desired width for web display
+
+    # List of subdirectories to process
+    subdirectories = ["bria", "photoroom", "clipdrop", "removebg"]
+
+    for subdir in subdirectories:
+        input_directory = os.path.join(base_input_directory, subdir)
+        output_directory = os.path.join(base_output_directory, subdir)
+        process_images(input_directory, output_directory, target_width)
+
+    # Additionally, process images in the resized-original-images directory
+    original_input_directory = "../data/resized-original-images"
+    original_output_directory = "../data/web-original-images"
+    process_images(original_input_directory, original_output_directory, target_width)
+
+    print("Image resizing completed.")
+
+if __name__ == "__main__":
+    main()