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red.py

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+import cv2
+import numpy as np
+import os
+import matplotlib.pyplot as plt
+
+# Define colors for different categories
+colors = {
+    0: [0, 0, 0],     # Black
+    2: [255, 255, 255], # White
+    3: [255, 0, 0]    # Red
+}
+
+# Function to process each image
+def process_image(image_path, output_folder):
+    image = cv2.imread(image_path)
+    
+    # BGR to RGB
+    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    
+    # Define color ranges
+    lower_black = np.array([0, 0, 0], dtype=np.uint8)
+    upper_black = np.array([50, 50, 50], dtype=np.uint8)
+    
+    lower_white = np.array([200, 200, 200], dtype=np.uint8)
+    upper_white = np.array([255, 255, 255], dtype=np.uint8)
+    
+    lower_red = np.array([100, 0, 0], dtype=np.uint8)
+    upper_red = np.array([255, 50, 50], dtype=np.uint8)
+    
+    # Create color masks
+    mask_black = cv2.inRange(image_rgb, lower_black, upper_black)
+    mask_white = cv2.inRange(image_rgb, lower_white, upper_white)
+    mask_red = cv2.inRange(image_rgb, lower_red, upper_red)
+    
+    # Create an output mask where black == 0, white == 2, red == 3
+    output_mask = np.zeros(image_rgb.shape[:2], dtype=np.uint8)
+    output_mask[mask_black != 0] = 0
+    output_mask[mask_white != 0] = 2
+    output_mask[mask_red != 0] = 3
+    
+    # Define output filename
+    filename = os.path.splitext(os.path.basename(image_path))[0]
+    output_filename = f"{filename}_color_mask_test.png"
+    output_path = os.path.join(output_folder, output_filename)
+    
+    # Save image
+    cv2.imwrite(output_path, output_mask)
+    print(f"Processed: {image_path} -> {output_path}")
+    
+    # Create RGB representation of the mask
+    rgb_mask = np.zeros((output_mask.shape[0], output_mask.shape[1], 3), dtype=np.uint8)
+    for label, color in colors.items():
+        rgb_mask[output_mask == label] = color
+    
+    # Display the RGB mask
+    plt.figure(figsize=(6, 6))
+    plt.title('RGB Color Mask')
+    plt.imshow(rgb_mask)
+    plt.axis('off')  # Hide the axis
+    plt.show()
+
+# Process images in folder
+def process_images_in_folder(input_folder, output_folder):
+    os.makedirs(output_folder, exist_ok=True)
+    
+    for filename in os.listdir(input_folder):
+        if filename.lower().endswith((".jpg", ".jpeg", ".png")):
+            image_path = os.path.join(input_folder, filename)
+            process_image(image_path, output_folder)
+
+input_folder = "in"
+output_folder = "out"
+
+process_images_in_folder(input_folder, output_folder)

red2.py

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+import cv2
+import numpy as np
+import os
+import matplotlib.pyplot as plt
+
+# Function to process each image
+def process_image(image_path, output_folder):
+    image = cv2.imread(image_path)
+    
+    # BGR to RGB
+    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    
+    # Define color ranges
+    lower_black = np.array([0, 0, 0], dtype=np.uint8)
+    upper_black = np.array([50, 50, 50], dtype=np.uint8)
+    
+    lower_white = np.array([200, 200, 200], dtype=np.uint8)
+    upper_white = np.array([255, 255, 255], dtype=np.uint8)
+    
+    lower_red = np.array([100, 0, 0], dtype=np.uint8)
+    upper_red = np.array([255, 50, 50], dtype=np.uint8)
+    
+    # Create color masks
+    mask_black = cv2.inRange(image_rgb, lower_black, upper_black)
+    mask_white = cv2.inRange(image_rgb, lower_white, upper_white)
+    mask_red = cv2.inRange(image_rgb, lower_red, upper_red)
+    
+    # Create an output mask where black == 0, white == 2, red == 3
+    output_mask = np.zeros(image_rgb.shape[:2], dtype=np.uint8)
+    output_mask[mask_black != 0] = 0
+    output_mask[mask_white != 0] = 2
+    output_mask[mask_red != 0] = 3
+    
+    # Define output filename
+    filename = os.path.splitext(os.path.basename(image_path))[0]
+    output_filename = f"{filename}_color_mask_test.png"
+    output_path = os.path.join(output_folder, output_filename)
+    
+    # Save image
+    cv2.imwrite(output_path, output_mask)
+    print(f"Processed: {image_path} -> {output_path}")
+    
+    # Display the output
+    plt.figure(figsize=(6, 6))
+    plt.title('Grayscale Color Mask')
+    plt.imshow(output_mask, cmap='gray', vmin=0, vmax=3)
+    plt.axis('off')  # Hide the axis
+    plt.show()
+
+# Process all images in folder
+def process_images_in_folder(input_folder, output_folder):
+    os.makedirs(output_folder, exist_ok=True)
+    
+    for filename in os.listdir(input_folder):
+        if filename.lower().endswith((".jpg", ".jpeg", ".png")):
+            image_path = os.path.join(input_folder, filename)
+            process_image(image_path, output_folder)
+
+input_folder = "in"
+output_folder = "out"
+
+process_images_in_folder(input_folder, output_folder)