added code

ocr.py

@@ -0,0 +1,46 @@
+import os
+import cv2
+import easyocr
+
+def perform_ocr(image_path):
+    # Read the image using OpenCV
+    img = cv2.imread(image_path)
+    
+    # Initialize the OCR reader
+    reader = easyocr.Reader(['en'])  # Use English language
+    
+    # Perform text extraction
+    result = reader.readtext(img)
+    
+    # Extract the text from the result
+    text = "\n".join([entry[1] for entry in result])
+    
+    return text
+
+def main():
+    screenshot_dir = 'screenshots'
+    output_dir = 'ocr_results'
+    
+    # Create output directory if it doesn't exist
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+    
+    # Process all PNG files in the screenshots directory
+    for filename in os.listdir(screenshot_dir):
+        if filename.endswith('.png'):
+            image_path = os.path.join(screenshot_dir, filename)
+            
+            # Perform OCR
+            extracted_text = perform_ocr(image_path)
+            
+            # Save the extracted text
+            output_filename = os.path.splitext(filename)[0] + '.txt'
+            output_path = os.path.join(output_dir, output_filename)
+            
+            with open(output_path, 'w', encoding='utf-8') as f:
+                f.write(extracted_text)
+            
+            print(f"Processed {filename}, saved result to {output_filename}")
+
+if __name__ == "__main__":
+    main()

screenshot.py

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+import time
+import numpy as np
+from PIL import Image
+import mss
+import cv2
+import os
+
+
+def take_screenshot():
+    with mss.mss() as sct:
+        monitor = sct.monitors[0]
+        screenshot = sct.grab(monitor)
+        img = Image.frombytes("RGB", screenshot.size, screenshot.rgb)
+        return cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
+
+
+def compare_images(img1, img2):
+    if img1 is None or img2 is None:
+        return 100.0
+
+    # Convert images to grayscale
+    gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
+    gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
+
+    # Compute the Mean Squared Error between the two images
+    mse = np.mean((gray1 - gray2) ** 2)
+
+    # Normalize the difference (assuming max pixel value is 255)
+    diff_percent = (mse / (255.0 ** 2)) * 100
+
+    return diff_percent
+
+
+def main():
+    last_saved_image = None
+    screenshot_count = 0
+
+    if not os.path.exists('screenshots'):
+        os.makedirs('screenshots')
+
+    while True:
+        current_image = take_screenshot()
+        diff_percent = compare_images(current_image, last_saved_image)
+
+        if diff_percent > 4.0:
+            screenshot_count += 1
+            filename = f'screenshots/screenshot_{screenshot_count}.png'
+            cv2.imwrite(filename, current_image)
+            print(f"Saved {filename} (Difference: {diff_percent:.2f}%)")
+            last_saved_image = current_image
+        else:
+            print(f"Screenshot not saved (Difference: {diff_percent:.2f}%)")
+
+        time.sleep(5)
+
+
+if __name__ == "__main__":
+    main()

updatedscreenshot.py

@@ -0,0 +1,59 @@
+import time
+import numpy as np
+from PIL import Image
+import mss
+import cv2
+import os
+from skimage.metrics import structural_similarity as ssim
+
+
+def take_screenshot():
+    with mss.mss() as sct:
+        monitor = sct.monitors[0]
+        screenshot = sct.grab(monitor)
+        img = Image.frombytes("RGB", screenshot.size, screenshot.rgb)
+        return cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
+
+
+def compare_images(img1, img2):
+    if img1 is None or img2 is None:
+        return 100.0
+
+    # Convert images to grayscale
+    gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
+    gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
+
+    # Compute the Structural Similarity Index (SSIM) between the two images
+    score, _ = ssim(gray1, gray2, full=True)
+
+    # The SSIM score is a value between -1 and 1, where 1 means identical image
+    # We'll convert it to a percentage difference
+    diff_percent = (1 - score) * 100
+
+    return diff_percent
+
+
+def main():
+    last_saved_image = None
+    screenshot_count = 0
+    if not os.path.exists('screenshots'):
+        os.makedirs('screenshots')
+
+    while True:
+        current_image = take_screenshot()
+        diff_percent = compare_images(current_image, last_saved_image)
+
+        if diff_percent > 15.0:  # Lowered threshold for increased sensitivity
+            screenshot_count += 1
+            filename = f'screenshots/screenshot_{screenshot_count}.png'
+            cv2.imwrite(filename, current_image)
+            print(f"Saved {filename} (Difference: {diff_percent:.2f}%)")
+            last_saved_image = current_image
+        else:
+            print(f"Screenshot not saved (Difference: {diff_percent:.2f}%)")
+
+        time.sleep(5)
+
+
+if __name__ == "__main__":
+    main()