Fix conflicts

utils/image_processing/contour.py

@@ -0,0 +1,34 @@
+import cv2
+from matplotlib import pyplot as plt
+
+# Load the image
+image = cv2.imread('../../mm_agents/stackoverflow.png')
+
+# Convert to grayscale
+gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+# Apply adaptive thresholding to get a binary image
+thresh = cv2.adaptiveThreshold(
+    gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2
+)
+
+# Find contours
+contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+# Filter out contours that are not of cell size
+# This is done by assuming that cells will have a relatively standard size
+# The size filter is just a placeholder, real values depend on the actual image size
+min_cell_size = 500
+max_cell_size = 5000
+cell_contours = [cnt for cnt in contours if min_cell_size < cv2.contourArea(cnt) < max_cell_size]
+
+# Draw contours on the image
+contour_output = image.copy()
+cv2.drawContours(contour_output, cell_contours, -1, (0, 255, 0), 2)
+
+# Display the image with cell contours
+plt.figure(figsize=(12,6))
+plt.imshow(cv2.cvtColor(contour_output, cv2.COLOR_BGR2RGB))
+plt.title('Spreadsheet with Cell Contours')
+plt.axis('off')
+plt.show()

utils/image_processing/point_marking.py

@@ -0,0 +1,32 @@
+from PIL import Image, ImageDraw
+
+
+def mark_point(image_path: str, x: int, y: int, radius: int = 5, color: str = 'red') -> str:
+    """
+    Mark a point on an image and save the image.
+    """
+    # Load the image
+    image = Image.open(image_path)
+
+    # Create a draw object
+    draw = ImageDraw.Draw(image)
+
+    # Draw a small circle to mark the point
+    draw.ellipse((x - radius, y - radius, x + radius, y + radius), fill=color, outline=color)
+
+    # Save the image with the point marked
+    marked_image_path = image_path[:-4] + '_marked' + image_path[-4:]
+    image.save(marked_image_path)
+
+    return marked_image_path
+
+
+if __name__ == '__main__':
+    image_path = 'chrome_start.png'
+    x = 100
+    y = 200
+    radius = 30
+    color = 'red'
+
+    marked_image_path = mark_point(image_path, x, y, radius, color)
+    print(f"Marked image saved to {marked_image_path}")