Initialize visual components such as SAM for assistance

utils/image_processing/contour.py

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+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()