Tue Mar 18 16:41:25 UTC 2025

import cv2
import numpy as np
import matplotlib.pyplot as plt

# Function to load and preprocess the image
def preprocess_image(image_path):
     # Read the image in grayscale
     img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)

     # Apply Gaussian Blur to reduce noise
     img_blurred = cv2.GaussianBlur(img, (5, 5), 0)

     # Apply adaptive thresholding to detect bands
     _, thresh_img = cv2.threshold(img_blurred, 0, 255, 
cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)

     return thresh_img

# Function to detect bands in the gel
def detect_bands(thresh_img):
     # Find contours in the thresholded image (these correspond to 
the bands)
     contours, _ = cv2.findContours(thresh_img, cv2.RETR_EXTERNAL, 
cv2.CHAIN_APPROX_SIMPLE)

     # Filter small contours that may be noise
     bands = [cnt for cnt in contours if cv2.contourArea(cnt) > 
100]

     return bands

# Function to plot the bands
def plot_bands(image_path, bands):
     # Load the original image for visualization
     img = cv2.imread(image_path)

     # Draw the detected bands on the image
     img_bands = img.copy()
     for band in bands:
         cv2.drawContours(img_bands, [band], -1, (0, 255, 0), 2)

     # Convert the image from BGR to RGB for matplotlib
     img_bands_rgb = cv2.cvtColor(img_bands, cv2.COLOR_BGR2RGB)

     # Display the image with detected bands
     plt.imshow(img_bands_rgb)
     plt.axis('off')
     plt.show()

# Function to measure the intensity of bands
def measure_band_intensity(image_path, bands):
     img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)

     intensities = []
     for band in bands:
         # Create a mask for each band
         mask = np.zeros_like(img)
         cv2.drawContours(mask, [band], -1, 255, 
thickness=cv2.FILLED)

         # Calculate the average intensity inside the band mask
         band_intensity = cv2.mean(img, mask)[0]
         intensities.append(band_intensity)

     return intensities

# Main program
if __name__ == "__main__":
     # Path to the gel electrophoresis image
     image_path = 'gel_image.jpg'  # Change this to your image 
file path

     # Preprocess the image
     thresh_img = preprocess_image(image_path)

     # Detect bands in the image
     bands = detect_bands(thresh_img)

     # Plot the bands on the original image
     plot_bands(image_path, bands)

     # Measure the intensity of each detected band
     intensities = measure_band_intensity(image_path, bands)

     # Display the intensity values for each band
     for i, intensity in enumerate(intensities):
         print(f"Band {i+1} intensity: {intensity}")