import cv2

# Load the image
img = cv2.imread('image.png')

# Convert the image to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Apply thresholding to the grayscale image
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Find contours in the thresholded image
contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

# Initialize an empty list to store the detected text
detected_text = []

# Loop over the contours
for contour in contours:
    # Compute the bounding box of the contour
    x, y, w, h = cv2.boundingRect(contour)

    # Extract the ROI from the image
    roi = img[y:y + h, x:x + w]

    # Apply OCR to the ROI
    text = pytesseract.image_to_string(roi)

    # Add the detected text to the list
    detected_text.append(text)

# Print the detected text
print(detected_text)