main.py

import cv2
import numpy as np
import pytesseract
import psycopg2

# Load an image from file
image = cv2.imread('path_to_image.jpg')

# Display the image in a window
cv2.imshow('Image', image)

# Wait for a key press and close the window
cv2.waitKey(0)
cv2.destroyAllWindows()
# Convert the image to grayscale
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Use pytesseract to do OCR on the image
text = pytesseract.image_to_string(gray_image)

# Print the recognized text
print(text)
# Connect to your postgres DB
conn = psycopg2.connect(
    dbname="your_dbname",
    user="your_username",
    password="your_password",
    host="your_host",
    port="your_port"
)

# Open a cursor to perform database operations
cur = conn.cursor()

# Create a table to store OCR results if it doesn't exist
cur.execute('''
    CREATE TABLE IF NOT EXISTS ocr_results (
        id SERIAL PRIMARY KEY,
        text TEXT NOT NULL
    )
''')

# Insert the OCR result into the table
cur.execute('''
    INSERT INTO ocr_results (text) VALUES (%s)
''', (text,))

# Commit the transaction
conn.commit()

# Close the cursor and connection
cur.close()
conn.close()
# Function to split the image into cells for scoreboard OCR
def split_image_into_cells(image, rows, cols):
    # Get the dimensions of the image
    height, width = image.shape[:2]
    cell_height = height // rows
    cell_width = width // cols

    cells = []
    for row in range(rows):
        for col in range(cols):
            # Calculate the coordinates of the cell
            start_row = row * cell_height
            start_col = col * cell_width
            end_row = start_row + cell_height
            end_col = start_col + cell_width

            # Extract the cell from the image
            cell = image[start_row:end_row, start_col:end_col]
            cells.append(cell)

    return cells

# Example usage
rows = 5  # Number of rows in the scoreboard
cols = 5  # Number of columns in the scoreboard
cells = split_image_into_cells(image, rows, cols)

# Perform OCR on each cell
for i, cell in enumerate(cells):
    cell_text = pytesseract.image_to_string(cell)
    print(f"Cell {i} text: {cell_text}")