similarity_module.py

import cv2
import os
import numpy as np
from PIL import Image
import shutil

def resize_image(image_path, target_width=800, target_height=600):
    # Get the directory path and filename
    directory, filename = os.path.split(image_path)
    
    # Create the output directory if it doesn't exist
    output_directory = os.path.join(directory, 'outputs')
    os.makedirs(output_directory, exist_ok=True)

    try:
        # Open the image
        with Image.open(image_path) as img:
            # Resize the image
            resized_img = img.resize((target_width, target_height))

            # Save the resized image to the output folder with the same name and extension
            output_path = os.path.join(output_directory, filename)
            resized_img.save(output_path)
            print("Image saved successfully:", output_path)
            return output_path
    except Exception as e:
        print("Error occurred while resizing image:", e)
        return None

def get_top_similar_images(input_image_path, images_folder_path, top_n=5):
    try:
        # Resize input image
        print("Resizing input image...")
        resized_input_image_path = resize_image(input_image_path)
        print("Input image resized:", resized_input_image_path)

        # Read resized input image
        resized_input_image = cv2.imread(resized_input_image_path)
        print("Input image read successfully")

        # Convert input image to HSV
        hsv_input = cv2.cvtColor(resized_input_image, cv2.COLOR_BGR2HSV)
        hist_input = cv2.calcHist([hsv_input], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
        
        # Calculate Bhattacharyya distance for all images in the folder
        distances = {}
        print(images_folder_path)
        for filename in os.listdir(images_folder_path):
            image_path = os.path.join(images_folder_path, filename)
            print(image_path)
            if os.path.isfile(image_path):
                # Read image
                image = cv2.imread(image_path)
                print("Image read successfully:", image_path)
                # Convert image to HSV (no need to resize again)
                hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
                hist_image = cv2.calcHist([hsv_image], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
                # Calculate Bhattacharyya distance
                distance = cv2.compareHist(hist_input, hist_image, cv2.HISTCMP_BHATTACHARYYA)
                distances[filename] = distance
        
        # Sort distances by increasing order
        sorted_distances = sorted(distances.items(), key=lambda x: x[1])
        print("Distances calculated successfully")
        
        # Return top similar images
        return sorted_distances[:top_n]
    except Exception as e:
        print("Error occurred during image comparison:", e)
        return []

# Example usage




def move_images_to_folder(images, destination_folder):
    try:
        # Empty the destination folder
        shutil.rmtree(destination_folder, ignore_errors=True)
        os.makedirs(destination_folder, exist_ok=True)
        
        # Move images to the destination folder
        for filename in images:
            shutil.copy(os.path.join('./resized_img', filename), destination_folder)
    except Exception as e:
        print("Error occurred while moving images to folder:", e)