Filter out blurry images based on the image Laplacian

sharp_image_filter.py

"""
MIT License

Copyright (c) 2024 Sergey Prokudin sergey.prokudin@gmail.com

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
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This script processes a directory of images to identify and copy sharp images to a specified directory.
It uses the Laplacian operator to measure the variance (sharpness) of images and filters them based on a given threshold.
Supports command-line arguments for specifying source and target directories, and an optional sharpness threshold.

Usage:
    python sharp_image_filter.py <source_directory> <target_directory> [-t --threshold <sharpness_threshold>]

    - <source_directory>: The directory containing images to process.
    - <target_directory>: The directory where sharp images will be stored.
    - [-t --threshold <sharpness_threshold>]: Optional. The sharpness threshold for determining if an image is sharp.
      Higher values increase sharpness requirement, potentially discarding more images. Default is 30.0.

Example:
    python sharp_image_filter.py ./images ./sharp_images -t 25.0
"""

import cv2
import os
import argparse
import shutil  

def is_sharp(image_path, threshold=30.0):
    """Check if the image is sharp based on the Laplacian variance.
    
    Args:
        image_path (str): Path to the image file.
        threshold (float): Variance threshold for determining sharpness.
        
    Returns:
        bool: True if the image is considered sharp, False otherwise.
    """
    print(image_path)
    image = cv2.imread(image_path)
    if image is None:
        print(f"Warning: Unable to load {image_path}, skipping.")
        return False
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    variance = cv2.Laplacian(gray, cv2.CV_64F).var()
    return variance > threshold

def process_images(frames_directory, sharp_frames_directory, threshold):
    """Process images from a directory and copy sharp images to another directory.
    
    Args:
        frames_directory (str): Directory containing images to process.
        sharp_frames_directory (str): Directory to store sharp images.
        threshold (float): Sharpness threshold.
    """
    if not os.path.exists(sharp_frames_directory):
        os.makedirs(sharp_frames_directory)

    supported_formats = ('.jpg', '.jpeg', '.png', '.bmp')
    for frame in os.listdir(frames_directory):
        if not frame.lower().endswith(supported_formats):
            continue
        frame_path = os.path.join(frames_directory, frame)
        if is_sharp(frame_path, threshold):
            sharp_frame_path = os.path.join(sharp_frames_directory, frame)
            shutil.copy(frame_path, sharp_frame_path)  

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Process images to filter sharp ones. Use the -t (--threshold) option to set the sharpness threshold. A higher threshold means fewer images will be considered sharp, as it requires higher sharpness variance.")
    parser.add_argument("source_directory", help="The directory containing images to process.")
    parser.add_argument("target_directory", help="The directory where sharp images will be stored.")
    parser.add_argument("-t", "--threshold", type=float, default=30.0, help="The sharpness threshold for determining if an image is sharp. Higher values increase sharpness requirement, potentially discarding more images.")
    args = parser.parse_args()

    process_images(args.source_directory, args.target_directory, args.threshold)