video stuff

mov2seq.py

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

def video_to_frames(video_file, output_dir, one_every_n_frames):
    # Create VideoCapture object
    vidcap = cv2.VideoCapture(video_file)
    fps = int(vidcap.get(cv2.CAP_PROP_FPS))

    # Make output directory if it doesn't already exist
    os.makedirs(output_dir, exist_ok=True)

    success, image = vidcap.read()
    count = 0
    n = one_every_n_frames
    filename = os.path.splitext(os.path.basename(video_file))[0]
    while success:
        # Save frame as JPEG file
        if count % n == 0:
            cv2.imwrite(os.path.join(output_dir, f"{filename}{count}.jpg"), image)
        success, image = vidcap.read()
        count += 1
# Usage
video_to_frames(sys.argv[1], "frames: " + sys.argv[1], int(sys.argv[2]))

vid2seq.py

import cv2
import numpy as np
import os, sys
import re

def natural_sort_key(s):
    return [int(text) if text.isdigit() else text.lower()
            for text in re.split(r'(\d+)', s)]

def histogram_similarity(image1, image2):
    hist1 = cv2.calcHist([image1], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
    hist2 = cv2.calcHist([image2], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
    cv2.normalize(hist1, hist1)
    cv2.normalize(hist2, hist2)
    similarity = cv2.compareHist(hist1, hist2, cv2.HISTCMP_CORREL)
    return similarity

def detect_scene_changes(image_folder, output_folder, threshold):
    images = sorted(os.listdir(image_folder), key=natural_sort_key)

    scene_number = 1
    frame_number = 1
    hist_sim_values = []
    scene_hist_sim_values = []

    for i in range(len(images) - 1):
        current_image = cv2.imread(os.path.join(image_folder, images[i]))
        next_image = cv2.imread(os.path.join(image_folder, images[i + 1]))

        current_hist_sim = histogram_similarity(current_image, next_image)
        hist_sim_values.append(current_hist_sim)
        scene_hist_sim_values.append(current_hist_sim)

        label = 's{}_p{}'.format(scene_number, frame_number)
        cv2.imwrite(os.path.join(output_folder, label + '.jpg'), current_image)

        if current_hist_sim < threshold:
            print(f"Average histogram similarity for scene {scene_number}: {np.mean(scene_hist_sim_values)}")
            scene_number += 1
            frame_number = 1
            scene_hist_sim_values = []
        else:
            frame_number += 1

    # Handle the last image in the sequence
    last_image = cv2.imread(os.path.join(image_folder, images[-1]))
    label = 's{}_p{}'.format(scene_number, frame_number)
    cv2.imwrite(os.path.join(output_folder, label + '.jpg'), last_image)

    if scene_hist_sim_values:
        print(f"Average histogram similarity for scene {scene_number}: {np.mean(scene_hist_sim_values)}")
    print(f"Total average histogram similarity: {np.mean(hist_sim_values)}")

image_folder = sys.argv[1]
output_folder = sys.argv[2]
os.makedirs(output_folder, exist_ok=True)
threshold = 0.5
detect_scene_changes(image_folder, output_folder, threshold)