C:\Users\NisimHurst\NDS\scripts\extract_presentation_youtube\youtube_presentation.py

youtube_presentation.py

# %%
# Importing necessary libraries
import cv2
from skimage.metrics import structural_similarity as ssim
import numpy as np
import os
from pptx import Presentation
from pptx.util import Inches

# %%
# Function to compare frames using SSIM
def is_different(frame1, frame2, threshold=0.5):
    gray_frame1 = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)
    gray_frame2 = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)
    score, _ = ssim(gray_frame1, gray_frame2, full=True)
    return score < threshold

# %%
# Load the video
video_path = 'input.mp4'
cap = cv2.VideoCapture(video_path)
frame_rate = cap.get(cv2.CAP_PROP_FPS)
total_frames = cap.get(cv2.CAP_PROP_FRAME_COUNT)
interval = int(frame_rate)  # Extract one frame per second
print(interval)

# %%
# Extract frames
from tqdm import tqdm

success, frame = cap.read()
count = 0
different_frames = []
prev_frame=False
pbar = tqdm(total=total_frames)
while success:
    if (count % (interval*5)) == 0:
        if prev_frame:
            if is_different(frame, prev_frame):
                different_frames.append(frame)
        else:
            different_frames.append(frame)
        # print("different_frames: ", len(different_frames), "count:", count)
        pbar.update(interval*5)
        # print(count/total_frames*100)
    success, frame = cap.read()
    count += 1
pbar.close()

# %%
# Save different frames
output_folder = 'output_frames'
os.makedirs(output_folder, exist_ok=True)

for i, frame in enumerate(different_frames):
    cv2.imwrite(f'{output_folder}/frame_{i}.jpg', frame)

# %%
# Create PowerPoint presentation
prs = Presentation()

for i in range(len(different_frames)):
    slide = prs.slides.add_slide(prs.slide_layouts[5])
    img_path = f'{output_folder}/frame_{i}.jpg'
    slide.shapes.add_picture(img_path, Inches(1), Inches(1), width=Inches(8), height=Inches(6))

prs.save('video_frames_presentation.pptx')

print("Presentation created successfully.")
# %%
#