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Update app.py
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app.py
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import cv2
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import os
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import glob
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def
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os.makedirs(output_folder, exist_ok=True)
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video_files = glob.glob(os.path.join(input_folder, "*.mp4")) # Modify if using other formats
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success, frame = cap.read()
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image_path = os.path.join(output_folder, f"{
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cv2.imwrite(image_path, frame)
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success, frame = cap.read()
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cap.release()
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input_folder = "videos" # Change this to the path where your videos are stored
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output_folder = "output_images"
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extract_frames_from_videos(input_folder, output_folder)
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import gradio as gr
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import cv2
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import pandas as pd
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import os
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def extract_frames(video_path, csv_path):
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output_folder = "extracted_frames"
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os.makedirs(output_folder, exist_ok=True)
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# Read timestamps from CSV
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df = pd.read_csv(csv_path)
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cap = cv2.VideoCapture(video_path)
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fps = cap.get(cv2.CAP_PROP_FPS)
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extracted_images = []
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for index, row in df.iterrows():
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timestamp = row['start'] # Using 'start' column for frame extraction
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frame_number = int(timestamp * fps)
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cap.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
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success, frame = cap.read()
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if success:
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image_path = os.path.join(output_folder, f"frame_{index}.jpg")
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cv2.imwrite(image_path, frame)
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extracted_images.append(image_path)
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cap.release()
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return extracted_images
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gui = gr.Interface(
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fn=extract_frames,
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inputs=[
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gr.Video(label="Upload Video"),
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gr.File(label="Upload CSV with timestamps")
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],
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outputs=gr.Gallery(label="Extracted Frames"),
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title="Frame Extractor from Video",
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description="Upload a video and a CSV file with timestamps to extract specific frames."
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)
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gui.launch()
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