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pip install opencv-python
import cv2
import os
import gradio as gr
def extract_clip(video_path, clip_start, clip_duration):
video = cv2.VideoCapture(video_path)
success, frame = video.read()
count = 0
frames = []
while success:
current_time = video.get(cv2.CAP_PROP_POS_MSEC) / 1000
# Seek to the desired starting point
if current_time < clip_start:
video.set(cv2.CAP_PROP_POS_MSEC, clip_start * 1000)
success, frame = video.read()
continue
# Check duration after reaching the clip_start timestamp
elif current_time - clip_start <= clip_duration:
frames.append(frame)
success, frame = video.read()
count += 1
else:
break
video.release()
return frames
def display_frames(frames):
num_cols = 4 # Number of columns in the image grid
num_rows = (len(frames) + num_cols - 1) // num_cols
grid_image = cv2.hconcat([cv2.hconcat(frames[i:i+num_cols]) for i in range(0, len(frames), num_cols)])
return grid_image
# Create Gradio interface
video_input = gr.inputs.Video(type="file")
start_input = gr.inputs.Number(default=5, label="Start Time (seconds)")
duration_input = gr.inputs.Number(default=3, label="Duration (seconds)")
image_output = gr.outputs.Image(type="pil")
gr.Interface(fn=lambda video, start, duration: display_frames(extract_clip(video, start, duration)),
inputs=[video_input, start_input, duration_input],
outputs=image_output,
title="Extract Video Clip").launch() |