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Update app.py
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app.py
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@@ -29,6 +29,16 @@ def get_frame_count_in_duration(filepath):
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video.release()
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return gr.update(maximum=frame_count)
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# Function to split video into chunks
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def split_video_into_chunks(video_path, chunk_size):
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@@ -93,11 +103,12 @@ def run_inference(prompt, video_path, condition, video_length):
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# Split the video into chunks
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video_chunks = split_video_into_chunks(video_path, chunk_size)
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# Process each chunk and store the processed chunk filenames
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for i, chunk in enumerate(video_chunks):
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# Count the frame number of the video chunk
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frame_count = len(chunk)
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command = f"python inference.py --prompt '{prompt}' --condition '{condition}' --video_path '{chunk}' --output_path '{output_path}' --video_length {frame_count} --smoother_steps 19 20"
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subprocess.run(command, shell=True)
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@@ -105,10 +116,11 @@ def run_inference(prompt, video_path, condition, video_length):
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video_path_output = os.path.join(output_path, f"{prompt}_{i}.mp4")
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processed_chunk_filename = video_path_output
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processed_chunk_filenames.append(processed_chunk_filename)
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# Load the processed video chunks
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processed_chunks = [VideoFileClip(filename) for filename in
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# Concatenate the processed video chunks into a final video
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final_video = concatenate_videoclips(processed_chunks)
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@@ -117,7 +129,7 @@ def run_inference(prompt, video_path, condition, video_length):
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final_video.write_videofile('final_video.mp4')
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# Clean up the temporary processed chunk files (optional)
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for filename in
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os.remove(filename)
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return "done", 'final_video.mp4'
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video.release()
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return gr.update(maximum=frame_count)
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# Function to process a video chunk and return the processed video
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def process_video_chunk(chunk, index):
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# Count the frame number of the video chunk
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frame_count = len(chunk)
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# Export the processed chunk to a file with the index in the file name
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processed_chunk_filename = f'processed_chunk_{index}.mp4'
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processed_chunk.write_videofile(processed_chunk_filename)
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return processed_chunk_filename, frame_count
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# Function to split video into chunks
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def split_video_into_chunks(video_path, chunk_size):
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# Split the video into chunks
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video_chunks = split_video_into_chunks(video_path, chunk_size)
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# Process each chunk and store the processed chunk filenames and frame counts
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processed_chunk_info = []
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for i, (chunk, _) in enumerate(video_chunks):
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processed_chunk_filename, frame_count = process_video_chunk(chunk, i)
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# Count the frame number of the video chunk
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#frame_count = len(chunk)
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command = f"python inference.py --prompt '{prompt}' --condition '{condition}' --video_path '{chunk}' --output_path '{output_path}' --video_length {frame_count} --smoother_steps 19 20"
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subprocess.run(command, shell=True)
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video_path_output = os.path.join(output_path, f"{prompt}_{i}.mp4")
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processed_chunk_filename = video_path_output
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#processed_chunk_filenames.append(processed_chunk_filename)
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processed_chunk_info.append((processed_chunk_filename, frame_count))
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# Load the processed video chunks
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processed_chunks = [VideoFileClip(filename) for filename, _ in processed_chunk_info]
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# Concatenate the processed video chunks into a final video
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final_video = concatenate_videoclips(processed_chunks)
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final_video.write_videofile('final_video.mp4')
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# Clean up the temporary processed chunk files (optional)
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for filename, _ in processed_chunk_info:
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os.remove(filename)
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return "done", 'final_video.mp4'
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