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martintomov
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Browse files- .DS_Store +0 -0
- app.py +169 -0
- requirements.txt +8 -0
.DS_Store
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Binary file (6.15 kB). View file
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app.py
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from dotenv import load_dotenv
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from IPython.display import display, Image, Audio
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from moviepy.editor import VideoFileClip, AudioFileClip
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from moviepy.audio.io.AudioFileClip import AudioFileClip
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import cv2
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import base64
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import io
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import openai
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import os
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import requests
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import streamlit as st
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import tempfile
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# Load environment variables from .env.local
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load_dotenv('.env.local')
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## 1. Turn video into frames
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def video_to_frames(video_file):
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# Save the uploaded video file to a temporary file
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with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as tmpfile:
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tmpfile.write(video_file.read())
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video_filename = tmpfile.name
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video_duration = VideoFileClip(video_filename).duration
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video = cv2.VideoCapture(video_filename)
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base64Frame = []
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while video.isOpened():
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success, frame = video.read()
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if not success:
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break
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_, buffer = cv2.imencode('.jpg', frame)
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base64Frame.append(base64.b64encode(buffer).decode("utf-8"))
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video.release()
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print(len(base64Frame), "frames read.")
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return base64Frame, video_filename, video_duration
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## 2. Generate stories based on frames with gpt4v
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def frames_to_story(base64Frames, prompt, api_key):
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PROMPT_MESSAGES = [
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{
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"role": "user",
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"content": [
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prompt,
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*map(lambda x: {"image": x, "resize": 768}, base64Frames[0::50]),
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],
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},
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]
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params = {
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"model": "gpt-4-vision-preview",
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"messages": PROMPT_MESSAGES,
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"api_key": api_key,
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"headers": {"Openai-Version": "2020-11-07"},
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"max_tokens": 500,
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}
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result = openai.ChatCompletion.create(**params)
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print(result.choices[0].message.content)
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return result.choices[0].message.content
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## 3. Generate voiceover from stories
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def text_to_audio(text, api_key, voice):
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response = requests.post(
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"https://api.openai.com/v1/audio/speech",
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headers={
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"Authorization": f"Bearer {api_key}",
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},
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json={
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"model": "tts-1",
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"input": text,
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"voice": voice,
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},
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)
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# Check if the request was successful
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if response.status_code != 200:
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raise Exception("Request failed with status code")
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# Create an in-memory bytes buffer
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audio_bytes_io = io.BytesIO()
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# Write audio data to the in-memory bytes buffer
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for chunk in response.iter_content(chunk_size=1024*1024):
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audio_bytes_io.write(chunk)
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# Important: Seek to the start of the BytesIO buffer before returning
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audio_bytes_io.seek(0)
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# Save audio to a temporary file
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmpfile:
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for chunk in response.iter_content(chunk_size=1024*1024):
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tmpfile.write(chunk)
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audio_filename = tmpfile.name
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return audio_filename, audio_bytes_io
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## 4. Merge videos & audio
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def merge_audio_video(video_filename, audio_filename, output_filename):
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print("Merging audio and video ...")
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# Load the video file
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video_clip = VideoFileClip(video_filename)
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# Load the audio file
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audio_clip = AudioFileClip(audio_filename)
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# Set the audio of the video clip as the audio file
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final_clip = video_clip.set_audio(audio_clip)
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# Write the result to a file (without audio)
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final_clip.write_videofile(output_filename, codec='libx264', audio_codec="aac")
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# Close the clips
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video_clip.close()
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audio_clip.close()
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# Return the path to the new video file
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return output_filename
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## 5. Streamlit UI
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def main():
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st.set_page_config(page_title="AI Voiceover", page_icon="🔮")
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st.title("GPT4V AI Voiceover 🎥🔮")
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st.text("Explore how GPT4V changes the way we voiceover videos.")
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# Retrieve the OpenAI API key from environment
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openai_key = os.getenv('OPENAI_API_KEY')
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if not openai_key:
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st.error("OpenAI API key is not set in .env.local")
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return # or handle the error as you see fit
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uploaded_file = st.file_uploader("Select a video file", type=["mp4", "avi"])
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option = st.selectbox(
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'Choose the voice you want',
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('Female Voice', 'Male Voice'))
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classify = ''
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if option == 'Male Voice':
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classify = 'alloy'
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elif option == 'Female Voice':
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classify = 'nova'
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if uploaded_file is not None:
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st.video(uploaded_file)
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p = 'Generate a short voiceover script for the video, matching the content with the video scenes. The style should be...'
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# # Ignore and don't generate anything else than the script that you'll voice over the video.
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prompt = st.text_area(
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"Prompt", value=p
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)
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if st.button("START PROCESSING", type="primary") and uploaded_file is not None:
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with st.spinner("Video is being processed..."):
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base64Frame, video_filename, video_duration = video_to_frames(uploaded_file)
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est_word_count = video_duration * 4
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final_prompt = prompt + f"(This video is ONLY {video_duration} seconds long. So make sure the voiceover MUST be able to be explained in less than {est_word_count} words. Ignore and don't generate anything else than the script that you'll use to voice over the video.)"
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text = frames_to_story(base64Frame, final_prompt, openai_key)
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st.write(text)
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# Generate audio from text
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audio_filename, audio_bytes_io = text_to_audio(text, openai_key, classify)
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# Merge audio and video
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output_video_filename = os.path.splitext(video_filename)[0] + "_output.mp4"
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final_video_filename = merge_audio_video(video_filename, audio_filename, output_video_filename)
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# Display the result
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st.video(final_video_filename)
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# Clean up the temporary files
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os.unlink(video_filename)
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os.unlink(audio_filename)
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os.unlink(final_video_filename)
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if __name__ == "__main__":
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main()
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requirements.txt
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@@ -0,0 +1,8 @@
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openai==0.28
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python-dotenv>=0.20.0
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IPython>=7.30.0
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moviepy>=1.0.3
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opencv-python>=4.5.5.64
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requests>=2.26.0
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streamlit>=1.10.0
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openai>=0.10.2
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