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Update app.py
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app.py
CHANGED
@@ -10,7 +10,7 @@ from concurrent.futures import ThreadPoolExecutor, as_completed
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from datetime import datetime
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import json
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import os
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from moviepy.editor import ImageSequenceClip
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from gradio_client import Client, file
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import subprocess
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import ffmpeg
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@@ -89,19 +89,19 @@ def encode_to_video_fast(frames, fps):
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return video_clip_path
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def encode_to_video(frames, fps):
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# Function to process video frames using GPT-4 API
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def process_frames(frames, frames_to_skip = 1):
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@@ -167,7 +167,7 @@ def process_clip(prompt, frames, chatbot):
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if api_response["condition_met"] == True:
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finish_time = datetime.now(israel_tz).strftime('%H:%M:%S')
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video_clip_path =
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chatbot.append(((video_clip_path,), None))
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chatbot.append((f"Time: {start_time}\nDetails: {api_response.get('details', '')}", None))
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from datetime import datetime
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import json
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import os
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# from moviepy.editor import ImageSequenceClip
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from gradio_client import Client, file
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import subprocess
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import ffmpeg
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return video_clip_path
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# def encode_to_video(frames, fps):
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# os.makedirs('videos', exist_ok=True)
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# video_clip_path = f"videos/{uuid.uuid4()}.mp4"
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# # Create a video clip from the frames using moviepy
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# clip = ImageSequenceClip([frame[:, :, ::-1] for frame in frames], fps=fps) # Convert from BGR to RGB
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# clip.write_videofile(video_clip_path, codec="libx264")
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# # Convert the video file to base64
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# with open(video_clip_path, "rb") as video_file:
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# video_data = base64.b64encode(video_file.read()).decode('utf-8')
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# return video_clip_path
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# Function to process video frames using GPT-4 API
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def process_frames(frames, frames_to_skip = 1):
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if api_response["condition_met"] == True:
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finish_time = datetime.now(israel_tz).strftime('%H:%M:%S')
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video_clip_path = encode_to_video_fast(frames, fps)
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chatbot.append(((video_clip_path,), None))
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chatbot.append((f"Time: {start_time}\nDetails: {api_response.get('details', '')}", None))
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