Update app.py

app.py

@@ -12,10 +12,7 @@ import json
 import os
 from moviepy.editor import ImageSequenceClip
 from gradio_client import Client, file
-    # https://16d3-2a0d-6fc2-61b1-8500-5d45-b385-9a4d-5522.ngrok-free.app/video_feed
-    # rtsp://admin:[email protected]:5678/Streaming/Channels/101
-    
-import os
+import subprocess
 
 api_key = os.getenv("OPEN_AI_KEY")
 user_name = os.getenv("USER_NAME")
@@ -41,6 +38,17 @@ client = openai.OpenAI(api_key=api_key)
 stop_capture = False
 alerts_mode = True
 
+def clip_video_segment(input_video_path, start_time, duration):
+    os.makedirs('videos', exist_ok=True)
+    output_video_path = f"videos/{uuid.uuid4()}.mp4"
+
+    subprocess.call([
+        'ffmpeg', '-y', '-ss', str(start_time), '-i', input_video_path,
+        '-t', str(duration), '-c', 'copy', output_video_path
+    ])
+
+    return output_video_path
+
 def encode_to_video_fast(frames, fps):
     
     os.makedirs('videos', exist_ok=True)
@@ -148,21 +156,21 @@ def process_clip(prompt, frames, chatbot):
                 f.write(frame_data)
             frame_paths.append(frame_path)
 
-def process_clip_from_file(prompt, frames, chatbot, fps):
+def process_clip_from_file(prompt, frames, chatbot, fps, video_path, id):
     global stop_capture
     if not stop_capture:
         israel_tz = pytz.timezone('Asia/Jerusalem')
         start_time = datetime.now(israel_tz).strftime('%H:%M:%S')
         print("[Start]:", start_time, len(frames))
         
-        fps = 20
-        frames_to_skip = int(fps * 1)
+        frames_to_skip = int(fps)
         base64Frames = process_frames(frames, frames_to_skip)
         frames_count, processing_time, api_response = check_condition(prompt, base64Frames)
         
         result = None
         if api_response and api_response.get("condition_met", False):
-            video_clip_path = encode_to_video_fast(frames, fps)
+            # video_clip_path = encode_to_video_fast(frames, fps)
+            video_clip_path = clip_video_segment(video_path, id*LENGTH, (id+1)*LENGTH)
             chatbot.append(((video_clip_path,), None))
             chatbot.append((f"Time: {start_time}\nDetails: {api_response.get('details', '')}", None))
     
@@ -206,6 +214,7 @@ def analyze_video_file(prompt, video_path, chatbot):
     frames_per_chunk = fps * LENGTH  # Number of frames per 5-second chunk
     
     frames = []
+    chunk = 0
     
     # Create a thread pool for concurrent processing
     with ThreadPoolExecutor(max_workers=4) as executor:
@@ -219,12 +228,14 @@ def analyze_video_file(prompt, video_path, chatbot):
             
             # Split the video into chunks of frames corresponding to 5 seconds
             if len(frames) >= frames_per_chunk:
-                futures.append(executor.submit(process_clip_from_file, prompt, frames.copy(), chatbot, fps))
+                futures.append(executor.submit(process_clip_from_file, prompt, frames.copy(), chatbot, fps, video_path, chunk))
                 frames = []
+                chunk++
         
         # If any remaining frames that are less than 5 seconds, process them as a final chunk
         if len(frames) > 0:
-            futures.append(executor.submit(process_clip_from_file, prompt, frames.copy(), chatbot, fps))
+            futures.append(executor.submit(process_clip_from_file, prompt, frames.copy(), chatbot, fps, video_path, chunk))
+            chunk++
         
         cap.release()
         # Yield results as soon as each thread completes