Update app.py

app.py

@@ -609,7 +609,7 @@ def add_transcript_voiceover(video_path, translated_json, output_path, process_m
 
     with concurrent.futures.ThreadPoolExecutor() as executor:
         futures = [executor.submit(process_entry, entry, i, tts_model, video.w, video.h, process_mode, target_language, font_path, speaker_sample_paths)
-                   for i, entry in enumerate(translated_json_withspeed)]
+                   for i, entry in enumerate(translated_json)]
 
         results = []
         for future in concurrent.futures.as_completed(futures):
@@ -837,14 +837,14 @@ def upload_and_manage(file, target_language, process_mode):
         # Step 2: Translate the transcription
         logger.info(f"Translating transcription from {source_language} to {target_language}...")
         translated_json_raw = translate_text(transcription_json, source_language, target_language)
-        logger.info(f"Translation completed. Number of translated segments: {len(translated_json)}")
+        logger.info(f"Translation completed. Number of translated segments: {len(translated_json_raw)}")
 
         # translated_json = post_edit_translated_segments(translated_json, file.name)
         translated_json = apply_adaptive_speed(translated_json_raw, source_language, target_language)
         
         # Step 3: Add transcript to video based on timestamps
         logger.info("Adding translated transcript to video...")
-        add_transcript_voiceover(file.name, translated_json_speedcontrol, output_video_path, process_mode, target_language)
+        add_transcript_voiceover(file.name, translated_json, output_video_path, process_mode, target_language)
         logger.info(f"Transcript added to video. Output video saved at {output_video_path}")
 
         # Convert translated JSON into a format for the editable table