Newest 'ffmpeg' Questions - Stack Overflow
Les articles publiés sur le site
-
Cutting multimedia files based on start and end time using ffmpeg [closed]
25 juillet, par KalaiyarasanI tried to cut the video using the start and end time of the video by using the following command:
ffmpeg -ss 00:00:03 -t 00:00:08 -i movie.mp4 -acodec copy -vcodec copy -async 1 cut.mp4By using the above command I want to cut the video from
00:00:03to00:00:08. But it is not cutting the video between those times instead of that it is cutting the video with first 11 seconds. -
How to Stream Audio from Google Cloud Storage in Chunks and Convert Each Chunk to WAV for Whisper Transcription
25 juillet, par Douglas LandvikI'm working on a project where I need to transcribe audio stored in a Google Cloud Storage bucket using OpenAI's Whisper model. The audio is stored in WebM format with Opus encoding, and due to the file size, I'm streaming the audio in 30-second chunks.
To convert each chunk to WAV (16 kHz, mono, 16-bit PCM) compatible with Whisper, I'm using FFmpeg. The first chunk converts successfully, but subsequent chunks fail to convert. I suspect this is because each chunk lacks the WebM container's header, which FFmpeg needs to interpret the Opus codec correctly.
Here’s a simplified version of my approach:
Download Chunk: I download each chunk from GCS as bytes. Convert with FFmpeg: I pass the bytes to FFmpeg to convert each chunk from WebM/Opus to WAV.
async def handle_transcription_and_notify( consultation_service: ConsultationService, consultation_processor: ConsultationProcessor, consultation: Consultation, language: str, notes: str, clinic_id: str, vet_email: str, trace_id: str, blob_path: str, max_retries: int = 3, retry_delay: int = 5, max_concurrent_tasks: int = 3 ): """ Handles the transcription process by streaming the file from GCS, converting to a compatible format, and notifying the client via WebSocket. """ chunk_duration_sec = 30 # 30 seconds per chunk logger.info(f"Starting transcription process for consultation {consultation.consultation_id}", extra={'trace_id': trace_id}) # Initialize GCS client service_account_key = os.environ.get('SERVICE_ACCOUNT_KEY_BACKEND') if not service_account_key: logger.error("Service account key not found in environment variables", extra={'trace_id': trace_id}) await send_discord_alert( f"Service account key not found for consultation {consultation.consultation_id}.\nTrace ID: {trace_id}" ) return try: service_account_info = json.loads(service_account_key) credentials = service_account.Credentials.from_service_account_info(service_account_info) except Exception as e: logger.error(f"Error loading service account credentials: {str(e)}", extra={'trace_id': trace_id}) await send_discord_alert( f"Error loading service account credentials for consultation {consultation.consultation_id}.\nError: {str(e)}\nTrace ID: {trace_id}" ) return # Initialize GCS client service_account_key = os.environ.get('SERVICE_ACCOUNT_KEY_BACKEND') if not service_account_key: logger.error("Service account key not found in environment variables", extra={'trace_id': trace_id}) await send_discord_alert( f"Service account key not found for consultation {consultation.consultation_id}.\nTrace ID: {trace_id}" ) return try: service_account_info = json.loads(service_account_key) credentials = service_account.Credentials.from_service_account_info(service_account_info) except Exception as e: logger.error(f"Error loading service account credentials: {str(e)}", extra={'trace_id': trace_id}) await send_discord_alert( f"Error loading service account credentials for consultation {consultation.consultation_id}.\nError: {str(e)}\nTrace ID: {trace_id}" ) return storage_client = storage.Client(credentials=credentials) bucket_name = 'vetz_consultations' blob = storage_client.bucket(bucket_name).get_blob(blob_path) bytes_per_second = 16000 * 2 # 32,000 bytes per second chunk_size_bytes = 30 * bytes_per_second size = blob.size async def stream_blob_in_chunks(blob, chunk_size): loop = asyncio.get_running_loop() start = 0 size = blob.size while start < size: end = min(start + chunk_size - 1, size - 1) try: logger.info(f"Requesting chunk from {start} to {end}", extra={'trace_id': trace_id}) chunk = await loop.run_in_executor( None, lambda: blob.download_as_bytes(start=start, end=end) ) if not chunk: break logger.info(f"Yielding chunk from {start} to {end}, size: {len(chunk)} bytes", extra={'trace_id': trace_id}) yield chunk start += chunk_size except Exception as e: logger.error(f"Error downloading chunk from {start} to {end}: {str(e)}", exc_info=True, extra={'trace_id': trace_id}) raise e async def convert_to_wav(chunk_bytes, chunk_idx): """ Convert audio chunk to WAV format compatible with Whisper, ensuring it's 16 kHz, mono, and 16-bit PCM. """ try: logger.debug(f"Processing chunk {chunk_idx}: size = {len(chunk_bytes)} bytes") detected_format = await detect_audio_format(chunk_bytes) logger.info(f"Detected audio format for chunk {chunk_idx}: {detected_format}") input_io = io.BytesIO(chunk_bytes) output_io = io.BytesIO() # ffmpeg command to convert webm/opus to WAV with 16 kHz, mono, and 16-bit PCM # ffmpeg command with debug information ffmpeg_command = [ "ffmpeg", "-loglevel", "debug", "-f", "s16le", # Treat input as raw PCM data "-ar", "48000", # Set input sample rate "-ac", "1", # Set input to mono "-i", "pipe:0", "-ar", "16000", # Set output sample rate to 16 kHz "-ac", "1", # Ensure mono output "-sample_fmt", "s16", # Set output format to 16-bit PCM "-f", "wav", # Output as WAV format "pipe:1" ] process = subprocess.Popen( ffmpeg_command, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE ) stdout, stderr = process.communicate(input=input_io.read()) if process.returncode == 0: logger.info(f"FFmpeg conversion completed successfully for chunk {chunk_idx}") output_io.write(stdout) output_io.seek(0) # Save the WAV file locally for listening output_dir = "converted_chunks" os.makedirs(output_dir, exist_ok=True) file_path = os.path.join(output_dir, f"chunk_{chunk_idx}.wav") with open(file_path, "wb") as f: f.write(stdout) logger.info(f"Chunk {chunk_idx} saved to {file_path}") return output_io else: logger.error(f"FFmpeg failed for chunk {chunk_idx} with return code {process.returncode}") logger.error(f"Chunk {chunk_idx} - FFmpeg stderr: {stderr.decode()}") return None except Exception as e: logger.error(f"Unexpected error in FFmpeg conversion for chunk {chunk_idx}: {str(e)}") return None async def transcribe_chunk(idx, chunk_bytes): for attempt in range(1, max_retries + 1): try: logger.info(f"Transcribing chunk {idx + 1} (attempt {attempt}).", extra={'trace_id': trace_id}) # Convert to WAV format wav_io = await convert_to_wav(chunk_bytes, idx) if not wav_io: logger.error(f"Failed to convert chunk {idx + 1} to WAV format.") return "" wav_io.name = "chunk.wav" chunk_transcription = await consultation_processor.transcribe_audio_whisper(wav_io) logger.info(f"Chunk {idx + 1} transcribed successfully.", extra={'trace_id': trace_id}) return chunk_transcription except Exception as e: logger.error(f"Error transcribing chunk {idx + 1} (attempt {attempt}): {str(e)}", exc_info=True, extra={'trace_id': trace_id}) if attempt < max_retries: await asyncio.sleep(retry_delay) else: await send_discord_alert( f"Max retries reached for chunk {idx + 1} in consultation {consultation.consultation_id}.\nError: {str(e)}\nTrace ID: {trace_id}" ) return "" # Return empty string for failed chunk await notification_manager.send_personal_message( f"Consultation {consultation.consultation_id} is being transcribed.", vet_email ) try: idx = 0 full_transcription = [] async for chunk in stream_blob_in_chunks(blob, chunk_size_bytes): transcription = await transcribe_chunk(idx, chunk) if transcription: full_transcription.append(transcription) idx += 1 combined_transcription = " ".join(full_transcription) consultation.full_transcript = (consultation.full_transcript or "") + " " + combined_transcription consultation_service.save_consultation(clinic_id, vet_email, consultation) logger.info(f"Transcription saved for consultation {consultation.consultation_id}.", extra={'trace_id': trace_id}) except Exception as e: logger.error(f"Error during transcription process: {str(e)}", exc_info=True, extra={'trace_id': trace_id}) await send_discord_alert( f"Error during transcription process for consultation {consultation.consultation_id}.\nError: {str(e)}\nTrace ID: {trace_id}" ) return await notification_manager.send_personal_message( f"Consultation {consultation.consultation_id} has been transcribed.", vet_email ) try: template_service = TemplateService() medical_record_template = template_service.get_template_by_name( consultation.medical_record_template_id).sections sections = await consultation_processor.extract_structured_sections( transcription=consultation.full_transcript, notes=notes, language=language, template=medical_record_template, ) consultation.sections = sections consultation_service.save_consultation(clinic_id, vet_email, consultation) logger.info(f"Sections processed for consultation {consultation.consultation_id}.", extra={'trace_id': trace_id}) except Exception as e: logger.error(f"Error processing sections for consultation {consultation.consultation_id}: {str(e)}", exc_info=True, extra={'trace_id': trace_id}) await send_discord_alert( f"Error processing sections for consultation {consultation.consultation_id}.\nError: {str(e)}\nTrace ID: {trace_id}" ) raise e await notification_manager.send_personal_message( f"Consultation {consultation.consultation_id} is fully processed.", vet_email ) logger.info(f"Successfully processed consultation {consultation.consultation_id}.", extra={'trace_id': trace_id}) -
FFMPEG remote IP camera over RTSP h.264 format to HLS Localhost m3u8 format [closed]
25 juillet, par macmeyers50I'm trying to convert the remote IP camera over RTSP to a localhost HLS format so that I can display it in a UI. I'm using a java library that only supports HLS over HTTP not remote IP camera.
I'm under the impression FFMPEG can do this because I can write the HLS file just fine directly to my disc but when I change the target to something like http://localhost:8080/stream.m3u8 it cannot seem to connect to localhost.
Below is my attempted FFMPEG command (IP/User/Pass left off) but I know that it can at least connect and read the RTSP camera fine.
ffmpeg -i rtsp://[Username]:[Password]@[IP]/axis-media/media.amp?videocodec=h264 -rtsp_transport ffplay http://localhost:8080/media.m3u8The error I'm getting back is Connection to tcp://localhost:8080 failed: Error number -138 occurred
I thought that ffmpeg could handle hosting the file on localhost itself. FFServer is deprecated and removed but according to documentation it can still kick up a server just fine
-
How can I seek and read in a video file that is served by a web server ? [closed]
24 juillet, par DanHow do you suggest to make an script to decode frames from an MP4 video by its URL without downloading the whole file just like what FFmpeg does with extracting frames out of a local file but I want to do the same by passing in a URL?
-
FFmpeg : About filter_complex command [closed]
24 juillet, par HJ KimI use this command.
ffmpeg -i Input.mp4 -i logo.png -c:v h264_nvenc -filter_complex "[0:v]scale=-1:720[video];[1:v][video]scale2ref=(iw/ih)*ih/8/sar:ih/8[wm][base];[base][wm]overlay=10:10" output.mp4But what does this mean?
scale2ref=(iw/ih)*ih/8/sar:ih/8
