youssef
commited on
Commit
·
abf26d0
1
Parent(s):
b841197
remove cuda ffmpeg
Browse files- Dockerfile +0 -2
- src/video_processor/processor.py +10 -37
Dockerfile
CHANGED
@@ -23,8 +23,6 @@ RUN apt-get update && \
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liblzma-dev \
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# gradio dependencies \
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ffmpeg \
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-
# NVIDIA Video Codec SDK \
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libnvidia-encode-12-3 \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/*
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liblzma-dev \
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# gradio dependencies \
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ffmpeg \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/*
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src/video_processor/processor.py
CHANGED
@@ -1,6 +1,6 @@
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import torch
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from transformers import AutoProcessor, AutoModelForImageTextToText
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from typing import List, Dict
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import logging
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import os
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import subprocess
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@@ -103,7 +103,7 @@ Be specific about visual details but stay concise."""}
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)
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return self.processor.batch_decode(outputs, skip_special_tokens=True)[0].split("Assistant: ")[-1]
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-
def process_video(self, video_path: str, segment_length: int = 10) ->
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try:
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# Create temp directory for segments
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temp_dir = tempfile.mkdtemp()
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@@ -128,49 +128,22 @@ Be specific about visual details but stay concise."""}
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cmd = [
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"ffmpeg",
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"-y", # Overwrite output files
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-
"-
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"-hwaccel_output_format", "cuda", # Keep frames in GPU memory
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"-threads", "0", # Use all available CPU threads
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"-thread_type", "frame", # Frame-level multi-threading
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"-i", video_path,
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"-ss", str(start_time), # Seek position
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"-t", str(end_time - start_time), # Duration
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"-c:v", "
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"-preset", "
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"-tune", "
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-
"-
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"-
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"-b:v", "0", # Let VBR control bitrate
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"-vf", "scale_cuda=640:-2", # GPU-accelerated scaling
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"-an", # Remove audio
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segment_path
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]
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ffmpeg_start = time.time()
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-
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result = subprocess.run(cmd, check=True, capture_output=True, text=True)
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logger.debug(f"FFmpeg output: {result.stderr}")
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except subprocess.CalledProcessError as e:
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logger.error(f"FFmpeg error: {e.stderr}")
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# Fallback to CPU if GPU encoding fails
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logger.warning("Falling back to CPU encoding")
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cmd = [
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"ffmpeg",
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"-y",
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"-threads", "0",
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"-i", video_path,
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"-ss", str(start_time),
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"-t", str(end_time - start_time),
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"-c:v", "libx264",
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"-preset", "ultrafast",
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"-tune", "fastdecode",
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"-crf", "28",
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"-vf", "scale=640:-2",
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"-an",
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"-pix_fmt", "yuv420p",
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segment_path
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]
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subprocess.run(cmd, check=True, capture_output=True)
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ffmpeg_time = time.time() - ffmpeg_start
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# Analyze segment
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import torch
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from transformers import AutoProcessor, AutoModelForImageTextToText
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+
from typing import List, Dict
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import logging
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import os
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import subprocess
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)
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return self.processor.batch_decode(outputs, skip_special_tokens=True)[0].split("Assistant: ")[-1]
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+
def process_video(self, video_path: str, segment_length: int = 10) -> List[Dict]:
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try:
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# Create temp directory for segments
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temp_dir = tempfile.mkdtemp()
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cmd = [
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"ffmpeg",
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"-y", # Overwrite output files
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"-threads", "4", # Use 4 threads
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"-i", video_path,
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"-ss", str(start_time), # Seek position
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"-t", str(end_time - start_time), # Duration
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"-c:v", "libx264", # Video codec
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"-preset", "ultrafast",
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"-tune", "fastdecode",
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"-crf", "28", # Lower quality but faster
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"-vf", "scale=640:-2", # Resize to smaller resolution
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"-an", # Remove audio
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"-pix_fmt", "yuv420p",
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segment_path
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]
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ffmpeg_start = time.time()
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subprocess.run(cmd, check=True, capture_output=True)
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ffmpeg_time = time.time() - ffmpeg_start
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# Analyze segment
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