mp4保存
This commit is contained in:
parent
eeb8400727
commit
c15cd659e3
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@ -5,36 +5,36 @@ Manages the server process and handles HTTP communication
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using standard library (avoiding requests dependency).
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"""
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import subprocess
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import time
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import json
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import urllib.request
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import urllib.error
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import threading
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import os
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import signal
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from typing import Optional, Dict, Any, Tuple
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import subprocess
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import threading
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import time
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import urllib.error
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import urllib.request
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from typing import Any, Dict, Optional, Tuple
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class InferenceClient:
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"""Client for the YOLO inference server."""
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SERVER_URL = "http://127.0.0.1:8181"
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def __init__(self):
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self.server_process: Optional[subprocess.Popen] = None
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self._server_lock = threading.Lock()
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self.log_file = None
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self.log_file_path = None
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def start_server(self):
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"""Start the inference server process."""
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with self._server_lock:
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if self.is_server_running():
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return
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print("[FaceMask] Starting inference server...")
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# Find project root
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# Assuming this file is in core/inference_client.py
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root_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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@ -46,24 +46,24 @@ class InferenceClient:
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# Load environment variables from .env file if it exists
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env_file = os.path.join(root_dir, ".env")
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if os.path.exists(env_file):
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with open(env_file, 'r') as f:
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with open(env_file, "r") as f:
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for line in f:
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line = line.strip()
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if line and not line.startswith('#') and '=' in line:
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key, value = line.split('=', 1)
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if line and not line.startswith("#") and "=" in line:
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key, value = line.split("=", 1)
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server_env[key] = value
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print(f"[FaceMask] Loaded environment from: {env_file}")
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# Clean PYTHONPATH to avoid conflicts with Nix Python packages
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# Only include project root to allow local imports
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server_env['PYTHONPATH'] = root_dir
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server_env["PYTHONPATH"] = root_dir
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# Remove Python-related environment variables that might cause conflicts
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# These can cause venv to import packages from Nix instead of venv
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env_vars_to_remove = [
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'PYTHONUNBUFFERED',
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'__PYVENV_LAUNCHER__', # macOS venv variable
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'VIRTUAL_ENV', # Will be set by venv's Python automatically
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"PYTHONUNBUFFERED",
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"__PYVENV_LAUNCHER__", # macOS venv variable
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"VIRTUAL_ENV", # Will be set by venv's Python automatically
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]
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for var in env_vars_to_remove:
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server_env.pop(var, None)
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@ -73,25 +73,27 @@ class InferenceClient:
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if os.path.isdir(venv_bin):
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# Build a clean PATH with venv first, then essential system paths
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# Filter out any Nix Python-specific paths to avoid version conflicts
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current_path = server_env.get('PATH', '')
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path_entries = current_path.split(':')
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current_path = server_env.get("PATH", "")
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path_entries = current_path.split(":")
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# Filter out Nix Python 3.11 paths
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filtered_paths = [
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p for p in path_entries
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if not ('/python3.11/' in p.lower() or '/python3-3.11' in p.lower())
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p
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for p in path_entries
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if not ("/python3.11/" in p.lower() or "/python3-3.11" in p.lower())
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]
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# Reconstruct PATH with venv first
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clean_path = ':'.join([venv_bin] + filtered_paths)
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server_env['PATH'] = clean_path
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clean_path = ":".join([venv_bin] + filtered_paths)
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server_env["PATH"] = clean_path
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print(f"[FaceMask] Using venv from: {venv_bin}")
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# Prepare log file for server output
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import tempfile
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log_dir = tempfile.gettempdir()
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self.log_file_path = os.path.join(log_dir, "facemask_server.log")
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self.log_file = open(self.log_file_path, 'w', buffering=1) # Line buffered
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self.log_file = open(self.log_file_path, "w", buffering=1) # Line buffered
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print(f"[FaceMask] Server log: {self.log_file_path}")
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# Start process with 'python' command (will use venv if PATH is set correctly)
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@ -120,12 +122,12 @@ class InferenceClient:
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try:
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if self.log_file:
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self.log_file.close()
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with open(self.log_file_path, 'r') as f:
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with open(self.log_file_path, "r") as f:
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log_content = f.read()
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if log_content.strip():
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print("[FaceMask] Server log:")
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# Show last 50 lines
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lines = log_content.strip().split('\n')
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lines = log_content.strip().split("\n")
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for line in lines[-50:]:
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print(line)
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except Exception as e:
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@ -143,18 +145,18 @@ class InferenceClient:
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try:
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if self.log_file:
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self.log_file.close()
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with open(self.log_file_path, 'r') as f:
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with open(self.log_file_path, "r") as f:
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log_content = f.read()
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if log_content.strip():
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print("[FaceMask] Server log (partial):")
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lines = log_content.strip().split('\n')
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lines = log_content.strip().split("\n")
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for line in lines[-30:]:
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print(line)
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except Exception:
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pass
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raise RuntimeError("Server startup timed out")
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def stop_server(self):
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"""Stop the inference server."""
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with self._server_lock:
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@ -175,15 +177,17 @@ class InferenceClient:
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except Exception:
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pass
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self.log_file = None
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def is_server_running(self) -> bool:
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"""Check if server is responding."""
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try:
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with urllib.request.urlopen(f"{self.SERVER_URL}/status", timeout=1) as response:
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with urllib.request.urlopen(
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f"{self.SERVER_URL}/status", timeout=1
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) as response:
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return response.status == 200
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except (urllib.error.URLError, ConnectionRefusedError, TimeoutError):
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return False
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def generate_mask(
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self,
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video_path: str,
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@ -196,13 +200,13 @@ class InferenceClient:
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) -> str:
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"""
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Request mask generation.
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Returns:
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task_id (str)
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"""
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if not self.is_server_running():
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self.start_server()
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data = {
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"video_path": video_path,
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"output_dir": output_dir,
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@ -212,35 +216,36 @@ class InferenceClient:
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"iou_threshold": iou_threshold,
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"mask_scale": mask_scale,
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}
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req = urllib.request.Request(
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f"{self.SERVER_URL}/generate",
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data=json.dumps(data).encode('utf-8'),
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headers={'Content-Type': 'application/json'},
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method='POST'
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data=json.dumps(data).encode("utf-8"),
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headers={"Content-Type": "application/json"},
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method="POST",
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)
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try:
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with urllib.request.urlopen(req) as response:
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result = json.loads(response.read().decode('utf-8'))
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return result['id']
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result = json.loads(response.read().decode("utf-8"))
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return result["id"]
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except urllib.error.HTTPError as e:
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raise RuntimeError(f"Server error: {e.read().decode('utf-8')}")
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def get_task_status(self, task_id: str) -> Dict[str, Any]:
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"""Get status of a task."""
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try:
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with urllib.request.urlopen(f"{self.SERVER_URL}/tasks/{task_id}") as response:
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return json.loads(response.read().decode('utf-8'))
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with urllib.request.urlopen(
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f"{self.SERVER_URL}/tasks/{task_id}"
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) as response:
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return json.loads(response.read().decode("utf-8"))
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except urllib.error.HTTPError:
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return {"status": "unknown"}
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def cancel_task(self, task_id: str):
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"""Cancel a task."""
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try:
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req = urllib.request.Request(
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f"{self.SERVER_URL}/tasks/{task_id}/cancel",
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method='POST'
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f"{self.SERVER_URL}/tasks/{task_id}/cancel", method="POST"
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)
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with urllib.request.urlopen(req):
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pass
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@ -251,6 +256,7 @@ class InferenceClient:
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# Singleton
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_client: Optional[InferenceClient] = None
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def get_client() -> InferenceClient:
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global _client
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if _client is None:
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@ -48,8 +48,8 @@
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export ROCM_PATH="${pkgs.rocmPackages.clr}"
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export HSA_OVERRIDE_GFX_VERSION="11.0.0" # RX 7900 (RDNA 3 / gfx1100)
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# LD_LIBRARY_PATH: ROCm、C++標準ライブラリ、その他必要なライブラリ
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export LD_LIBRARY_PATH="${pkgs.stdenv.cc.cc.lib}/lib:${pkgs.zlib}/lib:${pkgs.zstd.out}/lib:${pkgs.rocmPackages.clr}/lib:${pkgs.rocmPackages.rocm-runtime}/lib:$LD_LIBRARY_PATH"
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# LD_LIBRARY_PATH: ROCm libraries FIRST (critical for GPU inference)
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export LD_LIBRARY_PATH="${pkgs.rocmPackages.clr}/lib:${pkgs.rocmPackages.rocm-runtime}/lib:${pkgs.stdenv.cc.cc.lib}/lib:${pkgs.zlib}/lib:${pkgs.zstd.out}/lib:$LD_LIBRARY_PATH"
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# venvのセットアップ
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VENV_DIR="$PWD/.venv"
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export BLENDER_USER_ADDONS="$BLENDER_USER_SCRIPTS/addons"
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# 環境変数をファイルに保存（サーバープロセス用）
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# CRITICAL: ROCm library paths MUST come first for GPU inference
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cat > "$PWD/.env" << EOF
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LD_LIBRARY_PATH=${pkgs.stdenv.cc.cc.lib}/lib:${pkgs.zlib}/lib:${pkgs.zstd.out}/lib:${pkgs.rocmPackages.clr}/lib:${pkgs.rocmPackages.rocm-runtime}/lib
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LD_LIBRARY_PATH=${pkgs.rocmPackages.clr}/lib:${pkgs.rocmPackages.rocm-runtime}/lib:${pkgs.stdenv.cc.cc.lib}/lib:${pkgs.zlib}/lib:${pkgs.zstd.out}/lib
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ROCM_PATH=${pkgs.rocmPackages.clr}
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HSA_OVERRIDE_GFX_VERSION=11.0.0
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PYTORCH_ROCM_ARCH=gfx1100
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ROCBLAS_TENSILE_LIBPATH=${pkgs.rocmPackages.clr}/lib/rocblas/library
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EOF
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echo "[Setup] Environment ready with GPU support"
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@ -143,54 +143,109 @@ class SEQUENCER_OT_generate_face_mask(Operator):
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def _check_cache(self, cache_dir: str, expected_frames: int) -> bool:
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"""Check if cached masks exist and are complete.
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Args:
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cache_dir: Path to cache directory
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expected_frames: Number of frames expected
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Returns:
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True if cache exists and has at least 90% of expected frames
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True if cache exists and is valid
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"""
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if not os.path.exists(cache_dir):
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return False
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mask_files = [f for f in os.listdir(cache_dir)
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# Check for MP4 video (new format)
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mask_video = os.path.join(cache_dir, "mask.mp4")
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if os.path.exists(mask_video):
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# Verify video has expected number of frames
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import cv2
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cap = cv2.VideoCapture(mask_video)
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if cap.isOpened():
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frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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cap.release()
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# Accept cache if at least 90% of frames exist
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return frame_count >= expected_frames * 0.9
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cap.release()
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return False
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# Fallback: check for PNG sequence (backward compatibility)
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mask_files = [f for f in os.listdir(cache_dir)
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if f.startswith("mask_") and f.endswith(".png")]
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# Accept cache if at least 90% of frames exist
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# (some frames may have been skipped due to read errors)
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return len(mask_files) >= expected_frames * 0.9
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def _add_mask_strip(self, context, source_strip_name: str, mask_dir: str):
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"""Add mask image sequence as a new strip."""
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def _add_mask_strip(self, context, source_strip_name: str, mask_path: str):
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"""Add mask video as a new strip.
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Args:
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context: Blender context
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source_strip_name: Name of the source video strip
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mask_path: Path to mask video file or directory (for backward compatibility)
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"""
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scene = context.scene
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seq_editor = scene.sequence_editor
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if not seq_editor:
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return
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# Find source strip (Blender 5.0 uses 'strips' instead of 'sequences')
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source_strip = seq_editor.strips.get(source_strip_name)
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if not source_strip:
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return
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# Get first mask image
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mask_files = sorted([
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f for f in os.listdir(mask_dir)
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if f.startswith("mask_") and f.endswith(".png")
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])
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if not mask_files:
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return
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first_mask = os.path.join(mask_dir, mask_files[0])
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# Check if mask_path is a video file or directory (backward compatibility)
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if os.path.isfile(mask_path):
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# New format: single MP4 file
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mask_video = mask_path
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else:
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# Old format: directory with PNG sequence (backward compatibility)
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mask_video = os.path.join(mask_path, "mask.mp4")
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if not os.path.exists(mask_video):
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# Fallback to PNG sequence
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mask_files = sorted([
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f for f in os.listdir(mask_path)
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if f.startswith("mask_") and f.endswith(".png")
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])
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if not mask_files:
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return
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first_mask = os.path.join(mask_path, mask_files[0])
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self._add_mask_strip_png_sequence(context, source_strip_name, mask_path, mask_files, first_mask)
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return
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# Find an empty channel
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used_channels = {s.channel for s in seq_editor.strips}
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new_channel = source_strip.channel + 1
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while new_channel in used_channels:
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new_channel += 1
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# Add movie strip (Blender 5.0 API)
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mask_strip = seq_editor.strips.new_movie(
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name=f"{source_strip_name}_mask",
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filepath=mask_video,
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channel=new_channel,
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frame_start=source_strip.frame_final_start,
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)
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# Set blend mode for mask
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mask_strip.blend_type = 'ALPHA_OVER'
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mask_strip.blend_alpha = 0.5
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def _add_mask_strip_png_sequence(self, context, source_strip_name, mask_dir, mask_files, first_mask):
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"""Backward compatibility: Add PNG sequence as mask strip."""
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scene = context.scene
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seq_editor = scene.sequence_editor
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source_strip = seq_editor.strips.get(source_strip_name)
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if not source_strip:
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return
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# Find an empty channel
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used_channels = {s.channel for s in seq_editor.strips}
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new_channel = source_strip.channel + 1
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while new_channel in used_channels:
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new_channel += 1
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# Add image sequence (Blender 5.0 API)
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mask_strip = seq_editor.strips.new_image(
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name=f"{source_strip_name}_mask",
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@ -198,11 +253,11 @@ class SEQUENCER_OT_generate_face_mask(Operator):
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channel=new_channel,
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frame_start=source_strip.frame_final_start,
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)
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# Add remaining frames
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for mask_file in mask_files[1:]:
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mask_strip.elements.append(mask_file)
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# Set blend mode for mask
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mask_strip.blend_type = 'ALPHA_OVER'
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mask_strip.blend_alpha = 0.5
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132
server/main.py
132
server/main.py
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@ -8,6 +8,29 @@ GPU-accelerated face detection using ONNX Runtime.
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import os
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import sys
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import platform
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# CRITICAL: Fix LD_LIBRARY_PATH before importing cv2 or torch
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# cv2 adds its own lib path to the front, which can override ROCm libraries
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def fix_library_path():
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"""Ensure ROCm libraries are loaded before cv2's bundled libraries."""
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ld_path = os.environ.get('LD_LIBRARY_PATH', '')
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# Split and filter paths
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paths = [p for p in ld_path.split(':') if p]
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# Separate ROCm/GPU paths from other paths
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rocm_paths = [p for p in paths if 'rocm' in p.lower() or 'clr-' in p or 'hip' in p.lower()]
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other_paths = [p for p in paths if p not in rocm_paths]
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# Rebuild with ROCm paths first
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if rocm_paths:
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new_ld_path = ':'.join(rocm_paths + other_paths)
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os.environ['LD_LIBRARY_PATH'] = new_ld_path
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print(f"[FaceMask] Fixed LD_LIBRARY_PATH to prioritize ROCm libraries")
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# Fix library path BEFORE any other imports
|
||||
fix_library_path()
|
||||
|
||||
import threading
|
||||
import uuid
|
||||
import queue
|
||||
|
|
@ -61,11 +84,15 @@ class GenerateRequest(BaseModel):
|
|||
mask_scale: float = 1.5
|
||||
|
||||
def process_video_task(task_id: str, req: GenerateRequest):
|
||||
"""Background task to process video."""
|
||||
"""Background task to process video with async MP4 output."""
|
||||
writer = None
|
||||
write_queue = None
|
||||
writer_thread = None
|
||||
|
||||
try:
|
||||
tasks[task_id].status = TaskStatus.PROCESSING
|
||||
cancel_event = cancel_events.get(task_id)
|
||||
|
||||
|
||||
# Verify video exists
|
||||
if not os.path.exists(req.video_path):
|
||||
tasks[task_id].status = TaskStatus.FAILED
|
||||
|
|
@ -78,28 +105,60 @@ def process_video_task(task_id: str, req: GenerateRequest):
|
|||
conf_threshold=req.conf_threshold,
|
||||
iou_threshold=req.iou_threshold
|
||||
)
|
||||
# Ensure model is loaded
|
||||
_ = detector.model
|
||||
|
||||
|
||||
# Open video
|
||||
cap = cv2.VideoCapture(req.video_path)
|
||||
if not cap.isOpened():
|
||||
tasks[task_id].status = TaskStatus.FAILED
|
||||
tasks[task_id].message = "Failed to open video"
|
||||
return
|
||||
|
||||
# Determine frame range
|
||||
|
||||
# Get video properties
|
||||
fps = cap.get(cv2.CAP_PROP_FPS)
|
||||
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
|
||||
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
|
||||
total_video_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
|
||||
end_frame = min(req.end_frame, total_video_frames - 1)
|
||||
frames_to_process = end_frame - req.start_frame + 1
|
||||
|
||||
|
||||
tasks[task_id].total = frames_to_process
|
||||
|
||||
|
||||
# Ensure output directory exists
|
||||
os.makedirs(req.output_dir, exist_ok=True)
|
||||
|
||||
print(f"Starting processing: {req.video_path} ({frames_to_process} frames)")
|
||||
|
||||
|
||||
# Setup MP4 writer (grayscale)
|
||||
output_video_path = os.path.join(req.output_dir, "mask.mp4")
|
||||
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
|
||||
writer = cv2.VideoWriter(output_video_path, fourcc, fps, (width, height), isColor=False)
|
||||
|
||||
if not writer.isOpened():
|
||||
tasks[task_id].status = TaskStatus.FAILED
|
||||
tasks[task_id].message = "Failed to create video writer"
|
||||
cap.release()
|
||||
return
|
||||
|
||||
# Async writer setup
|
||||
write_queue = queue.Queue(maxsize=30) # Buffer up to 30 frames
|
||||
writer_running = threading.Event()
|
||||
writer_running.set()
|
||||
|
||||
def async_writer():
|
||||
"""Background thread for writing frames to video."""
|
||||
while writer_running.is_set() or not write_queue.empty():
|
||||
try:
|
||||
mask = write_queue.get(timeout=0.1)
|
||||
if mask is not None:
|
||||
writer.write(mask)
|
||||
write_queue.task_done()
|
||||
except queue.Empty:
|
||||
continue
|
||||
|
||||
writer_thread = threading.Thread(target=async_writer, daemon=True)
|
||||
writer_thread.start()
|
||||
|
||||
print(f"Starting processing: {req.video_path} ({frames_to_process} frames) -> {output_video_path}")
|
||||
|
||||
# Process loop
|
||||
current_count = 0
|
||||
for frame_idx in range(req.start_frame, end_frame + 1):
|
||||
|
|
@ -107,38 +166,44 @@ def process_video_task(task_id: str, req: GenerateRequest):
|
|||
tasks[task_id].status = TaskStatus.CANCELLED
|
||||
tasks[task_id].message = "Cancelled by user"
|
||||
break
|
||||
|
||||
|
||||
# Read frame
|
||||
cap.set(cv2.CAP_PROP_POS_FRAMES, frame_idx)
|
||||
ret, frame = cap.read()
|
||||
|
||||
|
||||
if ret:
|
||||
# Detect
|
||||
detections = detector.detect(frame)
|
||||
|
||||
|
||||
# Generate mask
|
||||
mask = detector.generate_mask(
|
||||
frame.shape,
|
||||
detections,
|
||||
mask_scale=req.mask_scale
|
||||
)
|
||||
|
||||
# Save
|
||||
mask_filename = f"mask_{current_count:06d}.png" # Note: using relative index for filename
|
||||
mask_path = os.path.join(req.output_dir, mask_filename)
|
||||
cv2.imwrite(mask_path, mask)
|
||||
|
||||
|
||||
# Async write to queue
|
||||
write_queue.put(mask)
|
||||
|
||||
# Update progress
|
||||
current_count += 1
|
||||
tasks[task_id].progress = current_count
|
||||
|
||||
|
||||
# Cleanup
|
||||
writer_running.clear()
|
||||
write_queue.join() # Wait for all frames to be written
|
||||
if writer_thread:
|
||||
writer_thread.join(timeout=5)
|
||||
|
||||
cap.release()
|
||||
|
||||
if writer:
|
||||
writer.release()
|
||||
|
||||
if tasks[task_id].status == TaskStatus.PROCESSING:
|
||||
tasks[task_id].status = TaskStatus.COMPLETED
|
||||
tasks[task_id].result_path = req.output_dir
|
||||
tasks[task_id].result_path = output_video_path # Return video path
|
||||
tasks[task_id].message = "Processing completed successfully"
|
||||
print(f"Task {task_id} completed.")
|
||||
print(f"Task {task_id} completed: {output_video_path}")
|
||||
|
||||
except Exception as e:
|
||||
tasks[task_id].status = TaskStatus.FAILED
|
||||
|
|
@ -230,12 +295,21 @@ def log_startup_diagnostics():
|
|||
for var in rocm_vars:
|
||||
value = os.environ.get(var)
|
||||
if value:
|
||||
# Truncate very long values
|
||||
if len(value) > 200:
|
||||
display_value = value[:200] + "... (truncated)"
|
||||
# For LD_LIBRARY_PATH, show if ROCm paths are included
|
||||
if var == 'LD_LIBRARY_PATH':
|
||||
has_rocm = 'rocm' in value.lower() or 'clr-' in value
|
||||
has_hip = 'hip' in value.lower()
|
||||
print(f" {var}: {value[:100]}...")
|
||||
print(f" Contains ROCm paths: {has_rocm}")
|
||||
print(f" Contains HIP paths: {has_hip}")
|
||||
if not has_rocm:
|
||||
print(f" ⚠️ WARNING: ROCm library paths not found!")
|
||||
else:
|
||||
display_value = value
|
||||
print(f" {var}: {display_value}")
|
||||
if len(value) > 200:
|
||||
display_value = value[:200] + "... (truncated)"
|
||||
else:
|
||||
display_value = value
|
||||
print(f" {var}: {display_value}")
|
||||
else:
|
||||
print(f" {var}: (not set)")
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user