blakeblackshear.frigate/frigate/util/downloader.py
Nicolas Mowen 13e90fc6e0 Face recognition backend (#14495)
* Add basic config and face recognition table

* Reconfigure updates processing to handle face

* Crop frame to face box

* Implement face embedding calculation

* Get matching face embeddings

* Add support face recognition based on existing faces

* Use arcface face embeddings instead of generic embeddings model

* Add apis for managing faces

* Implement face uploading API

* Build out more APIs

* Add min area config

* Handle larger images

* Add more debug logs

* fix calculation

* Reduce timeout

* Small tweaks

* Use webp images

* Use facenet model
2024-11-24 08:33:08 -07:00

148 lines
4.2 KiB
Python

import logging
import os
import threading
import time
from pathlib import Path
from typing import Callable, List
import requests
from frigate.comms.inter_process import InterProcessRequestor
from frigate.const import UPDATE_MODEL_STATE
from frigate.types import ModelStatusTypesEnum
logger = logging.getLogger(__name__)
class FileLock:
def __init__(self, path):
self.path = path
self.lock_file = f"{path}.lock"
# we have not acquired the lock yet so it should not exist
if os.path.exists(self.lock_file):
try:
os.remove(self.lock_file)
except Exception:
pass
def acquire(self):
parent_dir = os.path.dirname(self.lock_file)
os.makedirs(parent_dir, exist_ok=True)
while True:
try:
with open(self.lock_file, "x"):
return
except FileExistsError:
time.sleep(0.1)
def release(self):
try:
os.remove(self.lock_file)
except FileNotFoundError:
pass
class ModelDownloader:
def __init__(
self,
model_name: str,
download_path: str,
file_names: List[str],
download_func: Callable[[str], None],
silent: bool = False,
):
self.model_name = model_name
self.download_path = download_path
self.file_names = file_names
self.download_func = download_func
self.silent = silent
self.requestor = InterProcessRequestor()
self.download_thread = None
self.download_complete = threading.Event()
def ensure_model_files(self):
self.mark_files_state(
self.requestor,
self.model_name,
self.file_names,
ModelStatusTypesEnum.downloading,
)
self.download_thread = threading.Thread(
target=self._download_models,
name=f"_download_model_{self.model_name}",
daemon=True,
)
self.download_thread.start()
def _download_models(self):
for file_name in self.file_names:
path = os.path.join(self.download_path, file_name)
lock = FileLock(path)
if not os.path.exists(path):
lock.acquire()
try:
if not os.path.exists(path):
self.download_func(path)
finally:
lock.release()
self.requestor.send_data(
UPDATE_MODEL_STATE,
{
"model": f"{self.model_name}-{file_name}",
"state": ModelStatusTypesEnum.downloaded,
},
)
self.requestor.stop()
self.download_complete.set()
@staticmethod
def download_from_url(url: str, save_path: str, silent: bool = False) -> Path:
temporary_filename = Path(save_path).with_name(
os.path.basename(save_path) + ".part"
)
temporary_filename.parent.mkdir(parents=True, exist_ok=True)
if not silent:
logger.info(f"Downloading model file from: {url}")
try:
with requests.get(url, stream=True, allow_redirects=True) as r:
r.raise_for_status()
with open(temporary_filename, "wb") as f:
for chunk in r.iter_content(chunk_size=8192):
f.write(chunk)
temporary_filename.rename(save_path)
except Exception as e:
logger.error(f"Error downloading model: {str(e)}")
raise
if not silent:
logger.info(f"Downloading complete: {url}")
return Path(save_path)
@staticmethod
def mark_files_state(
requestor: InterProcessRequestor,
model_name: str,
files: list[str],
state: ModelStatusTypesEnum,
) -> None:
for file_name in files:
requestor.send_data(
UPDATE_MODEL_STATE,
{
"model": f"{model_name}-{file_name}",
"state": state,
},
)
def wait_for_download(self):
self.download_complete.wait()