mirror of
https://github.com/azaion/detections.git
synced 2026-04-22 08:56:32 +00:00
[AZ-175] Media table integration with XxHash64 content hashing and status lifecycle
Made-with: Cursor
This commit is contained in:
Oleksandr Bezdieniezhnykh
+202
-20
@@ -1,11 +1,17 @@
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import asyncio
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import base64
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import io
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import json
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import os
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import tempfile
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import time
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from concurrent.futures import ThreadPoolExecutor
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from pathlib import Path
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from typing import Annotated, Optional
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import av
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import cv2
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import numpy as np
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import requests as http_requests
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from fastapi import Body, FastAPI, UploadFile, File, Form, HTTPException, Request
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from fastapi.responses import StreamingResponse
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@@ -19,6 +25,14 @@ executor = ThreadPoolExecutor(max_workers=2)
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LOADER_URL = os.environ.get("LOADER_URL", "http://loader:8080")
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ANNOTATIONS_URL = os.environ.get("ANNOTATIONS_URL", "http://annotations:8080")
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_MEDIA_STATUS_NEW = 1
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_MEDIA_STATUS_AI_PROCESSING = 2
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_MEDIA_STATUS_AI_PROCESSED = 3
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_MEDIA_STATUS_ERROR = 6
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_VIDEO_EXTENSIONS = frozenset({".mp4", ".mov", ".webm", ".mkv", ".avi", ".m4v"})
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_IMAGE_EXTENSIONS = frozenset({".jpg", ".jpeg", ".png", ".bmp", ".webp", ".tif", ".tiff"})
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loader_client = LoaderHttpClient(LOADER_URL)
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annotations_client = LoaderHttpClient(ANNOTATIONS_URL)
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inference = None
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@@ -214,11 +228,66 @@ def _merged_annotation_settings_payload(raw: object) -> dict:
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return out
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def _build_media_detect_config_dict(
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def _normalize_upload_ext(filename: str) -> str:
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s = Path(filename or "").suffix.lower()
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return s if s else ""
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def _detect_upload_kind(filename: str, data: bytes) -> tuple[str, str]:
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ext = _normalize_upload_ext(filename)
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if ext in _VIDEO_EXTENSIONS:
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return "video", ext
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if ext in _IMAGE_EXTENSIONS:
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return "image", ext
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arr = np.frombuffer(data, dtype=np.uint8)
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if cv2.imdecode(arr, cv2.IMREAD_COLOR) is not None:
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return "image", ext if ext else ".jpg"
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try:
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bio = io.BytesIO(data)
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with av.open(bio):
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pass
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return "video", ext if ext else ".mp4"
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except Exception:
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raise HTTPException(status_code=400, detail="Invalid image or video data")
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def _is_video_media_path(media_path: str) -> bool:
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return Path(media_path).suffix.lower() in _VIDEO_EXTENSIONS
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def _post_media_record(payload: dict, bearer: str) -> bool:
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try:
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headers = {"Authorization": f"Bearer {bearer}"}
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r = http_requests.post(
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f"{ANNOTATIONS_URL}/api/media",
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json=payload,
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headers=headers,
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timeout=30,
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)
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return r.status_code in (200, 201)
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except Exception:
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return False
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def _put_media_status(media_id: str, media_status: int, bearer: str) -> bool:
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try:
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headers = {"Authorization": f"Bearer {bearer}"}
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r = http_requests.put(
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f"{ANNOTATIONS_URL}/api/media/{media_id}/status",
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json={"mediaStatus": media_status},
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headers=headers,
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timeout=30,
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)
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return r.status_code in (200, 204)
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except Exception:
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return False
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def _resolve_media_for_detect(
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media_id: str,
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token_mgr: Optional[TokenManager],
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override: Optional[AIConfigDto],
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) -> dict:
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) -> tuple[dict, str]:
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cfg: dict = {}
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bearer = ""
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if token_mgr:
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@@ -236,8 +305,7 @@ def _build_media_detect_config_dict(
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status_code=503,
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detail="Could not resolve media path from annotations service",
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)
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cfg["paths"] = [media_path]
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return cfg
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return cfg, media_path
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def detection_to_dto(det) -> DetectionDto:
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@@ -279,49 +347,120 @@ def health() -> HealthResponse:
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@app.post("/detect")
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async def detect_image(
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request: Request,
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file: UploadFile = File(...),
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config: Optional[str] = Form(None),
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):
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import cv2
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import numpy as np
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from pathlib import Path
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from media_hash import compute_media_content_hash
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from inference import ai_config_from_dict
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image_bytes = await file.read()
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if not image_bytes:
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raise HTTPException(status_code=400, detail="Image is empty")
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arr = np.frombuffer(image_bytes, dtype=np.uint8)
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if cv2.imdecode(arr, cv2.IMREAD_COLOR) is None:
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raise HTTPException(status_code=400, detail="Invalid image data")
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orig_name = file.filename or "upload"
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kind, ext = _detect_upload_kind(orig_name, image_bytes)
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config_dict = {}
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if config:
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config_dict = json.loads(config)
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media_name = Path(file.filename or "upload.jpg").stem.replace(" ", "")
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auth_header = request.headers.get("authorization", "")
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access_token = auth_header.removeprefix("Bearer ").strip() if auth_header else ""
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refresh_token = request.headers.get("x-refresh-token", "")
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token_mgr = TokenManager(access_token, refresh_token) if access_token else None
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user_id = TokenManager.decode_user_id(access_token) if access_token else None
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videos_dir = os.environ.get(
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"VIDEOS_DIR", os.path.join(os.getcwd(), "data", "videos")
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)
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images_dir = os.environ.get(
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"IMAGES_DIR", os.path.join(os.getcwd(), "data", "images")
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)
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storage_path = None
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content_hash = None
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if token_mgr and user_id:
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content_hash = compute_media_content_hash(image_bytes)
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base = videos_dir if kind == "video" else images_dir
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os.makedirs(base, exist_ok=True)
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if not ext.startswith("."):
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ext = "." + ext
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storage_path = os.path.abspath(os.path.join(base, f"{content_hash}{ext}"))
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with open(storage_path, "wb") as out:
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out.write(image_bytes)
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mt = "Video" if kind == "video" else "Image"
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payload = {
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"id": content_hash,
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"name": Path(orig_name).name,
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"path": storage_path,
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"mediaType": mt,
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"mediaStatus": _MEDIA_STATUS_NEW,
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"userId": user_id,
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}
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bearer = token_mgr.get_valid_token()
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_post_media_record(payload, bearer)
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_put_media_status(content_hash, _MEDIA_STATUS_AI_PROCESSING, bearer)
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media_name = Path(orig_name).stem.replace(" ", "")
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loop = asyncio.get_event_loop()
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inf = get_inference()
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results = []
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tmp_video_path = None
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def on_annotation(annotation, percent):
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results.extend(annotation.detections)
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ai_cfg = ai_config_from_dict(config_dict)
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def run_img():
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inf.run_detect_image(image_bytes, ai_cfg, media_name, on_annotation)
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def run_upload():
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nonlocal tmp_video_path
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if kind == "video":
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if storage_path:
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save = storage_path
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else:
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suf = ext if ext.startswith(".") else ".mp4"
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fd, tmp_video_path = tempfile.mkstemp(suffix=suf)
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os.close(fd)
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with open(tmp_video_path, "wb") as f:
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f.write(image_bytes)
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save = tmp_video_path
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inf.run_detect_video(image_bytes, ai_cfg, media_name, save, on_annotation)
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else:
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inf.run_detect_image(image_bytes, ai_cfg, media_name, on_annotation)
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try:
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await loop.run_in_executor(executor, run_img)
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await loop.run_in_executor(executor, run_upload)
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if token_mgr and user_id and content_hash:
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_put_media_status(
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content_hash, _MEDIA_STATUS_AI_PROCESSED, token_mgr.get_valid_token()
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)
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return [detection_to_dto(d) for d in results]
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except RuntimeError as e:
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if token_mgr and user_id and content_hash:
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_put_media_status(
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content_hash, _MEDIA_STATUS_ERROR, token_mgr.get_valid_token()
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)
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if "not available" in str(e):
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raise HTTPException(status_code=503, detail=str(e))
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raise HTTPException(status_code=422, detail=str(e))
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except ValueError as e:
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if token_mgr and user_id and content_hash:
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_put_media_status(
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content_hash, _MEDIA_STATUS_ERROR, token_mgr.get_valid_token()
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)
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raise HTTPException(status_code=400, detail=str(e))
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except Exception:
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if token_mgr and user_id and content_hash:
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_put_media_status(
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content_hash, _MEDIA_STATUS_ERROR, token_mgr.get_valid_token()
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)
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raise
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finally:
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if tmp_video_path and os.path.isfile(tmp_video_path):
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try:
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os.unlink(tmp_video_path)
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except OSError:
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pass
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def _post_annotation_to_service(token_mgr: TokenManager, media_id: str,
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@@ -362,7 +501,7 @@ async def detect_media(
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refresh_token = request.headers.get("x-refresh-token", "")
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token_mgr = TokenManager(access_token, refresh_token) if access_token else None
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config_dict = _build_media_detect_config_dict(media_id, token_mgr, config)
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config_dict, media_path = _resolve_media_for_detect(media_id, token_mgr, config)
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async def run_detection():
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loop = asyncio.get_event_loop()
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@@ -375,6 +514,22 @@ async def detect_media(
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pass
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try:
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from inference import ai_config_from_dict
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if token_mgr:
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_put_media_status(
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media_id,
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_MEDIA_STATUS_AI_PROCESSING,
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token_mgr.get_valid_token(),
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)
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with open(media_path, "rb") as mf:
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file_bytes = mf.read()
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video = _is_video_media_path(media_path)
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stem_name = Path(media_path).stem.replace(" ", "")
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ai_cfg = ai_config_from_dict(config_dict)
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inf = get_inference()
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if not inf.is_engine_ready:
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raise RuntimeError("Detection service unavailable")
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@@ -391,7 +546,7 @@ async def detect_media(
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if token_mgr and dtos:
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_post_annotation_to_service(token_mgr, media_id, annotation, dtos)
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def on_status(media_name, count):
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def on_status(media_name_cb, count):
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event = DetectionEvent(
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annotations=[],
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mediaId=media_id,
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@@ -399,11 +554,38 @@ async def detect_media(
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mediaPercent=100,
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)
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loop.call_soon_threadsafe(_enqueue, event)
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if token_mgr:
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_put_media_status(
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media_id,
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_MEDIA_STATUS_AI_PROCESSED,
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token_mgr.get_valid_token(),
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)
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await loop.run_in_executor(
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executor, inf.run_detect, config_dict, on_annotation, on_status
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)
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def run_sync():
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if video:
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inf.run_detect_video(
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file_bytes,
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ai_cfg,
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stem_name,
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media_path,
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on_annotation,
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on_status,
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)
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else:
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inf.run_detect_image(
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file_bytes,
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ai_cfg,
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stem_name,
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on_annotation,
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on_status,
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)
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await loop.run_in_executor(executor, run_sync)
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except Exception:
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if token_mgr:
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_put_media_status(
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media_id, _MEDIA_STATUS_ERROR, token_mgr.get_valid_token()
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)
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error_event = DetectionEvent(
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annotations=[],
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mediaId=media_id,
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