Add MP4 upload endpoint for testing pipeline without live camera
POST /upload saves the file, runs full processing (transcode, frame extraction, LPR, color detection) and redirects to the resulting event page. UI: "Tester un clip" button in header reveals a file picker form. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
perco
co-authored by
Claude Sonnet 4.6
Claude Sonnet 4.6
parent
5594010d78
commit
ec214ed7b2
+23
-2
@@ -2,9 +2,11 @@ import os
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import glob
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import logging
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import threading
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import tempfile
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import asyncio
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from contextlib import asynccontextmanager
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from fastapi import FastAPI, Request, Query, HTTPException
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from fastapi.responses import HTMLResponse
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from fastapi import FastAPI, Request, Query, HTTPException, UploadFile, File
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from fastapi.responses import HTMLResponse, RedirectResponse
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from fastapi.staticfiles import StaticFiles
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from fastapi.templating import Jinja2Templates
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from datetime import datetime
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@@ -134,6 +136,25 @@ async def api_events(
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return {"events": events, "total": total}
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@app.post("/upload")
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async def upload_clip(file: UploadFile = File(...)):
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if not file.filename.lower().endswith(".mp4"):
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raise HTTPException(status_code=400, detail="Seuls les fichiers .mp4 sont acceptés")
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with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmp:
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content = await file.read()
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tmp.write(content)
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tmp_path = tmp.name
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try:
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loop = asyncio.get_event_loop()
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event_id = await loop.run_in_executor(None, watcher.process_uploaded_clip, tmp_path)
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finally:
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os.unlink(tmp_path)
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return RedirectResponse(f"/event/{event_id}", status_code=303)
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@app.get("/health")
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async def health():
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return {"status": "ok"}
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@@ -16,6 +16,11 @@
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.btn:hover { background: #1d4ed8; }
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.btn-ghost { background: #1e293b; border: 1px solid #475569; color: #94a3b8; }
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.btn-ghost:hover { background: #334155; color: #e2e8f0; }
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.btn-upload { background: #1e293b; border: 1px solid #475569; color: #94a3b8; border-radius: 6px; padding: 6px 14px; font-size: 0.85rem; cursor: pointer; }
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.btn-upload:hover { background: #334155; color: #e2e8f0; }
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#upload-panel { display:none; background:#1e293b; border:1px solid #334155; border-radius:10px; padding:16px; margin-bottom:16px; }
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#upload-panel.open { display:block; }
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#upload-progress { display:none; }
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</style>
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</head>
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<body class="min-h-screen">
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@@ -26,11 +31,30 @@
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<span class="font-bold text-lg">CamWatch</span>
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<span class="text-slate-500 text-sm hidden sm:inline">— Passages véhicules</span>
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</div>
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<span class="text-slate-400 text-sm">{{ total }} passage{{ 's' if total != 1 else '' }}</span>
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<div class="flex items-center gap-2">
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<span class="text-slate-400 text-sm">{{ total }} passage{{ 's' if total != 1 else '' }}</span>
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<button class="btn-upload" onclick="document.getElementById('upload-panel').classList.toggle('open')">⬆ Tester un clip</button>
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</div>
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</header>
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<main class="max-w-5xl mx-auto px-3 py-4">
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<!-- Upload panel -->
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<div id="upload-panel">
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<p class="text-slate-300 text-sm font-medium mb-3">Tester un clip .mp4 — il sera traité comme un vrai passage (LPR + couleur + frames)</p>
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<form id="upload-form" action="/upload" method="post" enctype="multipart/form-data"
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onsubmit="startUpload(event)">
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<div class="flex items-center gap-3 flex-wrap">
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<input type="file" name="file" accept=".mp4,video/mp4" required
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class="text-sm text-slate-300 file:mr-3 file:py-1.5 file:px-4 file:rounded file:border-0 file:text-sm file:bg-slate-700 file:text-slate-200 hover:file:bg-slate-600 cursor-pointer">
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<button type="submit" class="btn text-sm">Analyser</button>
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</div>
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</form>
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<div id="upload-progress" class="mt-3 text-sm text-slate-400">
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⏳ Traitement en cours (extraction frames + LPR)… merci de patienter ~60s
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</div>
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</div>
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<!-- Filters -->
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<form method="get" class="flex flex-wrap gap-2 mb-5">
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<input type="text" name="plate" placeholder="Plaque…" value="{{ filter_plate }}" class="w-32">
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@@ -98,6 +122,13 @@
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</main>
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<script>setTimeout(() => location.reload(), 60000);</script>
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<script>
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setTimeout(() => location.reload(), 60000);
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function startUpload(e) {
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document.getElementById('upload-form').querySelector('button[type=submit]').disabled = true;
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document.getElementById('upload-progress').style.display = 'block';
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}
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</script>
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</body>
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</html>
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+60
-41
@@ -86,15 +86,13 @@ def _vehicle_color(frame: np.ndarray, plate_bbox: tuple | None) -> tuple[str, st
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px1, py1, px2, py2 = plate_bbox
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pw = px2 - px1
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ph = py2 - py1
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# Vehicle body: above plate, same horizontal span expanded ×3
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crop_x1 = max(0, px1 - pw * 2)
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crop_x2 = min(w, px2 + pw * 2)
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crop_y2 = max(0, py1 - 5)
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crop_y1 = max(0, py1 - ph * 10) # 10× plate height above plate
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crop_y1 = max(0, py1 - ph * 10)
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if crop_y2 > crop_y1 and crop_x2 > crop_x1:
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crop = frame[int(crop_y1):int(crop_y2), int(crop_x1):int(crop_x2)]
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return extract_dominant_color_from_frame(crop)
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# Fallback: center 50% of image (excludes sky at top, road at bottom)
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cy1 = h // 4
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cy2 = 3 * h // 4
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cx1 = w // 4
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@@ -110,58 +108,43 @@ def _frame_score(frame: np.ndarray, plates: list) -> float:
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return cv2.Laplacian(gray, cv2.CV_64F).var() * 0.001
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def _process_event():
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event_id = str(uuid.uuid4())
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event_dir = os.path.join(EVENTS_DIR, event_id)
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os.makedirs(event_dir, exist_ok=True)
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def _process_clip(event_id: str, event_dir: str, clip_path: str, camera_name: str = None):
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"""Process an existing clip: transcode, extract frames, LPR, store in DB."""
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if camera_name is None:
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camera_name = CAMERA_NAME
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url = _rtsp_url()
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clip_path = os.path.join(event_dir, "clip.mp4")
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frames_pattern = os.path.join(event_dir, "frame_%04d.jpg")
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log.info(f"Capturing {CAPTURE_DURATION}s at {CAPTURE_FPS}fps — event {event_id[:8]}")
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# Step 1: capture clip
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ret = subprocess.run([
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"ffmpeg", "-y", "-rtsp_transport", "tcp",
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"-i", url, "-t", str(CAPTURE_DURATION), "-c", "copy", clip_path,
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], capture_output=True, timeout=CAPTURE_DURATION + 10)
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if not os.path.exists(clip_path) or os.path.getsize(clip_path) < 1000:
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log.error(f"ffmpeg capture failed: {ret.stderr[-200:].decode(errors='ignore')}")
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shutil.rmtree(event_dir, ignore_errors=True)
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return
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# Step 2: extract all frames
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subprocess.run([
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"ffmpeg", "-y", "-i", clip_path,
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"-vf", f"fps={CAPTURE_FPS}", "-q:v", "2", frames_pattern,
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], capture_output=True, timeout=30)
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# Step 2b: transcode to H.264 baseline for browser compatibility
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# Transcode to H.264 baseline for browser compatibility
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web_clip = os.path.join(event_dir, "clip_web.mp4")
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subprocess.run([
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"ffmpeg", "-y", "-i", clip_path,
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"-c:v", "libx264", "-profile:v", "baseline", "-level", "3.1",
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"-preset", "fast", "-crf", "28",
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"-vf", "scale=-2:720", # downsample to 720p — enough for review
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"-an", # no audio needed for surveillance
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"-movflags", "+faststart", # moov atom at front for streaming
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"-vf", "scale=-2:720",
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"-an",
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"-movflags", "+faststart",
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web_clip,
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], capture_output=True, timeout=60)
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], capture_output=True, timeout=120)
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if os.path.exists(web_clip):
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os.replace(web_clip, clip_path)
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else:
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log.warning("Transcode failed, keeping raw clip")
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# Extract frames
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subprocess.run([
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"ffmpeg", "-y", "-i", clip_path,
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"-vf", f"fps={CAPTURE_FPS}", "-q:v", "2", frames_pattern,
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], capture_output=True, timeout=60)
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frame_files = sorted(glob.glob(os.path.join(event_dir, "frame_*.jpg")))
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log.info(f"Extracted {len(frame_files)} frames")
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if not frame_files:
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shutil.rmtree(event_dir, ignore_errors=True)
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return
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return None
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# Step 3: score ALL frames, rename sorted (best = frame_0001)
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# Score ALL frames, rename sorted (best = frame_0001)
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scored: list[tuple[float, np.ndarray, str]] = []
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for path in frame_files:
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frame = cv2.imread(path)
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@@ -173,7 +156,6 @@ def _process_event():
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scored.sort(key=lambda x: -x[0])
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# Rename to sorted order (temp names to avoid collisions)
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for i, (_, _, old_path) in enumerate(scored):
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os.rename(old_path, old_path + ".tmp")
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for i, (_, _, old_path) in enumerate(scored):
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@@ -182,28 +164,65 @@ def _process_event():
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best_frame = scored[0][1] if scored else None
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if best_frame is None:
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shutil.rmtree(event_dir, ignore_errors=True)
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return
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return None
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# Step 4: run LPR on best frame
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# LPR on best frame
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plate, conf, plate_bbox = ("", 0.0, None)
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if _analyzer:
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plate, conf, plate_bbox = _analyzer.read_plate(best_frame)
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log.info(f"LPR: plate={plate!r} conf={conf:.2f} bbox={plate_bbox}")
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# Step 5: save thumbnail (best frame)
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# Save thumbnail
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snapshot_file = f"{event_id}.jpg"
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snapshot_path = os.path.join(SNAPSHOTS_DIR, snapshot_file)
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cv2.imwrite(snapshot_path, best_frame, [cv2.IMWRITE_JPEG_QUALITY, 90])
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# Color: crop vehicle body above plate (avoids sky/road)
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hex_color, color_name = _vehicle_color(best_frame, plate_bbox)
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insert_event(
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event_id, CAMERA_NAME, int(time.time()),
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event_id, camera_name, int(time.time()),
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f"snapshots/{snapshot_file}",
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f"events/{event_id}/clip.mp4",
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plate or None, hex_color, color_name,
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)
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log.info(f"Stored: {event_id[:8]} | plate={plate} | color={color_name} | frames={len(frame_files)}")
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return event_id
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def _process_event():
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event_id = str(uuid.uuid4())
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event_dir = os.path.join(EVENTS_DIR, event_id)
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os.makedirs(event_dir, exist_ok=True)
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url = _rtsp_url()
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clip_path = os.path.join(event_dir, "clip.mp4")
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log.info(f"Capturing {CAPTURE_DURATION}s at {CAPTURE_FPS}fps — event {event_id[:8]}")
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ret = subprocess.run([
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"ffmpeg", "-y", "-rtsp_transport", "tcp",
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"-i", url, "-t", str(CAPTURE_DURATION), "-c", "copy", clip_path,
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], capture_output=True, timeout=CAPTURE_DURATION + 10)
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if not os.path.exists(clip_path) or os.path.getsize(clip_path) < 1000:
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log.error(f"ffmpeg capture failed: {ret.stderr[-200:].decode(errors='ignore')}")
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shutil.rmtree(event_dir, ignore_errors=True)
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return
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_process_clip(event_id, event_dir, clip_path)
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def process_uploaded_clip(src_path: str) -> str:
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"""Create a new event from an uploaded MP4. Returns event_id."""
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event_id = str(uuid.uuid4())
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event_dir = os.path.join(EVENTS_DIR, event_id)
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os.makedirs(event_dir, exist_ok=True)
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clip_path = os.path.join(event_dir, "clip.mp4")
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shutil.copy2(src_path, clip_path)
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log.info(f"Processing uploaded clip — event {event_id[:8]}")
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result = _process_clip(event_id, event_dir, clip_path, camera_name="upload")
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if result is None:
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raise RuntimeError("Processing failed: no frames extracted")
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return event_id
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def run_watcher():
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