Update Dockerfile

Dockerfile

@@ -1,16 +1,15 @@
 # Dockerfile
 
-
 FROM python:3.10-slim
 
 WORKDIR /app
 
-# ── System deps (OpenCV headless needs libGL) ────────────────────
+# ── System deps ──────────────────────────────────────────────────
 RUN apt-get update && apt-get install -y --no-install-recommends \
         libgl1 libglib2.0-0 libgomp1 git \
     && rm -rf /var/lib/apt/lists/*
 
-# ── Python deps ───────────────────────────────────────────────────
+# ── Python deps ──────────────────────────────────────────────────
 COPY requirements.txt .
 RUN pip install --no-cache-dir --compile -r requirements.txt
 
@@ -19,10 +18,8 @@ COPY . .
 
 RUN mkdir -p temp_uploads saved_images && chmod -R 777 temp_uploads saved_images
 
-# ── Pre-download all AI models at BUILD time ─────────────────────
-# This bakes the weights into the Docker image layer.
-# Cold-start on HF Spaces goes from ~3-5 min → ~10 sec.
-# Remove this block if your image size budget is tight (<5 GB limit on free HF).
+# ── Pre-download ALL AI models at BUILD time ─────────────────────
+# Bakes weights into Docker image layer → cold start ~10 sec not 5 min
 RUN python - <<'EOF'
 from transformers import AutoProcessor, AutoModel, AutoImageProcessor
 from ultralytics import YOLO
@@ -37,8 +34,8 @@ print("Pre-downloading DINOv2 …")
 AutoImageProcessor.from_pretrained("facebook/dinov2-base")
 AutoModel.from_pretrained("facebook/dinov2-base")
 
-print("Pre-downloading YOLO …")
-YOLO("yolo11n.pt")
+print("Pre-downloading YOLO (seg model) …")
+YOLO("yolo11n-seg.pt")   # ← FIXED: was yolo11n.pt, now yolo11n-seg.pt
 
 print("Pre-downloading GhostFaceNet + RetinaFace …")
 dummy = np.zeros((112, 112, 3), dtype=np.uint8)
@@ -46,16 +43,16 @@ try:
     DeepFace.represent(img_path=dummy, model_name="GhostFaceNet",
                        detector_backend="retinaface", enforce_detection=False)
 except Exception:
-    pass   # first run just downloads weights; inference error is fine here
+    pass  # first run just downloads weights; inference error is fine
 
 print("✅ All models cached in image layer")
 EOF
 
 EXPOSE 7860
 
-# ── Two uvicorn workers for true parallelism ─────────────────────
-# WEB_CONCURRENCY can be overridden via HF Space env vars
-ENV WEB_CONCURRENCY=2
+# ── Single worker — models are already in memory, no need for 2 ──
+# 2 workers was causing both to re-download yolo11n-seg.pt simultaneously
+ENV WEB_CONCURRENCY=1
 
 CMD uvicorn main:app \
         --host 0.0.0.0 \