Add Gradio UI at /ui for testing

Dockerfile

@@ -5,7 +5,7 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
     libsm6 libxext6 libxrender1 \
     && rm -rf /var/lib/apt/lists/*
 
-RUN pip install --no-cache-dir fastapi uvicorn mediapipe pillow supervision
+RUN pip install --no-cache-dir fastapi uvicorn mediapipe pillow supervision gradio
 
 RUN useradd -m -u 1000 user
 USER user
@@ -21,5 +21,4 @@ ENV MEDIAPIPE_MODEL_PATH=/home/user/app/models/hand_landmarker.task
 
 EXPOSE 7860
 
-# Force rebuild v2
 CMD ["uvicorn", "inference_server:app", "--host", "0.0.0.0", "--port", "7860"]

inference_server.py

@@ -12,6 +12,7 @@ from PIL import Image as _PILImage, ImageDraw as _PILDraw, ImageFont as _PILFont
 import mediapipe as mp
 from mediapipe.tasks import python as _mp_python
 from mediapipe.tasks.python import vision as _mp_vision
+import gradio as gr
 
 WEIGHTS_PATH = os.getenv(
     "WEIGHTS_PATH",
@@ -674,3 +675,31 @@ def root():
 @app.get("/health")
 def health():
     return {"status": "ok"}
+
+
+# ── Gradio UI ──────────────────────────────────────────────────────────────────
+def gradio_annotate(image: np.ndarray, confidence: float) -> np.ndarray:
+    """Gradio wrapper for annotate function."""
+    if image is None:
+        return None
+    # Convert RGB (Gradio) to BGR (OpenCV)
+    image_bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    result = annotate(image_bgr, conf=confidence)
+    # Convert back to RGB for Gradio
+    return cv2.cvtColor(result, cv2.COLOR_BGR2RGB)
+
+
+demo = gr.Interface(
+    fn=gradio_annotate,
+    inputs=[
+        gr.Image(label="Ảnh bàn tay", type="numpy"),
+        gr.Slider(0.1, 1.0, value=0.4, step=0.05, label="Confidence")
+    ],
+    outputs=gr.Image(label="Kết quả phân tích"),
+    title="🖐 Menhso - Phân tích đường chỉ tay",
+    description="Upload ảnh bàn tay để phát hiện các đường chỉ tay (head, life, love) và landmarks.",
+    examples=[],
+    allow_flagging="never"
+)
+
+app = gr.mount_gradio_app(app, demo, path="/ui")