Update app.py

app.py

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+from fastapi import FastAPI, UploadFile, File, HTTPException
+from fastapi.responses import JSONResponse
+from ultralytics import YOLO
+import cv2
+import numpy as np
+from shapely.geometry import box as shapely_box, Polygon
+from shapely.ops import unary_union
+import mediapipe as mp
+from collections import defaultdict
+
+app = FastAPI(title="Face Skin Percentage API")
+
+# -------------------- LOAD MODELS --------------------
+skin_model_path = "pores.pt"  # Your YOLO model path
+skin_model = YOLO(skin_model_path)
+mp_face_mesh = mp.solutions.face_mesh.FaceMesh(static_image_mode=True)
+
+# -------------------- HOME ROUTE --------------------
+@app.get("/")
+def home():
+    return {"message": "✅ Skin API is running", 
+            "usage": "POST an image (form-data key 'file') to /analyze"}
+
+# -------------------- ANALYZE ROUTE --------------------
+@app.post("/analyze")
+async def analyze(file: UploadFile = File(...)):
+    if not file:
+        raise HTTPException(status_code=400, detail="No file uploaded")
+
+    # Read image bytes and convert to OpenCV image
+    contents = await file.read()
+    np_arr = np.frombuffer(contents, np.uint8)
+    img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
+    if img is None:
+        raise HTTPException(status_code=400, detail="Invalid image file")
+
+    img_h, img_w = img.shape[:2]
+
+    # -------------------- STEP 1: Detect face --------------------
+    rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    result = mp_face_mesh.process(rgb_img)
+
+    face_area = 0
+    face_polygon = None
+    if result.multi_face_landmarks:
+        for facial_landmarks in result.multi_face_landmarks:
+            points = [[int(lm.x * img_w), int(lm.y * img_h)] for lm in facial_landmarks.landmark]
+            hull = cv2.convexHull(np.array(points, dtype=np.int32))
+            face_area = cv2.contourArea(hull)
+            face_polygon = Polygon(hull.reshape(-1, 2))
+            break  # only first face
+    else:
+        return JSONResponse({"success": False, "message": "No face detected", "percentages": {}})
+
+    # -------------------- STEP 2: Run YOLO skin detection --------------------
+    skin_results = skin_model(img)
+    boxes_xy = skin_results[0].boxes.xyxy.cpu().numpy()
+    boxes_cls = skin_results[0].boxes.cls.cpu().numpy().astype(int)
+
+    class_polygons = defaultdict(list)
+    for xy, cls_id in zip(boxes_xy, boxes_cls):
+        x1, y1, x2, y2 = xy.astype(int)
+        det_poly = shapely_box(x1, y1, x2, y2)
+        if face_polygon.intersects(det_poly):
+            intersection = det_poly.intersection(face_polygon)
+            if intersection.area > 0:
+                class_polygons[cls_id].append(intersection)
+
+    # -------------------- STEP 3: Calculate percentages --------------------
+    skin_percentages = {}
+    for cls_id, class_name in skin_model.names.items():
+        polys = class_polygons.get(cls_id, [])
+        if polys:
+            union_poly = unary_union(polys)
+            percentage = (union_poly.area / face_area) * 100 if face_area > 0 else 0.0
+        else:
+            percentage = 0.0
+        skin_percentages[class_name] = round(percentage, 2)
+
+    return {"success": True, "percentages": skin_percentages}