Update app.py

app.py

@@ -27,12 +27,6 @@ async def process_img(file: UploadFile = File(...)):
     try:
         img_bytes = await file.read()
         img = Image.open(io.BytesIO(img_bytes)).convert("RGB")
-
-        # Resize large images
-        max_dim = 1500
-        if max(img.size) > max_dim:
-            img.thumbnail((max_dim, max_dim))
-
         np_img = np.array(img)
 
         faces = face_app.get(np_img)
@@ -41,29 +35,71 @@ async def process_img(file: UploadFile = File(...)):
 
         face = faces[0]
 
-        # ---- FIX: use crop instead of face.normed ----
-        x1, y1, x2, y2 = face.bbox.astype(int)
-        cropped = img.crop((x1, y1, x2, y2))
-
-        # Basic alignment (centered crop)
-        aligned = cropped.resize((400, 500))
-
-        # Remove background safely
-        no_bg = remove(aligned)
-
-        # White background
-        white = Image.new("RGB", no_bg.size, (255, 255, 255))
-        white.paste(no_bg, mask=no_bg.split()[3])
-
-        # Resize to 4×6 cm output
-        final_img = resize_to_4x6(white)
+        # =============================
+        # 1. Extract main landmarks
+        # =============================
+        pts = face.landmark_2d_106
+        
+        left_eye = pts[38]
+        right_eye = pts[88]
+        nose = pts[52]
+
+        # =============================
+        # 2. Compute roll angle
+        # =============================
+        dx = right_eye[0] - left_eye[0]
+        dy = right_eye[1] - left_eye[1]
+        roll_angle = np.degrees(np.arctan2(dy, dx))
+
+        # =============================
+        # 3. Rotate image to fix roll
+        # =============================
+        rotated = img.rotate(-roll_angle, expand=True)
+        np_rot = np.array(rotated)
+
+        # =============================
+        # 4. Detect again after rotation
+        # =============================
+        faces2 = face_app.get(np_rot)
+        if not faces2:
+            return JSONResponse({"error": "Face lost after rotation"}, status_code=500)
+
+        f = faces2[0]
+        x1, y1, x2, y2 = f.bbox.astype(int)
+
+        # =============================
+        # 5. Resize face to Abshir ratio
+        # Face height should be 70% of image
+        # =============================
+        face_h = y2 - y1
+        target_face_ratio = 0.70
+        target_h = int(face_h / target_face_ratio)
+
+        center_y = (y1 + y2) // 2
+        top = center_y - target_h // 2
+        bottom = center_y + target_h // 2
+
+        top = max(0, top)
+        bottom = min(rotated.height, bottom)
+
+        crop_img = rotated.crop((0, top, rotated.width, bottom))
+
+        # =============================
+        # 6. Apply white background
+        # =============================
+        white_bg = Image.new("RGB", crop_img.size, (255, 255, 255))
+        white_bg.paste(crop_img, (0, 0))
+
+        # =============================
+        # 7. Final export 4x6
+        # =============================
+        final_img = white_bg.resize((472, 709), Image.LANCZOS)
 
         buf = io.BytesIO()
         final_img.save(buf, format="JPEG")
         buf.seek(0)
-
         return Response(buf.getvalue(), media_type="image/jpeg")
 
     except Exception as e:
-        print("PROCESS ERROR:", e)
+        print("ERROR:", e)
         return JSONResponse({"error": str(e)}, status_code=500)