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@@ -1,11 +1,9 @@
-FROM python:3.10-slim
+FROM python:3.10
 
 WORKDIR /app
 
 COPY requirements.txt .
 
-RUN pip uninstall -y opencv-python opencv-contrib-python || true
-
 RUN pip install --no-cache-dir -r requirements.txt
 
 COPY . .

main.py

@@ -1,50 +1,59 @@
-from fastapi import FastAPI, File, UploadFile
-from fastapi.responses import JSONResponse
-import cv2
+from fastapi import FastAPI, UploadFile, File
+from PIL import Image
 import numpy as np
 import mediapipe as mp
-from mediapipe.tasks import python
-from mediapipe.tasks.python import vision
-import tempfile
+import io
 
 app = FastAPI()
 
-# ===== Load Model =====
-MODEL_PATH = "gesture_recognizer.task"
+mp_face = mp.solutions.face_detection
+mp_hands = mp.solutions.hands
 
-base_options = python.BaseOptions(model_asset_path=MODEL_PATH)
-gesture_options = vision.GestureRecognizerOptions(base_options=base_options)
-gesture_recognizer = vision.GestureRecognizer.create_from_options(gesture_options)
+face_detection = mp_face.FaceDetection(
+    min_detection_confidence=0.5
+)
+
+hands_detection = mp_hands.Hands(
+    static_image_mode=True,
+    max_num_hands=2,
+    min_detection_confidence=0.5
+)
 
 
 @app.get("/")
 def home():
-    return {"message": "Gesture + Face API is running"}
+    return {"message": "Correct Photo API Running"}
+
+
+@app.post("/analyze")
+async def analyze(file: UploadFile = File(...)):
+
+    contents = await file.read()
+
+    image = Image.open(io.BytesIO(contents)).convert("RGB")
+
+    image_np = np.array(image)
 
+    results = {
+        "face_detected": False,
+        "hands_detected": False,
+        "status": "INVALID"
+    }
 
-# =========================
-# GESTURE DETECTION API
-# =========================
-@app.post("/gesture")
-async def detect_gesture(file: UploadFile = File(...)):
-    try:
-        contents = await file.read()
-        np_img = np.frombuffer(contents, np.uint8)
-        image = cv2.imdecode(np_img, cv2.IMREAD_COLOR)
+    # Face Detection
+    face_result = face_detection.process(image_np)
 
-        rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-        mp_image = mp.Image(image_format=mp.ImageFormat.SRGB, data=rgb)
+    if face_result.detections:
+        results["face_detected"] = True
 
-        result = gesture_recognizer.recognize(mp_image)
+    # Hands Detection
+    hands_result = hands_detection.process(image_np)
 
-        if result.gestures:
-            top = result.gestures[0][0]
-            return JSONResponse({
-                "gesture": top.category_name,
-                "confidence": float(top.score)
-            })
+    if hands_result.multi_hand_landmarks:
+        results["hands_detected"] = True
 
-        return JSONResponse({"gesture": "none", "confidence": 0})
+    # Final Status
+    if results["face_detected"] and results["hands_detected"]:
+        results["status"] = "CORRECT"
 
-    except Exception as e:
-        return JSONResponse({"error": str(e)}, status_code=500)
+    return results

requirements.txt

@@ -1,6 +1,6 @@
 fastapi
 uvicorn
-opencv-python-headless
-mediapipe==0.10.9
+python-multipart
+mediapipe
 numpy
-python-multipart
+pillow