from fastapi import FastAPI, UploadFile, File
from fastapi.responses import JSONResponse
import mediapipe as mp
import numpy as np
from PIL import Image
import io

app = FastAPI()

mp_pose = mp.solutions.pose

pose = mp_pose.Pose(
    static_image_mode=True,
    model_complexity=1,
    enable_segmentation=False
)

@app.post("/analyze_pose")
async def analyze_pose(image: UploadFile = File(...)):
    try:
        data = await image.read()
        pil_image = Image.open(io.BytesIO(data)).convert("RGB")
        np_img = np.array(pil_image)
        
        # MediaPipe는 RGB를 사용하지만, OpenCV 기반 변환이 필요할 수 있어 BGR로 변환
        # (일반적인 MediaPipe 사용 예제에서는 RGB를 넣지만, cv2 함수를 섞어 쓸 때 주의 필요)
        # 작성하신 코드대로라면 BGR로 변환해서 넣고 있습니다.
        bgr = np_img[:, :, ::-1]

        result = pose.process(bgr)

        if not result.pose_landmarks:
            return {"landmarks": None}

        landmarks = []
        for lm in result.pose_landmarks.landmark:
            landmarks.append({
                "x": lm.x,
                "y": lm.y,
                "z": lm.z,
                "visibility": lm.visibility
            })

        return {"landmarks": landmarks}

    except Exception as e:
        return {"error": str(e)}