from fastapi import FastAPI, File, UploadFile, HTTPException, Query
from fastapi.responses import HTMLResponse
from pydantic import BaseModel
from typing import List
import cv2
from PIL import Image
import numpy as np
from io import BytesIO

app = FastAPI()

def buscar_existe(image):
    existe = "NO SE DETECTO SONRISA"
    print("resultado: ", image.shape)

    # Cargar el clasificador de sonrisa
    smile_cascade = cv2.CascadeClassifier('haarcascade_smile.xml') 
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    # Detectar sonrisas
    smiles = smile_cascade.detectMultiScale(
        gray,
        scaleFactor=1.7,
        minNeighbors=22,
        minSize=(25, 25)
    )

    for (x, y, w, h) in smiles:
        existe = "SONRISA DETECTADA"
        break

    return existe

@app.post('/predict/')
async def predict(file: UploadFile = File(...), rostro: str = Query(...)):
    try:
        image = Image.open(BytesIO(await file.read()))
        image = np.asarray(image)
        prediction = buscar_existe(image)
        return {"prediction": prediction}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))