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from fastapi import FastAPI, File, UploadFile, HTTPException
import cv2
import numpy as np
from PIL import Image
import io
import base64
app = FastAPI()
@app.post("/detect/")
async def detect_face(file: UploadFile = File(...)):
try:
image_bytes = await file.read()
image = Image.open(io.BytesIO(image_bytes))
img_np = np.array(image)
if img_np.shape[2] == 4:
img_np = cv2.cvtColor(img_np, cv2.COLOR_BGRA2BGR)
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
gray = cv2.cvtColor(img_np, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
if len(faces) == 0:
raise HTTPException(status_code=404, detail="No se detectaron rostros en la imagen.")
for (x, y, w, h) in faces:
cv2.rectangle(img_np, (x, y), (x+w, y+h), (255, 0, 0), 2)
result_image = Image.fromarray(cv2.cvtColor(img_np, cv2.COLOR_BGR2RGB))
img_byte_arr = io.BytesIO()
result_image.save(img_byte_arr, format='JPEG')
img_byte_arr = img_byte_arr.getvalue()
return {
"message": "Rostros detectados",
"rostros": len(faces),
"imagen_base64": base64.b64encode(img_byte_arr).decode('utf-8')
}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
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