| 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(hombre_rostro.jpg)): |
| 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)) |
|
|
