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| from fastapi import FastAPI, File, UploadFile, HTTPException | |
| from fastapi.responses import HTMLResponse | |
| from pydantic import BaseModel | |
| from typing import List | |
| import cv2 | |
| import numpy as np | |
| app = FastAPI() | |
| def buscar_existe(image): | |
| existe = "no" | |
| face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') | |
| gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
| faces = face_cascade.detectMultiScale(gray, 1.3,5,minSize=(30, 30)) | |
| for (x,y,w,h) in faces: | |
| existe = "si" | |
| break | |
| return existe | |
| # Ruta para la p谩gina principal con formulario HTML | |
| async def main(): | |
| content = """ | |
| <html> | |
| <head> | |
| <title>RECONOCIMIENTO FACIAL</title> | |
| <style> | |
| body { | |
| font-family: Arial, sans-serif; | |
| display: flex; | |
| justify-content: center; | |
| align-items: center; | |
| height: 100vh; | |
| margin: 0; | |
| background-image: url('Background.png'); /* Reemplaza con la ruta de tu imagen */ | |
| background-size: cover; /* Ajusta el tama帽o para cubrir todo el cuerpo */ | |
| background-position: center; /* Centra la imagen en el cuerpo */ | |
| background-repeat: no-repeat; /* Evita que la imagen se repita */ | |
| } | |
| .container { | |
| position: relative; | |
| padding: 20px; | |
| border-radius: 10px; | |
| box-shadow: 0px 0px 10px rgba(247, 15, 15, 0.808); | |
| text-align: center; | |
| } | |
| .overlay{ | |
| position: absolute; | |
| top: 0; | |
| left: 0; | |
| width: 100%; | |
| height: 100%; | |
| background-color: rgba(0, 0, 0, 0); /* Capa de opacidad */ | |
| border-radius: 10px; | |
| } | |
| .content { | |
| position: relative; | |
| z-index: 1; | |
| } | |
| .content h1 { | |
| margin-bottom: 20px; | |
| } | |
| .custom-file-input { | |
| display: none; | |
| } | |
| .file-label { | |
| background-color: #007bff; | |
| color: white; | |
| padding: 10px 20px; | |
| border-radius: 5px; | |
| cursor: pointer; | |
| display: inline-block; | |
| margin-top: 20px; | |
| margin-bottom: 20px; | |
| } | |
| .file-label:hover { | |
| background-color: #000000; | |
| } | |
| .custom-button { | |
| background-color: #2cb1ff; | |
| color: white; | |
| border: none; | |
| padding: 10px 20px; | |
| margin-top: 20px; | |
| border-radius: 5px; | |
| cursor: pointer; | |
| display: inline-block; | |
| } | |
| .custom-button:hover { | |
| background-color: #01050a; | |
| } | |
| .container img { | |
| margin: 20px auto; | |
| max-width: 100%; | |
| max-height: 300px; | |
| border-radius: 10px; | |
| display: none; | |
| } | |
| </style> | |
| </head> | |
| <body style="background-image: url('Background.png'); background-size: cover; background-position: center; background-repeat: no-repeat;"> | |
| <div class="container"> | |
| <div class="overlay"></div> | |
| <div class="content"> | |
| <h1>RECONOCIMIENTO FACIAL</h1> | |
| <form action="/predict" method="post" enctype="multipart/form-data" onsubmit="mostrarResultado(event)"> | |
| <label for="file-input" class="file-label">Seleccionar archivo</label> | |
| <input id="file-input" class="custom-file-input" name="file" type="file" accept="image/*" onchange="mostrarImagen(event)"> | |
| <img id="imagenSeleccionada"> | |
| <button type="submit" class="custom-button">Subir Imagen</button> | |
| </form> | |
| </div> | |
| </div> | |
| <script> | |
| function mostrarImagen(event) { | |
| const archivo = event.target.files[0]; | |
| if (archivo) { | |
| const lector = new FileReader(); | |
| lector.onload = function(e) { | |
| const imagen = document.getElementById('imagenSeleccionada'); | |
| imagen.src = e.target.result; | |
| imagen.style.display = 'block'; | |
| } | |
| lector.readAsDataURL(archivo); | |
| } | |
| } | |
| // Funci贸n para mostrar el resultado como un alert | |
| async function mostrarResultado(event) { | |
| event.preventDefault(); // Evitar que el formulario se env铆e autom谩ticamente | |
| event.preventDefault(); // Evitar que el formulario se env铆e autom谩ticamente | |
| try { | |
| const formData = new FormData(event.target); | |
| const response = await fetch('/predict', { | |
| method: 'POST', | |
| body: formData | |
| }); | |
| if (!response.ok) { | |
| throw new Error('HTTP error! Status: ${response.status}'); | |
| } | |
| const data = await response.json(); | |
| alert('Rostro detectado : ${data.emotion}'); | |
| } catch (error) { | |
| console.error('Error al procesar la solicitud:', error); | |
| alert('Ocurri贸 un error al procesar la solicitud.'); | |
| } | |
| } | |
| </script> | |
| </body> | |
| </html> | |
| """ | |
| return HTMLResponse(content) | |
| # Ruta de predicci贸n | |
| async def predict(file: UploadFile = File(...)): | |
| try: | |
| # Verificar si es una imagen v谩lida | |
| if not file.content_type.startswith('image/'): | |
| raise HTTPException(status_code=400, detail="El archivo debe ser una imagen.") | |
| # Convertir la imagen a formato adecuado | |
| image = cv2.imdecode(np.frombuffer(await file.read(), np.uint8), cv2.IMREAD_COLOR) | |
| # Realizar el reconocimiento de emociones en la imagen | |
| emotion = buscar_existe(image) | |
| #print(emotion) | |
| # Devolver la emoci贸n detectada como respuesta en formato JSON | |
| return {'emotion': emotion} | |
| except HTTPException as he: | |
| raise he | |
| except Exception as e: | |
| print(f"Error general: {str(e)}") | |
| raise HTTPException(status_code=500, detail="Error durante la predicci贸n de emociones.") | |
| # Punto de entrada principal para la aplicaci贸n | |
| if __name__ == '__main__': | |
| # Ejecutar la aplicaci贸n FastAPI utilizando Uvicorn | |
| import uvicorn | |
| uvicorn.run(app, host='0.0.0.0', port=8000) | |