| import gradio as gr |
| import pandas as pd |
| import numpy as np |
| import os |
| from tqdm import tqdm |
| import tensorflow as tf |
| from tensorflow import keras |
| from keras.utils import np_utils |
| from tensorflow.keras.preprocessing import image |
| from tensorflow.keras.preprocessing.image import ImageDataGenerator |
| import matplotlib.pyplot as plt |
|
|
| new_model = tf.keras.models.load_model('modelo_entrenado.h5') |
| objects = ('angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral') |
| y_pos = np.arange(len(objects)) |
|
|
|
|
| def predict_image(pic): |
| img = image.load_img(pic, grayscale=True, target_size=(48, 48)) |
| x = image.img_to_array(img) |
| |
| x = np.expand_dims(x, axis = 0) |
| |
| x /= 255 |
|
|
|
|
| custom = new_model.predict(x) |
|
|
| m=0.000000000000000000001 |
| a=custom[0] |
| for i in range(0,len(a)): |
| if a[i]>m: |
| m=a[i] |
| ind=i |
| |
| return ('Expression Prediction:',objects[ind]) |
| |
| iface = gr.Interface( |
| predict_image, |
| [ |
| |
| gr.inputs.Image(source="upload",type="filepath", label="Imagen") |
| ], |
|
|
| "text", |
| |
| |
| interpretation="default", |
| title = 'FER - Facial Expression Recognition', |
| description = 'Probablemente nos daremos cuenta de que muchas veces se miente cuando se tratan las emociones, ¿pero nuestra cara también miente? https://saturdays.ai/2022/03/16/detectando-emociones-mediante-imagenes-con-inteligencia-artificial/ ', |
| examples=[["28860.png"], ["28790.png"], ["28953.png"], ["30369.png"], ["28722.png"], ["29026.png"], ["28857.png"], ["28795.png"], ["28880.png"], ["28735.png"], ["28757.png"], ["28727.png"], ["28874.png"], ["28723.png"]], |
| theme = 'grass' |
| ) |
|
|
|
|
| |
| iface.launch() |
|
|
