| 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 keras.preprocessing import image | |
| from 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() | |