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Configuration error
Configuration error
| """ | |
| como usar | |
| 1.instalar la libreria deepface | |
| pip install deepface | |
| 2. instanciar el modelo | |
| emo = f_my_emotion.Age_Model() | |
| 3. ingresar una imagen donde solo se vea un rostro (usar modelo deteccion de rostros para extraer una imagen con solo el rostro) | |
| emo.predict_age(face_image) | |
| """ | |
| #from basemodels import VGGFace | |
| from deepface.basemodels import VGGFace | |
| import os | |
| from pathlib import Path | |
| import gdown | |
| import numpy as np | |
| from keras.models import Model, Sequential | |
| from keras.layers import Convolution2D, Flatten, Activation | |
| from keras.preprocessing import image | |
| import cv2 | |
| class Age_Model(): | |
| def __init__(self): | |
| self.model = self.loadModel() | |
| self.output_indexes = np.array([i for i in range(0, 101)]) | |
| def predict_age(self,face_image): | |
| image_preprocesing = self.transform_face_array2age_face(face_image) | |
| age_predictions = self.model.predict(image_preprocesing )[0,:] | |
| result_age = self.findApparentAge(age_predictions) | |
| return result_age | |
| def loadModel(self): | |
| model = VGGFace.baseModel() | |
| #-------------------------- | |
| classes = 101 | |
| base_model_output = Sequential() | |
| base_model_output = Convolution2D(classes, (1, 1), name='predictions')(model.layers[-4].output) | |
| base_model_output = Flatten()(base_model_output) | |
| base_model_output = Activation('softmax')(base_model_output) | |
| #-------------------------- | |
| age_model = Model(inputs=model.input, outputs=base_model_output) | |
| #-------------------------- | |
| #load weights | |
| home = str(Path.home()) | |
| if os.path.isfile(home+'/.deepface/weights/age_model_weights.h5') != True: | |
| print("age_model_weights.h5 will be downloaded...") | |
| url = 'https://drive.google.com/uc?id=1YCox_4kJ-BYeXq27uUbasu--yz28zUMV' | |
| output = home+'/.deepface/weights/age_model_weights.h5' | |
| gdown.download(url, output, quiet=False) | |
| age_model.load_weights(home+'/.deepface/weights/age_model_weights.h5') | |
| return age_model | |
| #-------------------------- | |
| def findApparentAge(self,age_predictions): | |
| apparent_age = np.sum(age_predictions * self.output_indexes) | |
| return apparent_age | |
| def transform_face_array2age_face(self,face_array,grayscale=False,target_size = (224, 224)): | |
| detected_face = face_array | |
| if grayscale == True: | |
| detected_face = cv2.cvtColor(detected_face, cv2.COLOR_BGR2GRAY) | |
| detected_face = cv2.resize(detected_face, target_size) | |
| img_pixels = image.img_to_array(detected_face) | |
| img_pixels = np.expand_dims(img_pixels, axis = 0) | |
| #normalize input in [0, 1] | |
| img_pixels /= 255 | |
| return img_pixels |