def network_predict(image):
image_to_predict = prepare_image(image)
with graph.as_default():
prediction = network_model.predict(image_to_predict)
label = decode_predictions(prediction)
return label
def decode_predictions(*args, **kwargs):
return vgg16.decode_predictions(*args, **kwargs)
https://colab.research.google.com/drive/1kLOtfIlx8gpJamwqZSXZiJ67Tz7f1Pah
"""
import tensorflow
from keras_preprocessing.image import load_img, img_to_array
from keras_applications.vgg16 import preprocess_input, decode_predictions, VGG16
model = VGG16()
images = load_img("speaker.jpg", target_size=(224, 224))
img_array = img_to_array(images)
img_array
img_array = img_array.reshape(
(1, img_array.shape[0], img_array.shape[1], img_array.shape[2]))
img_array.shape
image = preprocess_input(img_array)
image
img_pred = model.predict(image)
d_img_pred = decode_predictions(img_pred)
d_img_pred