Python Deep Learning Projects

Data preparation for a deep CNN encoder

Next, we will use Inception-v3 (pretrained on ImageNet) to classify each image. We will extract features from the last convolutional layer. We will create a helper function that will transform the input image to the format that is expected by Inception-v3:

#Resizing the image to (299, 299)#Using the preprocess_input method to place the pixels in the range of -1 to 1.def load_image(image_path):    img = tf.read_file(image_path)    img = tf.image.decode_jpeg(img, channels=3)    img = tf.image.resize_images(img, (299, 299))    img = tf.keras.applications.inception_v3.preprocess_input(img)    return img, image_path

Now let's initialize the Inception-v3 model and load the pretrained ImageNet weights. To do so, we'll create ...