PYTHON

transfer learning in python with custom dataset

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.preprocessing import image_dataset_from_directory
training_set = image_dataset_from_directory(train_dir,
                                             shuffle=True,
                                             batch_size=32,
                                             image_size=(150, 150))
val_dataset = image_dataset_from_directory(validation_dir,
                                                  shuffle=True,
                                                  batch_size=32,
                                                  image_size=(150, 150))

transfer learning in python with custom dataset

model = tf.keras.applications.MobileNet(
    input_shape=None,
    alpha=1.0,
    depth_multiplier=1,
    dropout=0.001,
    include_top=True,
    weights="imagenet",
    input_tensor=None,
    pooling=None,
    classes=1000,
    classifier_activation="softmax",
)