For using text_dataset_from_directory directory structure should be as follows. Tensorflow: Unable to call "image_dataset_from_directory" Then calling image_dataset_from_directory(main_directory, labels='inferred') will return a tf.data.Dataset that yields batches of images from the subdirectories class_a and class_b, together with labels 0 and 1 (0 corresponding to class_a and 1 corresponding to class_b).. tf.summary.image("Training data", img, step=0) Now, use TensorBoard to examine the image. # Initiating the writer and creating the tfrecords file. Along with the above files, the loss and accuracy plots will also be generated as we start executing the. preprocessing_function: function that will be implied on each input. Get labels from dataset when using tensorflow … On Line 32 we begin to loop over dataset type, image paths, and output directory. Der Aufruf von image_dataset_from_directory(main_directory, labels='inferred') dann ein tf.data.Dataset zurück, das Stapel von Bildern aus den Unterverzeichnissen class_a und class_b zusammen mit den Labels 0 und 1 (0 entsprechend class_a und 1 entsprechend class_b) liefert . Image