Fine-tune a keras model with a TensorFlow backend (either trained on ImageNet or our PlantNet/Oxford Flower Datasets) using the labels images and labels from data collection.
create a generator to stream in training data
load data in batches
perform data augmentation
parallelized (optional)
replace final layer with a fully connected layer with number of neurons equal to the number of plant categories.
Fine-tune a keras model with a TensorFlow backend (either trained on ImageNet or our PlantNet/Oxford Flower Datasets) using the labels images and labels from data collection.