pip3 install -r requirements.txt
python3 train_image.py -d=data/vegetables/
python3 train_image.py -d=data/vegetables/ -t 0.1
python3 train_image.py -d=data/vegetables/ -n 10
python3 test_image.py -m=model_data/vegetables/000/model.h5 -c=model_data/vegetables/000/classes.txt -i=data/vegetables/tomato/18bdb508fd44bff5df656448c57e00cb4a751572.jpg
python3 test_generator.py -d [DATASET_PATH]
python3 test_generator.py -d data/vegetables
python3 train_network.py -d [DATASET DIR]
python3 train_network.py -t test_data/vegetables_000/train_list.txt -f --image_size 28
Evaluate a model by applying it to dataset with labels.
python3 test_network.py -m [MODEL_PATH] -t [TEST_DIR]
python3 test_network.py -m logs/005/vegetables_model.21-0.38.hdf5 -t test_data/001