from core.siamese import Siamese
model = Siamese('mobilenet_like',
input_shape=(672, 896, 3),
embedding_size=128)
model.load_weights('trained/final_weights.h5')
#model.make_embeddings('data/train', 'data/train.csv', batch_size=5, meta_dir='data/meta')
model.load_embeddings('trained/embeddings.pkl')
model.predict('data/test', meta_dir='data/meta')
#model.load_predictions('trained/predictions.pkl')
model.make_kaggle_csv('data/meta/idx_to_whales_mapping.npy')
from core.siamese import Siamese
model = Siamese('resnet_like_33', input_shape=(384, 512, 3), embedding_size=128, strategy='batch_all')
model.load_weights('trained/checkpoint-05.h5')
model.load_embeddings('trained/embeddings.pkl')
model.load_predictions('trained/predictions.pkl')
model.make_kaggle_csv('trained/idx_to_whales_mapping.npy')