""" Add dataset configurations here. Each dataset must have the following structure: NAME = { IMAGE_HEIGHT: int, IMAGE_WIDTH: int, ITEMS_TO_DESCRIPTIONS: { 'image_a': 'A 3-channel image.', 'image_b': 'A 3-channel image.', 'flow': 'A 2-channel optical flow field', }, SIZES: { 'train': int, 'validate': int, (optional) ... }, BATCH_SIZE: int, PATHS: { 'train': '', 'validate': '', (optional) ... } } """ """ note that one step = one batch of data processed, ~not~ an entire epoch 'coeff_schedule_param': { 'half_life': 50000, after this many steps, the value will be i + (f - i)/2 'initial_coeff': 0.5, initial value 'final_coeff': 1, final value }, """ FLYING_CHAIRS_DATASET_CONFIG = { 'IMAGE_HEIGHT': 384, 'IMAGE_WIDTH': 512, 'ITEMS_TO_DESCRIPTIONS': { 'image_a': 'A 3-channel image.', 'image_b': 'A 3-channel image.', 'flow': 'A 2-channel optical flow field', }, 'SIZES': { 'train': 22232, 'validate': 640, 'sample': 8, }, 'BATCH_SIZE': 8, 'PATHS': { 'train': './data/tfrecords/fc_train.tfrecords', 'validate': './data/tfrecords/fc_val.tfrecords', 'sample': './data/tfrecords/fc_sample.tfrecords', }, 'PREPROCESS': { 'scale': False, 'crop_height': 320, 'crop_width': 448, 'image_a': { 'translate': { 'rand_type': "uniform_bernoulli", 'exp': False, 'mean': 0, 'spread': 0.4, 'prob': 1.0, }, 'rotate': { 'rand_type': "uniform_bernoulli", 'exp': False, 'mean': 0, 'spread': 0.4, 'prob': 1.0, }, 'zoom': { 'rand_type': "uniform_bernoulli", 'exp': True, 'mean': 0.2, 'spread': 0.4, 'prob': 1.0, }, 'squeeze': { 'rand_type': "uniform_bernoulli", 'exp': True, 'mean': 0, 'spread': 0.3, 'prob': 1.0, }, 'noise': { 'rand_type': "uniform_bernoulli", 'exp': False, 'mean': 0.03, 'spread': 0.03, 'prob': 1.0, }, }, # All preprocessing to image A will be applied to image B in addition to the following. 'image_b': { 'translate': { 'rand_type': "gaussian_bernoulli", 'exp': False, 'mean': 0, 'spread': 0.03, 'prob': 1.0, }, 'rotate': { 'rand_type': "gaussian_bernoulli", 'exp': False, 'mean': 0, 'spread': 0.03, 'prob': 1.0, }, 'zoom': { 'rand_type': "gaussian_bernoulli", 'exp': True, 'mean': 0, 'spread': 0.03, 'prob': 1.0, }, 'gamma': { 'rand_type': "gaussian_bernoulli", 'exp': True, 'mean': 0, 'spread': 0.02, 'prob': 1.0, }, 'brightness': { 'rand_type': "gaussian_bernoulli", 'exp': False, 'mean': 0, 'spread': 0.02, 'prob': 1.0, }, 'contrast': { 'rand_type': "gaussian_bernoulli", 'exp': True, 'mean': 0, 'spread': 0.02, 'prob': 1.0, }, 'color': { 'rand_type': "gaussian_bernoulli", 'exp': True, 'mean': 0, 'spread': 0.02, 'prob': 1.0, }, 'coeff_schedule_param': { 'half_life': 50000, 'initial_coeff': 0.5, 'final_coeff': 1, }, } }, }