pin_memory = False if opt.usegpu: pin_memory = True train_dataset = SegDataset(ts.TRAINING_LMDB) assert train_dataset train_align_collate = AlignCollate( 'training', ts.N_CLASSES, ts.MAX_N_OBJECTS, ts.MEAN, ts.STD, ts.IMAGE_HEIGHT, ts.IMAGE_WIDTH, random_hor_flipping=ts.HORIZONTAL_FLIPPING, random_ver_flipping=ts.VERTICAL_FLIPPING, random_transposing=ts.TRANSPOSING, random_90x_rotation=ts.ROTATION_90X, random_rotation=ts.ROTATION, random_color_jittering=ts.COLOR_JITTERING, random_grayscaling=ts.GRAYSCALING, random_channel_swapping=ts.CHANNEL_SWAPPING, random_gamma=ts.GAMMA_ADJUSTMENT, random_resolution=ts.RESOLUTION_DEGRADING) train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=opt.batchsize, shuffle=True, num_workers=opt.nworkers, pin_memory=pin_memory, collate_fn=train_align_collate)
# Define Data Loaders pin_memory = False if opt.usegpu: pin_memory = True train_dataset = SegDataset(ts.TRAINING_LMDB) assert train_dataset train_align_collate = AlignCollate('training', ts.N_CLASSES, ts.MAX_N_OBJECTS, ts.MEAN, ts.STD, ts.IMAGE_HEIGHT, ts.IMAGE_WIDTH, random_hor_flipping=ts.HORIZONTAL_FLIPPING, random_ver_flipping=ts.VERTICAL_FLIPPING, random_90x_rotation=ts.ROTATION_90X, random_rotation=ts.ROTATION, random_color_jittering=ts.COLOR_JITTERING, use_coordinates=ts.USE_COORDINATES) train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=opt.batchsize, shuffle=True, num_workers=opt.nworkers, pin_memory=pin_memory, collate_fn=train_align_collate) test_dataset = SegDataset(ts.VALIDATION_LMDB)
np.random.seed(ts.SEED) torch.manual_seed(ts.SEED) # Define Data Loaders pin_memory = False if opt.usegpu: pin_memory = True train_dataset = SegDataset(ts.TRAINING_LMDB) train_align_collate = AlignCollate('training', ts.LABELS, ts.MEAN, ts.STD, ts.IMAGE_SIZE_HEIGHT, ts.IMAGE_SIZE_WIDTH, ts.ANNOTATION_SIZE_HEIGHT, ts.ANNOTATION_SIZE_WIDTH, ts.CROP_SCALE, ts.CROP_AR, random_cropping=ts.RANDOM_CROPPING, horizontal_flipping=ts.HORIZONTAL_FLIPPING, random_jitter=ts.RANDOM_JITTER) assert train_dataset train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=opt.batchsize, shuffle=True, num_workers=opt.nworkers, pin_memory=pin_memory, collate_fn=train_align_collate) test_dataset = SegDataset(ts.VALIDATION_LMDB)
print( 'WARNING: You have a CUDA device, so you should probably run with --cuda' ) # Define Data Loaders pin_memory = False if opt.usegpu: pin_memory = True test_dataset = SegDataset(opt.lmdb) test_align_collate = AlignCollate('test', ms.LABELS, ms.MEAN, ms.STD, ms.IMAGE_SIZE_HEIGHT, ms.IMAGE_SIZE_WIDTH, ms.ANNOTATION_SIZE_HEIGHT, ms.ANNOTATION_SIZE_WIDTH, ms.CROP_SCALE, ms.CROP_AR, random_cropping=ms.RANDOM_CROPPING, horizontal_flipping=ms.HORIZONTAL_FLIPPING) assert test_dataset test_loader = torch.utils.data.DataLoader(test_dataset, batch_size=opt.batchsize, shuffle=False, num_workers=opt.nworkers, pin_memory=pin_memory, collate_fn=test_align_collate) # Define Model model = Model(ms.LABELS, load_model_path=model_path, usegpu=opt.usegpu)