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)