def get_tusimple(params):
# augmentation
flip = Flip()
translate = Translate()
rotate = Rotate()
add_noise = AddGaussianNoise()
change_intensity = ChangeIntensity()
resize = Resize(rows=256, cols=512)
norm_to_1 = NormalizeInstensity()
whc_to_cwh = TransposeNumpyArray((2, 0, 1))
train_dataset = DatasetTusimple(
root_path=params.train_root_url,
json_files=params.train_json_file,
transform=transforms.Compose([
flip, translate, rotate, add_noise, change_intensity, resize,
norm_to_1, whc_to_cwh
]),
)
val_dataset = DatasetTusimple(
params.val_root_url,
params.val_json_file,
transform=transforms.Compose([resize, norm_to_1, whc_to_cwh]),
)
return train_dataset, val_dataset
def __init__(self, ):
print("usage examples:")
print("python -m dataset.culane.test sample")
print("python -m dataset.culane.test batch")
print("python -m dataset.culane.test batch shuffle=False")
flip = Flip(1.0)
translate = Translate(1.0)
rotate = Rotate(1.0)
add_noise = AddGaussianNoise(1.0)
change_intensity = ChangeIntensity(1.0)
resize = Resize(rows=256, cols=512)
hwc_to_chw = TransposeNumpyArray((2, 0, 1))
norm_to_1 = NormalizeInstensity()
self.train_dataset = DatasetCollections(transform=transforms.Compose([
flip, translate, rotate, add_noise, change_intensity, resize,
norm_to_1, hwc_to_chw
]), )
def __init__(self,):
flip = Flip(1.0)
translate = Translate(1.0)
rotate = Rotate(1.0)
add_noise = AddGaussianNoise(1.0)
change_intensity = ChangeIntensity(1.0)
resize = Resize(rows=256, cols=512)
hwc_to_chw = TransposeNumpyArray((2, 0, 1))
norm_to_1 = NormalizeInstensity()
json_file = ['label_data_0313.json', 'label_data_0531.json', 'label_data_0601.json']
self.train_dataset = DatasetTusimple(root_path="/media/zzhou/data-tusimple/lane_detection/train_set/",
json_files=json_file,
transform=transforms.Compose([flip,
translate,
rotate,
add_noise,
change_intensity,
resize,
norm_to_1,
hwc_to_chw]),)
def __init__(self,):
print("usage examples:")
print("python -m dataset.bdd100k.test sample")
print("python -m dataset.bdd100k.test batch")
print("python -m dataset.bdd100k.test batch shuffle=False")
flip = Flip(1.0)
translate = Translate(1.0)
rotate = Rotate(1.0)
add_noise = AddGaussianNoise(1.0)
change_intensity = ChangeIntensity(1.0)
resize = Resize(rows=256, cols=512)
hwc_to_chw = TransposeNumpyArray((2, 0, 1))
norm_to_1 = NormalizeInstensity()
self.train_dataset = DatasetBDD100K(root_path="/media/zzhou/data-BDD100K/bdd100k/",
json_files="labels/bdd100k_labels_images_train.json",
transform=transforms.Compose([flip,
translate,
rotate,
add_noise,
change_intensity,
resize,
norm_to_1,
hwc_to_chw]), )