SIZE = 128
HEIGHT = 137
WIDTH = 236
OUT_DIR = 'models'
# https://albumentations.readthedocs.io/en/latest/api/augmentations.html
data_transforms = albumentations.Compose([
albumentations.ShiftScaleRotate(shift_limit=0.0625,
scale_limit=0.1,
rotate_limit=(15, 30),
p=0.5),
albumentations.CenterCrop(96, 96, p=1),
albumentations.Cutout(p=0.3),
albumentations.Resize(128, 128, p=1),
albumentations.OneOf([
GridMask(num_grid=3, rotate=(15, 30), p=0.3),
GridMask(num_grid=4, rotate=(5, 15), p=0.3),
],
p=0.3),
])
data_transforms_test = albumentations.Compose([
albumentations.Flip(p=0),
albumentations.CenterCrop(96, 96, p=1),
albumentations.Resize(128, 128, p=1),
])
class BengaliAIDataset(torch.utils.data.Dataset):
def __init__(self, df, y=None, transform=None):
self.df = df.iloc[:, 1:].values
LOGGER_PATH = f"logs/log_{EXP_ID}.txt"
setup_logger(out_file=LOGGER_PATH)
LOGGER.info("seed={}".format(SEED))
SIZE = 128
HEIGHT = 137
WIDTH = 236
OUT_DIR = 'models'
# https://albumentations.readthedocs.io/en/latest/api/augmentations.html
data_transforms = albumentations.Compose([
albumentations.Flip(p=0.2),
albumentations.Rotate(limit=15, p=0.2),
albumentations.ShiftScaleRotate(rotate_limit=15, p=0.5),
albumentations.Cutout(p=0.2),
GridMask(num_grid=3, rotate=15, p=0.3),
])
'''
data_transforms = albumentations.Compose([
albumentations.ShiftScaleRotate(p=1,border_mode=cv2.BORDER_CONSTANT,value =1),
GridMask(num_grid=3, rotate=15, p=0.3),
albumentations.OneOf([
albumentations.ElasticTransform(p=0.1, alpha=1, sigma=50, alpha_affine=50,border_mode=cv2.BORDER_CONSTANT,value =1),
albumentations.GridDistortion(distort_limit =0.05 ,border_mode=cv2.BORDER_CONSTANT,value =1, p=0.1),
albumentations.OpticalDistortion(p=0.1, distort_limit= 0.05, shift_limit=0.2,border_mode=cv2.BORDER_CONSTANT,value =1)
], p=0.3),
albumentations.OneOf([
albumentations.GaussNoise(var_limit=1.0),
albumentations.Blur(),
albumentations.GaussianBlur(blur_limit=3)
], p=0.4),
SIZE = 128
HEIGHT = 137
WIDTH = 236
OUT_DIR = 'models'
data_transforms_96 = albumentations.Compose([
albumentations.ShiftScaleRotate(shift_limit=0.0625,
scale_limit=0.1,
rotate_limit=(5, 15),
p=0.5),
albumentations.CenterCrop(96, 96, p=1),
albumentations.Resize(256, 256, p=1),
albumentations.Cutout(num_holes=1, max_h_size=40, max_w_size=15, p=0.1),
albumentations.OneOf([
GridMask(num_grid=1, rotate=(5, 15), p=0.15),
GridMask(num_grid=2, rotate=(5, 15), p=0.15),
],
p=0.1)
])
data_transforms_104 = albumentations.Compose([
albumentations.ShiftScaleRotate(shift_limit=0.0625,
scale_limit=0.1,
rotate_limit=(5, 15),
p=0.3),
albumentations.CenterCrop(104, 104, p=1),
albumentations.Resize(256, 256, p=1),
albumentations.Cutout(p=0.3),
albumentations.OneOf([
GridMask(num_grid=2, rotate=(5, 15), p=0.3),