mataney

class SegDataset(Dataset):
    def __init__(self, csv_loc, data_dir, augments=200):
        self.data_dir = data_dir
        self.images_data = read_csv(csv_loc)
        self.images = self.prepare_images()

    def transform(self, raw, seg):
        i, j, h, w = transforms.RandomCrop.get_params(
            raw, output_size=(128, 128))
        raw = trans_f.crop(raw, i, j, h, w)

mataney

device = torch.device("cuda")

class SegDataset(Dataset):
    def __init__(self, csv_loc, data_dir):
        self.data_dir = data_dir
        self.images_data = read_csv(csv_loc)
        self.images = self.prepare_images()

    def transform(self, raw, seg):
        t = transforms.CenterCrop(128)

mataney

class UNet(nn.Module):

    def __init__(self, in_dim, out_dim, num_filter, lr):
        super(UNet, self).__init__()
        self.in_dim = in_dim
        self.out_dim = out_dim
        self.num_filter = num_filter
        act_fn = nn.LeakyReLU(0.2, inplace=True)

        def conv_block(in_dim, out_dim, act_fn):

mataney

from tensorflow.core.example import example_pb2
import tensorflow as tf
import glob, struct

def text_generator(example_generator):
    """Generates article and abstract text from tf.Example.

    Args:
      example_generator: a generator of tf.Examples from file. See data.example_generator"""
    while True: