def __init__(self, input_size, color_mean, color_std):
self.data_transform = {
"train":
Compose([
Scale(scale=[0.5, 1.5]),
RandomRotation(angle=[-10, 10]),
RandomMirror(),
Resize(input_size),
Normalize_Tensor(color_mean, color_std),
]),
"val":
Compose(
[Resize(input_size),
Normalize_Tensor(color_mean, color_std)])
}
from torch.optim import lr_scheduler
from utils import ChestXrayDataset, ToTensor, LeftToRightFlip, RandomCrop, Resize, ColorJitter, RandomRotation
from torchvision import transforms, models
from torch.utils.data import DataLoader
import torch
import torch.nn as nn
from focal_loss import FocalLoss
from model import get_model
transform = {
'train':
transforms.Compose([
LeftToRightFlip(0.5),
RandomRotation(angle=3, p=0.5),
Resize(224),
ColorJitter(p=0.5,
color=0.1,
contrast=0.1,
brightness=0.1,
sharpness=0.1),
RandomCrop(scale=210, p=0.5),
Resize(224),
ToTensor()
]),
'test':
transforms.Compose([ToTensor()])
}
datasets = {