| import torch |
| import numpy as np |
| import torch.nn.functional as F |
| import matplotlib.pyplot as plt |
|
|
|
|
| def adjust_lr(optimizer, init_lr, epoch, decay_rate=0.1, decay_epoch=30): |
| decay = decay_rate ** (epoch // decay_epoch) |
| for param_group in optimizer.param_groups: |
| param_group['lr'] = decay*init_lr |
| lr=param_group['lr'] |
| return lr |
|
|
|
|
| def dice_coef(result, reference): |
| result = np.atleast_1d(result.astype(np.bool_)) |
| reference = np.atleast_1d(reference.astype(np.bool_)) |
|
|
| intersection = np.count_nonzero(result & reference) |
|
|
| size_i1 = np.count_nonzero(result) |
| size_i2 = np.count_nonzero(reference) |
|
|
| try: |
| dc = 2. * intersection / float(size_i1 + size_i2) |
| except ZeroDivisionError: |
| dc = 0.0 |
|
|
| return dc |
|
|
|
|
| def structure_loss(pred, mask): |
| """ |
| loss function (ref: F3Net-AAAI-2020) |
| """ |
| weit = 1 + 5 * torch.abs(F.avg_pool2d(mask, kernel_size=31, stride=1, padding=15) - mask) |
| wbce = F.binary_cross_entropy_with_logits(pred, mask, reduction='mean') |
| wbce = (weit * wbce).sum(dim=(2, 3)) / weit.sum(dim=(2, 3)) |
|
|
| pred = torch.sigmoid(pred) |
| inter = ((pred * mask) * weit).sum(dim=(2, 3)) |
| union = ((pred + mask) * weit).sum(dim=(2, 3)) |
| wiou = 1 - (inter + 1) / (union - inter + 1) |
| return (wbce + wiou).mean() |
|
|
|
|
| def plot_image(path, epoch_losses, epoch_dices, epoch_val_losses, epoch_val_dices): |
| losses = np.array(epoch_losses) |
| dices = np.array(epoch_dices) |
| val_losses = np.array(epoch_val_losses) |
| val_dices = np.array(epoch_val_dices) |
|
|
| plt.figure(figsize=(6, 6)) |
| plt.plot(losses, lw=1.5) |
| plt.title('Train Loss') |
| plt.xlabel('Epoch Number') |
| plt.ylabel('Loss') |
| plt.savefig(f'{path}/train_loss.png') |
|
|
| plt.figure(figsize=(6, 6)) |
| plt.plot(dices, lw=1.5) |
| plt.title('Train Dice') |
| plt.xlabel('Epoch Number') |
| plt.ylabel('Dice') |
| plt.savefig(f'{path}/train_dice.png') |
|
|
| plt.figure(figsize=(6, 6)) |
| plt.plot(val_losses, lw=1.5) |
| plt.title('Valid Loss') |
| plt.xlabel('Epoch Number') |
| plt.ylabel('Loss') |
| plt.savefig(f'{path}/valid_loss.png') |
|
|
| plt.figure(figsize=(6, 6)) |
| plt.plot(val_dices, lw=1.5) |
| plt.title('Valid Dice') |
| plt.xlabel('Epoch Number') |
| plt.ylabel('Dice') |
| plt.savefig(f'{path}/valid_dice.png') |
|
|
