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2adb41a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | # Optional CNN texture classifier (e.g. corrugation) if a labeled class is required.
import torch
import torch.nn as nn
from ml.core.registry import register_model
@register_model("texture_classifier")
class RailTextureClassifier(nn.Module):
"""Compact convolutional neural network for railhead texture & corrugation pattern classification."""
def __init__(self, num_classes: int = 4):
super().__init__()
self.features = nn.Sequential(
nn.Conv2d(3, 32, kernel_size=3, padding=1),
nn.BatchNorm2d(32),
nn.ReLU(inplace=True),
nn.MaxPool2d(2, 2),
nn.Conv2d(32, 64, kernel_size=3, padding=1),
nn.BatchNorm2d(64),
nn.ReLU(inplace=True),
nn.AdaptiveAvgPool2d((1, 1)),
)
self.classifier = nn.Sequential(
nn.Flatten(),
nn.Linear(64, 32),
nn.ReLU(inplace=True),
nn.Linear(32, num_classes),
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
feat = self.features(x)
logits = self.classifier(feat)
return logits
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