IranCars_V0 / model.py
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import torch
import torchvision
from torch import nn
device='cpu'
def create_model(num_classes: int=13):
weights = torchvision.models.EfficientNet_B0_Weights.DEFAULT
transforms = weights.transforms()
model = torchvision.models.efficientnet_b0(weights=weights).to(device)
for param in model.features.parameters():
param.requires_grad = False
model.classifier = torch.nn.Sequential(
torch.nn.Dropout(p=0.2, inplace=True),
torch.nn.Linear(in_features=1280, out_features=13, bias=True)
).to(device)
return model, transforms