How can I change pretrained resnet model to accept single channel image?

[Nishanth_Sasankan]

someone told me this, but I have not tried it yet

Grayscale images for resenet and deeplabv3

You can always define a custom resnet and change the first layer to adapt for your input shape. For example, with resnet18: import torch import torchvision resnet = torchvision.models.resnet18() input = torch.randn((16,3,244,244)) output = resnet(input) print(output.shape) # this fails becasue resnet expects 3 channels #input = torch.randn((16,1,244,244)) #output = resnet(input) #print(output.shape) import torch.nn as nn class MyResNet(nn.Module): def __init__(self, in_channels=1): …