You could load your grayscale image and convert it to an RGB one.
E.g. if you are using PIL, you can call Image.open('your_path').convert('RGB').
Alternatively you could add a conv layer at the beginning of your model, which takes in_channels=1 and returns out_channels=3. Since this layer would need training, I would try the first approach to get the features.