Deploying Lesson 3 - Image Segmengation - Results in Error

I’ve gone over the image segmentation notebook with the camvid dataset and exported the pickle model using learn.export() to deploy on a flask web app using a hosting service (which means the notebook and flask app are not run on the exact same environments), however when trying to use learn = load_learner(model_path) I get the error:

File ".local/lib/python3.6/site-packages/torch/", line 538, in _load result = unpickler.load() AttributeError: Can't get attribute 'acc_camvid' on <module '__main__' (built-in)>

I believe this is because in the notebook, we defined our own metric called acc_camvid with the following function:

name2id = {v:k for k,v in enumerate(codes)}
void_code = name2id['Void']

def acc_camvid(input, target):
    target = target.squeeze(1)
    mask = target != void_code
    return (input.argmax(dim=1)[mask]==target[mask]).float().mean()

I put the function as well as the ‘codes’ array into a file called and imported it into my flask app using from helpers import acc_camvid but I still get the error. So I don’t know how to add the attribute. I think I might have to recreate the model somehow but I’m not sure.

Also please let me know if this is the wrong place to ask. This is my first post.

Hi @visiondev

I think BentoML ( can help you to move forward with this.

You can check out the fastai examples (pet classification and tabular csv) at