Model inference in one step

[kasra-hosseini]

Summary

Currently, we first need to patchify an image and then do the model inference (in two separate steps). In this issue, we plan to have a method that does both steps, i.e.,

# example interface
my_classifier.inference(path2image, **kwds for the slice method, including patch size, ...)
my_classifier.plot()

TODO

• Refer to https://github.com/alan-turing-institute/mapreader-plant-scivision. Here, we have a function/method called "predict" that does model inference on an image. Under the hood, it slices an image into patches, does model inference on the patches and then plot the results (and return the predicted labels).
• It would be interesting to have a similar function/method in MapReader.

[kasra-hosseini]

Implemented here: https://github.com/alan-turing-institute/mapreader-plant-scivision/blob/main/mapreader-plant-scivision/model.py

[kasra-hosseini]

As mentioned above, this is now implemented here: https://github.com/alan-turing-institute/mapreader-plant-scivision/blob/main/mapreader-plant-scivision/model.py

Also, we have a notebook on scivision gallery: https://github.com/scivision-gallery/plant-phenotyping-classification (it is WIP)