This repository contains a TensorFlow implementation of the CNN-MIL combination described in Classifying and Segmenting Microscopy Images with Deep Multiple Instance Learning from Brendan Frey`s lab.
- Install requirements (will install CPU version of TensorFlow):
pip install requirements.txt. - Follow instructions on (tf_cnnvis)[https://github.com/InFoCusp/tf_cnnvis] README.
tf_cnnvis/should be at the root after installation.
The following options are available for running the model:
-e, Number of epochs for which to train the model-r, Specify the seed-b, Batch size for training-s, Where to save model-m, Name of model-t, Whether to train (1) or load model (0)
The datasets.py file contains a small cluttered MNIST dataset. Each
image is 72 x 72 pixels and contains four numbers: three are 0's, the other one is a number
1 - 9 excluding 0. The locations of these numbers in the image are semi-random.
This dataset is a much smaller version of what the authors use in the paper.