Final deck: https://1drv.ms/p/s!Aq_TlvfieKvqu8t5DYBMbiD91PxE6Q?e=STaglB

Some areas to explore:

• CNN training from a few examples. We have several options for fine-tuning: yolo, aml resnets, torchvision
• given an extraction, unroll it to optimize OCR.
• other enhancements to improve OCR
• labeling and storage workspaces
• mobile app workflow

https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html

• conda install cython
• conda install jupyter
• pip install opencv-python
• pip install git+https://github.com/gautamchitnis/cocoapi.git@cocodataset-master#subdirectory=PythonAPI
• pip install pillow
• conda install matplotlib
• pip install azureml-sdk
• pip install azure.cli.core
• pip install azureml-contrib-dataset

• wget https://pjreddie.com/media/files/yolov3.weights

• potentially important: pytorch/vision#2720

Torchvision todo:

• move to a GPU box.
• double check batch size, epoch size
• visualize outputs
• understand evaluation outputs.