Port of https://github.com/vijishmadhavan/SkinDeep from FastAI 1 to FastAI 2.
To run the Jupyter Notebooks I use a an extended version of the FastAI docker containers. https://github.com/fastai/docker-containers. The changes I've made are:
- Changed the root from fastai to local
- Changed the base ubuntu image to an NVIDIA/CUDA one (nvidia/cuda:11.3.1-base-ubuntu20.04) for GPU training
- Added an image (-ext) with my dependencies and endpoint
- Locally install ffmpeg libsm6 libxext6
- Pip install nvidia-ml-py3 opencv-python Pillow
This is the command that I use to run the customized container.
docker run --rm \
--gpus all --privileged \
--name fastai --ipc=host \
-p 8888:8888 \
-v `pwd`:/home \
local/fastai-ext \
jupyter notebook
Haven't set this up yet
Place your training set in data/rawdata. The tattoo image and clean image should be named _tattoo.jpeg and _clean.jpeg respectively.
Run the Deink - Process Raw Data notebook. This will prep the images for training and put them in data/tattoo and data/clean respectively.
The Deink - Train Model notebook, unsurprisingly, is for training the model. There is a cell for setting training variables.
Use the Deink - Predict Image notebook to load the model and process an image of your choosing.