| .. | ||
| Colab_UNet_Industrial_TF_TFHub_export.ipynb | ||
| Colab_UNet_Industrial_TF_TFHub_inference_demo.ipynb | ||
| Colab_UNet_Industrial_TF_TFTRT_inference_demo.ipynb | ||
| download_and_preprocess_dagm2007_public.sh | ||
| README.md | ||
| TensorFlow_UNet_Industrial_TF_train_and_inference.ipynb | ||
Jupyter demo notebooks
This folder contains demo notebooks for the TensorFlow UNet Industrial model.
1. TensorFlow_UNet_Industrial_TF_train_and_inference.ipynb: end to end training and inference demo.
The most convenient way to make use of the NVIDIA Tensorflow UNet model is via a docker container, which provides a self-contained, isolated and re-producible environment for all experiments. Refer to the Quick Start Guide section of the Readme documentation for a comprehensive guide. We briefly summarize the steps here.
First, clone the repository:
git clone https://github.com/NVIDIA/DeepLearningExamples.git
cd DeepLearningExamples/TensorFlow/Segmentation/UNet_Industrial
Next, build the NVIDIA UNet_Industrial container:
docker build . --rm -t unet_industrial:latest
Then launch the container with:
nvidia-docker run -it --rm \
--shm-size=2g --ulimit memlock=-1 --ulimit stack=67108864 \
-v /path/to/dataset:/data/dagm2007/ \
-v /path/to/results:/results \
unet_industrial:latest
where /path/to/dataset is the path on the host machine where the data was/is to be downloaded. More on data set preparation in the next section. /path/to/results is wher the trained model will be stored.
Within the docker interactive bash session, start Jupyter with
jupyter notebook --ip 0.0.0.0 --port 8888
Then open the Jupyter GUI interface on your host machine at http://localhost:8888. Within the container, this notebook itself is located at /workspace/unet_industrial/notebooks.
2. Colab_UNet_Industrial_TF_TFTRT_inference_demo.ipynb: inference from a pretrained UNet model with TensorFlow-TensorRT (TF-TRT).
This notebook is designed to run on Google Colab via this link
3. Colab_UNet_Industrial_TF_TFHub_export.ipynb: Colab notebook demostrating creation of TF-Hub module from NVIDIA NGC UNet model.
This notebook is designed to run on Google Colab vie this link
4. Colab_UNet_Industrial_TF_TFHub_inference_demo.ipynb: Colab notebook demostrating inference with TF-Hub UNet module.
This notebook is designed to run on Google Colab vie this link