Fixed demo + added demo README + new Dockerfile

Dockerfile

@@ -1,33 +1,18 @@
 # read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
 # you will also find guides on how best to write your Dockerfile
-FROM tensorflow/tensorflow:2.4.2-gpu
-
-# fix for broken keys in Ubuntu-18.04
-RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/3bf863cc.pub
-
-# install Python 3.7
-RUN apt-get update && apt-get install -y --no-install-recommends software-properties-common \
-    libsm6 libxext6 libxrender-dev curl \
-    && rm -rf /var/lib/apt/lists/*
-
-RUN echo "**** Installing Python ****" && \
-    add-apt-repository ppa:deadsnakes/ppa &&  \
-    apt-get install -y build-essential python3.7 python3.7-dev python3-pip && \
-    curl -O https://bootstrap.pypa.io/get-pip.py && \
-    python3.7 get-pip.py && \
-    rm -rf /var/lib/apt/lists/*
+#FROM pytorch/pytorch:1.10.0-cuda11.3-cudnn8-runtime
+FROM python:3.8.10-slim
 
 WORKDIR /code
 
 RUN apt-get update -y
+#RUN apt-get install -y python3 python3-pip
 RUN apt install git --fix-missing -y
+RUN apt install wget -y
 
 # install dependencies
 COPY ./demo/requirements.txt /code/demo/requirements.txt
-RUN python3.7 -m pip install --no-cache-dir --upgrade -r /code/demo/requirements.txt
-
-# Install wget
-RUN apt install wget -y
+RUN python -m pip install --no-cache-dir --upgrade -r /code/demo/requirements.txt
 
 # Set up a new user named "user" with user ID 1000
 RUN useradd -m -u 1000 user
@@ -51,4 +36,4 @@ COPY --chown=user . $HOME/app
 # Download test sample
 RUN wget https://github.com/VemundFredriksen/LungTumorMask/releases/download/0.0.1/lung_001.nii.gz
 
-CMD ["python3.7", "demo/app.py"]
+CMD ["python", "demo/app.py"]

demo/README.md

@@ -0,0 +1,31 @@
+# Hugging Face demo - through docker SDK
+
+Deploying simple models in a gradio-based web interface in Hugging Face spaces is easy.
+For any other custom pipeline, with various dependencies and challenging behaviour, it
+might be necessary to use Docker containers instead.
+
+For every new push to the main branch, continuous deployment to the Hugging Face
+`LungTumorMask` space is performed through a GitHub Actions workflow.
+
+When the space is updated, the Docker image is rebuilt/updated (caching if possible).
+Then when finished, the end users can test the app as they please.
+
+Right now, the functionality of the app is extremely limited, only offering a widget
+for uploading a NIfTI file (`.nii` or `.nii.gz`) and visualizing the produced surface
+of the predicted lung tumor volume when finished processing.
+
+Analysis process can be monitored from the `Logs` tab next to the `Running` button
+in the Hugging Face `LungTumorMask` space.
+
+It is also possible to build the app as a docker image and deploy it. To do so follow these steps:
+
+```
+docker build -t lungtumormask:latest ..
+docker run -it -p 7860:7860 lungtumormask:latest
+```
+
+Then open `http://localhost:7860` in your favourite internet browser to view the demo.
+
+TODOs:
+- [X] Add gallery widget to enable scrolling through 2D slices
+- [X] Render segmentation for individual 2D slices as overlays

demo/requirements.txt

@@ -1,2 +1,2 @@
 lungtumormask @ git+https://github.com/vemundfredriksen/LungTumorMask.git
-gradio==3.32.0
+gradio==3.44.4

demo/src/compute.py

@@ -1,3 +1,3 @@
 def run_model(input_path):
     from lungtumormask import mask
-    mask.mask(input_path, "./output.nii.gz", lung_filter=True, threshold=0.5, radius=1, batch_size=1)
+    mask.mask(input_path, "./prediction.nii.gz", lung_filter=True, threshold=0.5, radius=1, batch_size=1)

demo/src/gui.py

@@ -11,7 +11,7 @@ class WebUI:
         self.pred_images = []
 
         # @TODO: This should be dynamically set based on chosen volume size
-        self.nb_slider_items = 160
+        self.nb_slider_items = 300
 
         self.class_name = class_name
         self.cwd = cwd
@@ -100,4 +100,4 @@ class WebUI:
 
         # sharing app publicly -> share=True: https://gradio.app/sharing-your-app/
         # inference times > 60 seconds -> need queue(): https://github.com/tloen/alpaca-lora/issues/60#issuecomment-1510006062
-        demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=True)
+        demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False)