moving unzip and wget to app.py

Dockerfile

@@ -1,7 +1,7 @@
 # Use an official Python runtime as a parent image
 FROM python:3.10.12
 
-RUN apt-get update && apt-get install -y unzip wget
+# RUN apt-get update && apt-get install -y unzip wget
 
 # Set up a new user named "user" with user ID 1000
 RUN useradd -m -u 1000 user
@@ -29,21 +29,21 @@ COPY --chown=user . $HOME/app
 # RUN wget https://github.com/rordenlab/dcm2niix/releases/latest/download/dcm2niix_lnx.zip && \
 #     unzip dcm2niix_lnx.zip && \
 #     cp dcm2niix /home/user/.local/bin
-RUN pip install git+https://github.com/rordenlab/dcm2niix.git 
-RUN dcm2niix -h
+# RUN pip install git+https://github.com/rordenlab/dcm2niix.git 
+# RUN dcm2niix -h
 
 # Install any needed packages specified in requirements.txt
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Download files as the non-root user
-RUN wget -O scaling_factors.csv https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/scaling_factors.csv
-RUN wget -O metadata_only_model.zip https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/metadata_only_model.zip
-RUN wget -O images_only_model.zip https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_only_model.zip
-RUN wget -O images_and_metadata_model.zip https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_and_metadata_model.zip
+# # Download files as the non-root user
+# RUN wget -O scaling_factors.csv https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/scaling_factors.csv
+# RUN wget -O metadata_only_model.zip https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/metadata_only_model.zip
+# RUN wget -O images_only_model.zip https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_only_model.zip
+# RUN wget -O images_and_metadata_model.zip https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_and_metadata_model.zip
 
-RUN unzip "metadata_only_model.zip" -d "metadata_only_model/"
-RUN unzip "images_only_model.zip" -d "images_only_model/"
-RUN unzip "images_and_metadata_model.zip" -d "images_and_metadata_model/"
+# RUN unzip "metadata_only_model.zip" -d "metadata_only_model/"
+# RUN unzip "images_only_model.zip" -d "images_only_model/"
+# RUN unzip "images_and_metadata_model.zip" -d "images_and_metadata_model/"
 
 # Create the .streamlit directory
 RUN mkdir -p .streamlit

app.py

@@ -56,12 +56,24 @@ print('selected_series: ' + str(selected_series))
 if st.button("Run inference"):
 
     # Code to run when the button is pressed
-    st.write("Button pressed! Running inference")
+    st.write("Running inference")
 
     if os.path.exists("DICOMScanClassification_user_demo.ipynb"):
         os.remove("DICOMScanClassification_user_demo.ipynb")
 
-    subprocess.run(["wget", "https://raw.githubusercontent.com/deepakri201/DICOMScanClassification_pw41/main/DICOMScanClassification_user_demo.ipynb"])
+    if not os.path.exists("DICOMScanClassification_user_demo.ipynb"):
+        subprocess.run(["wget", "https://raw.githubusercontent.com/deepakri201/DICOMScanClassification_pw41/main/DICOMScanClassification_user_demo.ipynb"])
+    if not os.path.exists("scaling_factors.csv"):
+        subprocess.run(["wget", "-O", "scaling_factors.csv", "https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/scaling_factors.csv"])
+    if not os.path.exists("metadata_only_model.zip"):
+        subprocess.run(["wget", "-O", "metadata_only_model.zip", "https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/metadata_only_model.zip"])
+        subprocess.run(["unzip", "metadata_only_model.zip", -d, "metadata_only_model/"])
+    if not os.path.exists("images_only_model.zip"):
+        subprocess.run(["wget", "-O", "images_only_model.zip", "https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_only_model.zip"])
+        subprocess.run(["unzip", "images_only_model.zip", -d, "images_only_model/"])
+    if not os.path.exists("images_and_metadata_model.zip"):
+        subprocess.run(["wget", "-O", "images_and_metadata_model.zip", "https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_and_metadata_model.zip"])
+        subprocess.run(["unzip", "images_and_metadata_model.zip", -d, "images_and_metadata_model/"])
 
     # pm.execute_notebook(
     #         "DICOMScanClassification_user_demo.ipynb",
@@ -78,5 +90,9 @@ if st.button("Run inference"):
             file_name="output.ipynb",
             mime="application/json"
         )
+    
+    # Show 2D image 
+
+    # Display classification results in a table - display dataframe 
 
     

packages.txt

@@ -0,0 +1,2 @@
+unzip 
+wget

requirements.txt

@@ -13,4 +13,5 @@ nibabel==4.0.2
 matplotlib==3.7.1
 scikit-learn==1.2.2
 sklearn-pandas
-numpy==1.25.2
+numpy==1.25.2
+dcmniix==1.0.20220715