fixing dcm2nii and wget etc

Dockerfile

@@ -1,8 +1,6 @@
 # Use an official Python runtime as a parent image
 FROM python:3.10.12
 
-# 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
 
@@ -29,17 +27,16 @@ 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
+
 
 # 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 curl https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/scaling_factors.csv
+# RUN curl https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/metadata_only_model.zip
+# RUN curl https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_only_model.zip
+# RUN curl 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/"
@@ -58,4 +55,4 @@ maxMessageSize = 2000\n\
 EXPOSE 8501
 
 # Run filter_data_app.py when the container launches
-CMD streamlit run app.py
+CMD streamlit run app.py

app.py

@@ -56,33 +56,30 @@ print('selected_series: ' + str(selected_series))
 if st.button("Run inference"):
 
     # Code to run when the button is pressed
-    st.write("Running inference")
-
-    if os.path.exists("DICOMScanClassification_user_demo.ipynb"):
-        os.remove("DICOMScanClassification_user_demo.ipynb")
+    st.write("Button pressed! Running inference")
 
     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"])
+        subprocess.run(["wget", "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/"])
+        subprocess.run(["wget", "https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/metadata_only_model.zip"])
+        subprocess.run(["unzip", "metadata_only_model.zip"])
+
     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",
-    #         'output.ipynb',
-    #         parameters = dict(SeriesInstanceUID=selected_series)
-    # )
+        subprocess.run(["wget", "https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_and_metadata_model.zip"])
+        subprocess.run(["unzip", "images_and_metadata_model.zip"])
     
+    if not os.path.exists("images_only_model.zip"):
+        subprocess.run(["wget", "https://github.com/deepakri201/DICOMScanClassification/releases/download/v1.0.0/images_only_model.zip"])
+        subprocess.run(["unzip", "images_only_model.zip"])
+        
     subprocess.run(["papermill", "-p", "SeriesInstanceUID", selected_series,  "DICOMScanClassification_user_demo.ipynb", "output.ipynb"])
 
+    st.write(subprocess.run(["ls","-R"]))
+             
     with open('output.ipynb', "rb") as f:
         st.download_button(
             label="Download the output notebook file",
@@ -90,9 +87,7 @@ if st.button("Run inference"):
             file_name="output.ipynb",
             mime="application/json"
         )
-    
-    # Show 2D image 
 
-    # Display classification results in a table - display dataframe 
+    # show classification results df 
 
-    
+    # show image 

requirements.txt

@@ -14,4 +14,4 @@ matplotlib==3.7.1
 scikit-learn==1.2.2
 sklearn-pandas
 numpy==1.25.2
-dcm2niix==1.0.20220715
+git+https://github.com/rordenlab/dcm2niix.git