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README.md

@@ -29,15 +29,12 @@ Our methods emphasize **robust image synthesis**, **reproducible pipelines**, an
   Contains all necessary files to build and run the Docker image for **Task 2** (CBCT → sCT).  
   - `process.py`: Script that performs inference, converting CBCT images into synthetic CT (sCT).  
 
-- **Normalization Config Files**  
-  - `260_gt_nnUNetResEncUNetLPlans.json`: Normalization configuration for the **Abdomen** region.  
-  - `262_gt_nnUNetResEncUNetLPlans.json`: Normalization configuration for the **Head & Neck** region.  
-  - `266_gt_nnUNetResEncUNetLPlans.json`: Normalization configuration for the **Thorax** region.  
+- **`Normalization Config Files`**  
+  - `260_gt_nnUNetResEncUNetLPlans.json/540_gt_nnUNetResEncUNetLPlans.json`: Normalization configuration for the **Abdomen** region.  
+  - `262_gt_nnUNetResEncUNetLPlans.json/542_gt_nnUNetResEncUNetLPlans.json`: Normalization configuration for the **Head & Neck** region.  
+  - `264_gt_nnUNetResEncUNetLPlans.json/544_gt_nnUNetResEncUNetLPlans.json`: Normalization configuration for the **Thorax** region.  
   These files are essential for inverse normalization, ensuring that the synthesized CT intensities are mapped back to their correct clinical ranges.  
 
-- **`nnunet_results`**  
-  You also need to place your **trained models** under the `nnunet_results/` directory so that inference can correctly locate and load them.  
-  
 - **`Dockerfile`**  
   Defines all steps and dependencies needed to build the Docker image. It ensures reproducibility and consistency across environments.  
 
@@ -58,7 +55,8 @@ Our methods emphasize **robust image synthesis**, **reproducible pipelines**, an
 
 
 ## 🚀 Getting Started
-
+- **`nnunet_results`**  
+  Before starting inference, you also need to create a folder called `nnunet_results/` in docker_task_1/docker_task_2 and place your **trained models** under the `nnunet_results/` directory so that inference can correctly locate and load them.  
 ### 1. Build the Docker Image
 ```bash
 cd docker_task_1

docker_task_1/Dockerfile

@@ -27,13 +27,15 @@ COPY --chown=algorithm:algorithm requirements.txt /opt/algorithm/
 RUN python -m pip install --user -r requirements.txt
 COPY --chown=algorithm:algorithm nnsyn /opt/algorithm/nnsyn
 RUN cd /opt/algorithm/nnsyn && python -m pip install --user -e .
-
+RUN mkdir -p /opt/algorithm/nnunet_raw \
+    /opt/algorithm/nnunet_preprocessed \
+    && chown -R algorithm:algorithm /opt/algorithm/nnunet_raw /opt/algorithm/nnunet_preprocessed
 COPY --chown=algorithm:algorithm .env /opt/algorithm/
 COPY --chown=algorithm:algorithm process.py /opt/algorithm/
 COPY --chown=algorithm:algorithm base_algorithm.py /opt/algorithm/
-COPY --chown=algorithm:algorithm nnunet_preprocessed/ /opt/algorithm/nnunet_preprocessed
-COPY --chown=algorithm:algorithm nnunet_raw/ /opt/algorithm/nnunet_raw
-# COPY --chown=algorithm:algorithm nnunet_results/ /opt/algorithm/nnunet_results
+# COPY --chown=algorithm:algorithm nnunet_preprocessed/ /opt/algorithm/nnunet_preprocessed
+# COPY --chown=algorithm:algorithm nnunet_raw/ /opt/algorithm/nnunet_raw
+COPY --chown=algorithm:algorithm nnunet_results/ /opt/algorithm/nnunet_results
 COPY --chown=algorithm:algorithm 260_gt_nnUNetResEncUNetLPlans.json /opt/algorithm/
 COPY --chown=algorithm:algorithm 262_gt_nnUNetResEncUNetLPlans.json /opt/algorithm/
 COPY --chown=algorithm:algorithm 264_gt_nnUNetResEncUNetLPlans.json /opt/algorithm/

docker_task_2/Dockerfile

@@ -21,7 +21,12 @@ ENV PATH="/home/algorithm/.local/bin:${PATH}"
 # ENV PYTHONPATH="/opt/algorithm/nnUNetv2:$PYTHONPATH"
 
 RUN python -m pip install --user -U pip
-
+RUN mkdir -p /opt/algorithm/nnunet_raw \
+    /opt/algorithm/nnunet_preprocessed \
+    && chown -R algorithm:algorithm /opt/algorithm/nnunet_raw /opt/algorithm/nnunet_preprocessed 
+COPY --chown=algorithm:algorithm .env /opt/algorithm/
+COPY --chown=algorithm:algorithm process.py /opt/algorithm/
+COPY --chown=algorithm:algorithm base_algorithm.py /opt/algorithm/
 
 COPY --chown=algorithm:algorithm requirements.txt /opt/algorithm/
 RUN python -m pip install --user -r requirements.txt
@@ -31,9 +36,9 @@ RUN cd /opt/algorithm/nnsyn && python -m pip install --user -e .
 COPY --chown=algorithm:algorithm .env /opt/algorithm/
 COPY --chown=algorithm:algorithm process.py /opt/algorithm/
 COPY --chown=algorithm:algorithm base_algorithm.py /opt/algorithm/
-COPY --chown=algorithm:algorithm nnunet_preprocessed/ /opt/algorithm/nnunet_preprocessed
-COPY --chown=algorithm:algorithm nnunet_raw/ /opt/algorithm/nnunet_raw
-# COPY --chown=algorithm:algorithm nnunet_results/ /opt/algorithm/nnunet_results
+# COPY --chown=algorithm:algorithm nnunet_preprocessed/ /opt/algorithm/nnunet_preprocessed
+# COPY --chown=algorithm:algorithm nnunet_raw/ /opt/algorithm/nnunet_raw
+COPY --chown=algorithm:algorithm nnunet_results/ /opt/algorithm/nnunet_results
 COPY --chown=algorithm:algorithm 540_gt_nnUNetResEncUNetLPlans.json /opt/algorithm/
 COPY --chown=algorithm:algorithm 542_gt_nnUNetResEncUNetLPlans.json /opt/algorithm/
 COPY --chown=algorithm:algorithm 544_gt_nnUNetResEncUNetLPlans.json /opt/algorithm/