Code changes

README.md

@@ -36,29 +36,33 @@ pip install -r requirements.txt
 # this script loads the radiata-ai/brain-structure dataset from Hugging Face
 python create_csv.py
 
-mkdir pca_cache
 mkdir pca_output
 
 # train the model
-nohup python train_brain2vec_PCA.py --inputs_csv inputs.csv --output_dir ./pca_output --pca_type standard --n_components 1200 > train_log.txt 2>&1 &
+nohup python train_brain2vec_PCA.py \
+    --inputs_csv inputs.csv \
+    --output_dir ./pca_output \
+    --pca_type standard \
+    --n_components 1200 \
+    > train_log.txt 2>&1 &
 
 # model inference
-    python inference_brain2vec_PCA.py \
-        --pca_model /path/to/pca_model.joblib \
-        --input_images /path/to/img1.nii.gz /path/to/img2.nii.gz \
-        --output_dir /path/to/out
+python inference_brain2vec_PCA.py \
+    --pca_model /path/to/pca_model.joblib \
+    --input_images /path/to/img1.nii.gz /path/to/img2.nii.gz \
+    --output_dir /path/to/out
     
 # or if you have a CSV with image paths:
-    python inference_brain2vec_PCA.py \
-        --pca_model /path/to/pca_model.joblib \
-        --csv_input /path/to/images.csv \
-        --output_dir /path/to/out
+python inference_brain2vec_PCA.py \
+    --pca_model /path/to/pca_model.joblib \
+    --csv_input /path/to/input.csv \
+    --output_dir /path/to/out
 ```
 
 # Methods
 Input scan image dimensions are 113x137x113, 1.5mm^3 resolution, aligned to MNI152 space (see [radiata-ai/brain-structure](https://huggingface.co/datasets/radiata-ai/brain-structure)).  
 
-The image transform crops to 80 x 96 x 80, 2mm^3 resolution, and scales image intensity to range [0,1].  
+The image transform crops to 80 x 96 x 80, 2mm^3 resolution, and scales image intensity to range [0,1]. Images are flattened to 614400-length 1D vectors.
 
 PCA is performed using [sklearn.decomposition.PCA](https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html).  
 

inference_brain2vec_PCA.py

@@ -18,7 +18,7 @@ Or, if you have a CSV with image paths:
 
     python inference_brain2vec_PCA.py \
         --pca_model /path/to/pca_model.joblib \
-        --csv_input /path/to/images.csv \
+        --csv_input /path/to/input.csv \
         --output_dir /path/to/out
 """