merged

Author: tfunck

brainbuilder/interp/acqvolume.py

@@ -5,7 +5,6 @@
 
 import numpy as np
 import pandas as pd
-import stripy as stripy
 from scipy.interpolate import interp1d
 from scipy.ndimage import gaussian_filter, label
 

brainbuilder/interp/surfinterp.py

@@ -6,7 +6,6 @@
 import nibabel as nb_surf
 import numpy as np
 import pandas as pd
-import stripy as stripy
 from joblib import Parallel, delayed
 
 import brainbuilder.utils.ants_nibabel as nib
@@ -527,6 +526,7 @@ def interpolate_over_surface(
     )
 
     # create mesh data structure
+    import stripy as stripy
     mesh = stripy.sTriangulation(lons_src, lats_src)
 
     lats, lons = spherical_coords[:, 1] - np.pi / 2, spherical_coords[:, 2]

brainbuilder/qc/validate_interp_error.py

@@ -726,8 +726,6 @@ def validate_interp_error(
     output_sect_info_csv = f"{output_dir}/validate_interp_error_sect_info.csv"
     sect_info = pd.read_csv(sect_info_csv)
     chunk_info = pd.read_csv(chunk_info_csv)
-    print(sect_info["img"].values[0:10])
-    exit(0)
 
     # Only keep highest resolution in chunk_info
     chunk_info = chunk_info.loc[

brainbuilder/tests/generate_synthetic_data.py

@@ -82,6 +82,7 @@ def save_coronal_sections(input_fn:str, out_dir:str, raw_dir:str, sub:str, hemis
                 continue
 
             save_section(input_vol, y, affine, raw_sec_fn)
+            print(raw_sec_fn)
 
             row_dict = {
                 "raw": [raw_sec_fn],
@@ -135,18 +136,16 @@ def generate_synthetic_data(
     for dir_path in [out_dir, raw_dir]:
         os.makedirs(dir_path, exist_ok=True)
 
-
     save_coronal_sections(input_fn, out_dir, raw_dir, sub, hemisphere, chunk, ystep=ystep, clobber=clobber )
 
-
     chunk_info_df = pd.DataFrame(
         {
             "sub": [sub],
             "chunk": [chunk],
             "hemisphere": [hemisphere],
-            "pixel_size_0": [1],
-            "pixel_size_1": [1],
-            "section_thickness": [1],
+            "pixel_size_0": [1.0],
+            "pixel_size_1": [1.0],
+            "section_thickness": [1.0],
             "direction": ["caudal_to_rostral"],
         }
     )

brainbuilder/utils/validate_inputs.py

@@ -59,7 +59,7 @@ def val_func(x: Union[int, float, str]) -> bool:
                 return True
 
             if n_jobs is None:
-                n_jobs = int(cpu_count() / 2)
+                n_jobs = int(cpu_count() )
 
             validated_rows = Parallel(n_jobs=n_jobs)(
                 delayed(val_func)(var) for var in rows
@@ -124,6 +124,7 @@ def validate_dataframe(
             validated = column.validate_rows_in_column(
                 df[column.name].values, n_jobs=n_jobs
             )
+            print(column.name, validated)
             valid_columns.append(validated)
 
     valid_inputs = np.product(np.array(valid_columns))

docker/Dockerfile

@@ -0,0 +1,19 @@
+FROM tffunck/brainbuilder:base
+
+SHELL ["/bin/bash", "-c"]
+RUN cd /opt && \
+	rm -fr brainbuilder && \
+    git clone https://www.github.com/tfunck/brainbuilder &&\
+	cd brainbuilder &&\
+	/opt/bbenv/bin/pip3 install -r requirements.txt &&\
+	/opt/bbenv/bin/pip3 install . 
+
+# Create the entrypoint.sh script
+RUN echo '#!/bin/bash' > /opt/entrypoint.sh && \
+	echo 'source /opt/bbenv/bin/activate' >> /opt/entrypoint.sh && \
+	echo 'exec "$@"' >> /opt/entrypoint.sh
+
+# Make the script executable
+RUN chmod +x /opt/entrypoint.sh
+ENTRYPOINT ["/opt/entrypoint.sh"]
+RUN pwd

docker/base/Dockerfile

@@ -0,0 +1,27 @@
+FROM antsx/ants
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Install system dependencies
+RUN apt update && apt upgrade -y && \
+	apt-get install -y \
+        git \
+		curl\
+		python3 python3-dev python3-venv python3-pip\
+        python3-opencv \
+        libglib2.0-0 \
+		build-essential libssl-dev\
+		cmake
+
+# Install any python packages you need
+WORKDIR /opt
+
+RUN cd /opt && \
+	python3 -m venv bbenv &&\
+	git clone https://www.github.com/tfunck/brainbuilder && \
+	cd brainbuilder && \
+	/opt/bbenv/bin/pip3 install -r requirements.txt
+
+
+
+

docker/build.sh

@@ -0,0 +1 @@
+ docker build -t tffunck/brainbuilder:v.1 -t tffunck/brainbuilder:latest .

notebooks/tutorial.py

@@ -1,20 +1,27 @@
 # CELL 1
 from brainbuilder.tests.generate_synthetic_data import generate_synthetic_data
-   
+import os
+
+default_path = os.path.realpath(os.path.dirname(os.path.abspath(__file__))+'/../')+'/'
+
 generate_synthetic_data( 
-    input_fn = '../data/mni_icbm152_01_tal_nlin_asym_09c.nii.gz',
-    out_dir = '../data/mni152_test',
-    gm_surf_fn = '../data/MR1_gray_surface_R_81920.surf.gii',
-    wm_surf_fn = '../data/MR1_white_surface_R_81920.surf.gii',
-    clobber = False
+    input_fn = f'{default_path}data/mni_icbm152_01_tal_nlin_asym_09c.nii.gz',
+    out_dir = f'{default_path}data/mni152_test',
+    gm_surf_fn = f'{default_path}data/MR1_gray_surface_R_81920.surf.gii',
+    wm_surf_fn = f'{default_path}data/MR1_white_surface_R_81920.surf.gii',
+    clobber = True
     )
 
+
+def realpath(x) : return os.path.realpath(default_path+x)
+
 # CELL 2
 import pandas as pd
 
-sect_info_csv = "../data/mni152_test/sect_info.csv"
-chunk_info_csv = "../data/mni152_test/chunk_info.csv"
-hemi_info_csv = "../data/mni152_test/hemi_info.csv"
+sect_info_csv = f"{default_path}data/mni152_test/sect_info.csv"
+chunk_info_csv = f"{default_path}data/mni152_test/chunk_info.csv"
+hemi_info_csv = f"{default_path}data/mni152_test/hemi_info.csv"
+
 
 # Load the sect_info csv and visualize contents. Stores section-wise information
 print('Sect Info:')
@@ -43,6 +50,6 @@
         chunk_info_csv,
         sect_info_csv,
         [4, 3, 2, 1],
-        "tests/data/mni152_test_output/",
+        f"{default_path}/data/mni152_test_output/",
         clobber=False,
     )

requirements.txt

@@ -1,21 +1,18 @@
+numpy<2
 stripy
+scipy
 pandas
 h5py
-guppy3
 psutil
 statsmodels
 configparser
 scikit-learn
 scikit-image
 SimpleITK
 imageio
-keras
-pydot
 matplotlib
 nibabel
 seaborn
-torch
-torchvision
 antspyx
 pre-commit
 webcolors
@@ -24,5 +21,3 @@ pre-commit
 nnunet
 nnunetv2
 medpy
-numpy<2
-scipy