Missing utils file[skip ci]

.gitignore

@@ -7,3 +7,8 @@ venv/
 *.ini
 *__pycache__/
 *.DS_Store
+*.json
+*.onnx
+*.xml
+*.txt
+*.obj

AeroPath/utils.py

@@ -0,0 +1,67 @@
+import nibabel as nib
+import numpy as np
+from nibabel.processing import resample_to_output
+from skimage.measure import marching_cubes
+
+
+def load_ct_to_numpy(data_path):
+    if type(data_path) != str:
+        data_path = data_path.name
+
+    image = nib.load(data_path)
+    resampled = resample_to_output(image, None, order=0)
+    data = resampled.get_fdata()
+
+    data = np.rot90(data, k=1, axes=(0, 1))
+
+    data[data < -1024] = -1024
+    data[data > 1024] = 1024
+
+    data = data - np.amin(data)
+    data = data / np.amax(data) * 255
+    data = data.astype("uint8")
+
+    print(data.shape)
+    return [data[..., i] for i in range(data.shape[-1])]
+
+
+def load_pred_volume_to_numpy(data_path):
+    if type(data_path) != str:
+        data_path = data_path.name
+
+    image = nib.load(data_path)
+    resampled = resample_to_output(image, None, order=0)
+    data = resampled.get_fdata()
+
+    data = np.rot90(data, k=1, axes=(0, 1))
+
+    data[data > 0] = 1
+    data = data.astype("uint8")
+
+    print(data.shape)
+    return [data[..., i] for i in range(data.shape[-1])]
+
+
+def nifti_to_glb(path, output="prediction.obj"):
+    # load NIFTI into numpy array
+    image = nib.load(path)
+    resampled = resample_to_output(image, [1, 1, 1], order=1)
+    data = resampled.get_fdata().astype("uint8")
+
+    # extract surface
+    verts, faces, normals, values = marching_cubes(data, 0)
+    faces += 1
+
+    with open(output, "w") as thefile:
+        for item in verts:
+            thefile.write("v {0} {1} {2}\n".format(item[0], item[1], item[2]))
+
+        for item in normals:
+            thefile.write("vn {0} {1} {2}\n".format(item[0], item[1], item[2]))
+
+        for item in faces:
+            thefile.write(
+                "f {0}//{0} {1}//{1} {2}//{2}\n".format(
+                    item[0], item[1], item[2]
+                )
+            )