task conversion

app.py

@@ -2,28 +2,38 @@ import gradio as gr
 import subprocess
 import os
 import numpy as np
+from PIL import Image
 
 os.environ['data_raw'] = 'data_raw/'
 os.environ['nnUNet_raw_data_base'] = 'nnUNet_raw_data_base/'
 os.environ['nnUNet_preprocessed'] = 'nnUNet_preprocessed/'
 os.environ['RESULTS_FOLDER'] = 'calvingfronts/'
 
+model_path = 'Task500_Glacier_zonefronts'
 
 
 def run_front_detection(input_img):
-    input_img.save('data_raw/test.png')
+    image_gray = input_img.convert("L")
+    image_gray.save('data_raw/test.png')
     subprocess.run(
         ['python3', 'nnunet/dataset_conversion/Task500_Glacier_inference.py', '-data_percentage', '100', '-base',
          os.environ['data_raw']])
     cmd = [
         'python3', 'nnunet/inference/predict_simple.py',
-        '-i', os.path.join('$nnUNet_raw_data_base', 'nnUNet_raw_data/Task500_Glacier_zonefronts/imagesTs/'),
-        '-o', os.path.join('$RESULTS_FOLDER', 'fold_0'),
+        '-i', os.path.join(os.environ['nnUNet_raw_data_base'], 'nnUNet_raw_data/Task500_Glacier_zonefronts/imagesTs/'),
+        '-o', os.path.join(os.environ['RESULTS_FOLDER'], 'fold_0'),
         '-t', '500','-m','2d','-f','0','-p', 'nnUNetPlansv2.1', '-tr','nnUNetTrainerV2', '-model_folder_name',
-        '$model'
+        model_path
     ]
-    #subprocess.run(cmd)
-    #TODO remove files
+    subprocess.run(cmd)
+    subprocess.run(['python3', 'nnunet/dataset_conversion/Task500_Glacier_reverse.py', '-i',
+                    os.path.join(os.environ['RESULTS_FOLDER'], 'fold_0')])
 
-demo = gr.Interface(run_front_detection, gr.Image(type='pil'), "image")
+    os.remove('data_raw/test.png')
+    os.remove('nnUNet_raw_data_base/nnUNet_raw_data/Task500_Glacier_zonefronts/imagesTs/test_0000.nii.gz')
+
+    front = Image.open(os.path.join(os.environ['RESULTS_FOLDER'], 'tifs/test_front.png'))
+    return front
+
+demo = gr.Interface(run_front_detection, gr.Image(type='pil'), "image",interface_size=(1000, 1000))
 demo.launch()

nnunet/dataset_conversion/Task500_Glacier_inference.py

@@ -1,3 +1,4 @@
+from batchgenerators.utilities.file_and_folder_operations import *
 from nnunet.utilities.file_conversions import convert_2d_image_to_nifti
 from nnunet.paths import nnUNet_raw_data, preprocessing_output_dir
 from nnunet.dataset_conversion.utils import generate_dataset_json
@@ -10,73 +11,6 @@ import json
 from typing import List
 
 
-def subdirs(folder: str, join: bool = True, prefix: str = None, suffix: str = None, sort: bool = True) -> List[str]:
-    if join:
-        l = os.path.join
-    else:
-        l = lambda x, y: y
-    res = [l(folder, i) for i in os.listdir(folder) if os.path.isdir(os.path.join(folder, i))
-           and (prefix is None or i.startswith(prefix))
-           and (suffix is None or i.endswith(suffix))]
-    if sort:
-        res.sort()
-    return res
-
-
-def subfiles(folder: str, join: bool = True, prefix: str = None, suffix: str = None, sort: bool = True) -> List[str]:
-    if join:
-        l = os.path.join
-    else:
-        l = lambda x, y: y
-    res = [l(folder, i) for i in os.listdir(folder) if os.path.isfile(os.path.join(folder, i))
-           and (prefix is None or i.startswith(prefix))
-           and (suffix is None or i.endswith(suffix))]
-    if sort:
-        res.sort()
-    return res
-
-
-def nifti_files(folder: str, join: bool = True, sort: bool = True) -> List[str]:
-    return subfiles(folder, join=join, sort=sort, suffix='.nii.gz')
-
-
-def maybe_mkdir_p(directory: str) -> None:
-    os.makedirs(directory, exist_ok=True)
-
-
-def load_pickle(file: str, mode: str = 'rb'):
-    with open(file, mode) as f:
-        a = pickle.load(f)
-    return a
-
-
-def write_pickle(obj, file: str, mode: str = 'wb') -> None:
-    with open(file, mode) as f:
-        pickle.dump(obj, f)
-
-
-def load_json(file: str):
-    with open(file, 'r') as f:
-        a = json.load(f)
-    return a
-
-
-def save_json(obj, file: str, indent: int = 4, sort_keys: bool = True) -> None:
-    with open(file, 'w') as f:
-        json.dump(obj, f, sort_keys=sort_keys, indent=indent)
-
-
-def pardir(path: str):
-    return os.path.join(path, os.pardir)
-
-
-def split_path(path: str) -> List[str]:
-    """
-    splits at each separator. This is different from os.path.split which only splits at last separator
-    """
-    return path.split(os.sep)
-
-
 # I'm tired of typing these out
 join = os.path.join
 isdir = os.path.isdir

nnunet/dataset_conversion/Task500_Glacier_reverse.py

@@ -1,6 +1,7 @@
 import SimpleITK as sitk
 import argparse
 
+import imageio
 import numpy as np
 import torch
 import os
@@ -40,13 +41,17 @@ def main(input_folder):
             color_front = extract_front_from_zones(color_zone, 10)
             color_front[color_front==255] =1
 
-            output_path_zone = join(output_folder, file[:-len('.nii.gz')] + '_zone.tif')
-            output_path_front = join(output_folder, file[:-len('.nii.gz')] + '_front.tif')
+            output_path_zone = join(output_folder, file[:-len('.nii.gz')] + '_zone.png')
+            output_path_front = join(output_folder, file[:-len('.nii.gz')] + '_front.png')
 
+            imageio.imwrite(output_path_zone, color_zone)
+            imageio.imwrite(output_path_front, color_front)
+            """
             img_zone = Image.fromarray(color_zone)
             img_front = Image.fromarray(color_front)
             img_zone.save(output_path_zone)
             img_front.save(output_path_front)
+            """
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()

requirements.txt

@@ -18,4 +18,7 @@ astropy
 einops
 plotly
 imageio
-SimpleITK
+SimpleITK
+gradio
+torch
+MedPy