Add output path to LesionsAnalyzer

aI-lab-glider · Feb 13, 2022 · 5c500de · 5c500de
1 parent 182b35a
commit 5c500de
Show file tree

Hide file tree

Showing 4 changed files with 12 additions and 11 deletions.
diff --git a/bayesian_cnn_prometheus/analysis/analyse_lesions.py b/bayesian_cnn_prometheus/analysis/analyse_lesions.py
@@ -10,6 +10,7 @@ def analyse_lesions():
     model_path = sys.argv[1]
     config_path = sys.argv[2]
     input_path = sys.argv[3]
+    output_path = sys.argv[4]
 
     patients_to_analysis = [3, 4, 5, 6, 8, 10, 11, 14, 17, 21, 26, 27, 29, 30, 32, 34, 35, 36, 37, 39, 41]
 
@@ -19,7 +20,7 @@ def analyse_lesions():
         stride=model_config['preprocessing']['create_chunks']['stride'],
         mc_sample=model_config['mc_samples'])
 
-    lesions_analyzer = LesionsAnalyzer(model_path, input_path, prediction_options, patients_to_analysis)
+    lesions_analyzer = LesionsAnalyzer(model_path, input_path, prediction_options, patients_to_analysis, output_path)
     lesions_analyzer.run_analysis()
 
 

diff --git a/bayesian_cnn_prometheus/analysis/lesions_analyzer.py b/bayesian_cnn_prometheus/analysis/lesions_analyzer.py
@@ -16,18 +16,19 @@
 
 class LesionsAnalyzer:
     def __init__(self, model_path: str, input_path: str, prediction_options: PredictionOptions,
-                 patients_to_analysis: List[int] = None):
+                 patients_to_analysis: List[int] = None, output_path: str = None):
         """
         Creates LesionsAnalyzer instance.
         :param model_path: path to the model in h5 form
         :param input_path: path to the directory with images, lesions and segmentations labels
         :param prediction_options: parameters for prediction
         :param patients_to_analysis: indices of patients to perform analysis on them, if None - every patient
         in the input dir will be analyzed
+        :param output_path: path to the dir where output should be saved
         """
         self.model_path = model_path
         self.input_path = input_path
-        self.output_path = os.path.join(input_path, Paths.RESULTS_DIR)
+        self.output_path = output_path or os.path.join(input_path, Paths.RESULTS_DIR)
         self.prediction_options = prediction_options
         self.patients_to_analysis = patients_to_analysis
         self.model_evaluator = BayesianModelEvaluator(self.model_path, prediction_options.chunk_size)
@@ -36,7 +37,7 @@ def __init__(self, model_path: str, input_path: str, prediction_options: Predict
 
     def run_analysis(self):
         for image_path in tqdm(glob.glob(os.path.join(self.input_path, Paths.IMAGES_DIR, '*.nii.gz'))):
-            patient_idx = get_patient_index(image_path)
+            patient_idx = int(get_patient_index(image_path))
 
             if self.patients_to_analysis:
                 if patient_idx not in self.patients_to_analysis:
@@ -47,7 +48,7 @@ def run_analysis(self):
                                              .format(f'{patient_idx:0>4}', 'nii.gz'))
             mask_path = os.path.join(self.input_path, Paths.MASKS_DIR,
                                      str(Paths.MASK_FILE_PATTERN).format(f'{patient_idx:0>4}', 'nii.gz'))
-            variance_path = os.path.join(self.input_path, Paths.RESULTS_DIR,
+            variance_path = os.path.join(self.output_path,
                                          str(Paths.VARIANCE_FILE_PATTERN).format(f'{patient_idx:0>4}', 'nii.gz'))
 
             nifti = nib.load(image_path)

diff --git a/bayesian_cnn_prometheus/evaluation/bayesian_model_evaluator.py b/bayesian_cnn_prometheus/evaluation/bayesian_model_evaluator.py
@@ -138,7 +138,6 @@ def binarize_prediction(self, mean_prediction: np.ndarray) -> np.ndarray:
         mean_prediction = mean_prediction.copy()
         mean_prediction = mean_prediction * 255
         mean_prediction = mean_prediction.astype(np.uint8)
-        max_value = np.max(mean_prediction)
 
         for i in range(mean_prediction.shape[0]):
             im_slice = mean_prediction[i]

diff --git a/bayesian_cnn_prometheus/run_training_for_experiments.py b/bayesian_cnn_prometheus/run_training_for_experiments.py
@@ -12,7 +12,7 @@
 
 from bayesian_cnn_prometheus.constants import Paths
 
-EXPERIMENTS_DIR = Path('experiments') / 'control_group'
+EXPERIMENTS_DIR = Path('experiments_hp50')
 EXPERIMENTS_DIR = str(EXPERIMENTS_DIR)
 
 
@@ -144,14 +144,14 @@ def parse():
         'name': 'chunk_change',
         'overrides': [
             {
-                'alias': 's',
+                'alias': 'cs',
                 'key': 'preprocessing.create_chunks.chunk_size',
-                'values': [[128, 16, 16]]
+                'values': [[64, 32, 32]]
             },
             {
-                'alias': 'cs',
+                'alias': 's',
                 'key': 'preprocessing.create_chunks.stride',
-                'values': [[64, 16, 16]]
+                'values': [[64, 32, 32]]
             }
         ],
     }