dMerge branch 'master' of https://fsstud.is.uni-due.de:8090/sjromuel/Masterarbeit

RobinNet/allModelsCreatePredNpys.py

@@ -22,26 +22,26 @@ def main():
     folds = ["12", "34", "56", "78", "910", "1112", "1314", "1516"]
     folder_path = "finalResults/complete_"
     unet_models_paths = ["ctfgt2/unet_cv_ctfgt2/",
-                         "seg/unet_seg/",
+                         "seg/unet_cv_seg/",
                          "thresh/unet_cv_thresh/",
-                         "segmr/mr_unet_cv_ctsegmr/",
+                         "segmr/mr_unet_cv_segmr/",
                          "segmr/mr_unet_cv_ctseg/",
                          "segmr/mr_unet_cv_ctthresh/",
                          "segmr/mr_unet_cv_unetpred/"]
     cluster_models_paths = ["ctfgt2/ae_noclass_cv_ctfgt2/",
-                             "seg/ae_noclass_seg/",
+                             "seg/ae_noclass_cv_seg/",
                              "thresh/ae_noclass_cv_thresh/"]
     class_models_paths = ["ctfgt2/ae_class_cv_ctfgt2/",
-                         "seg/ae_class_seg/",
+                         "seg/ae_class_cv_seg/",
                          "thresh/ae_class_cv_thresh/"]
     clusterclass_models_paths = ["ctfgt2/ae_class_cv_ctfgt2/",
-                                 "seg/ae_class_seg/",
+                                 "seg/ae_class_cv_seg/",
                                  "thresh/ae_class_cv_thresh/"]
     modeltypes = ["Unet_", "Cluster_", "Class_", "Cluster_class_"]
 
     for modeltype in modeltypes:
         if modeltype == "Unet_": model_paths = unet_models_paths
-        elif modeltype == "Cluster_": model_paths == cluster_models_paths
+        elif modeltype == "Cluster_": model_paths = cluster_models_paths
         elif modeltype == "Class_": model_paths = class_models_paths
         elif modeltype == "Cluster_class_": model_paths = clusterclass_models_paths
 
@@ -155,9 +155,6 @@ def main():
                         X_img_npys = np.load(img_path + X_img_list[j*3])
                         GT_img_npys = np.load(img_path + GT_img_list[j*3])
                         ytrue_img_npys = np.load(img_path + ytrue_img_list[j*3])
-                        print(GT_img_list[j*3])
-                        print(GT_img_list[j * 3+1])
-                        print(GT_img_list[j * 3+2])
         
                         X_img_npys = np.append(X_img_npys, np.load(img_path + X_img_list[j * 3+1]), axis=0)
                         GT_img_npys = np.append(GT_img_npys, np.load(img_path + GT_img_list[j * 3+1]), axis=0)
@@ -258,4 +255,4 @@ def main():
           #####
 
 if __name__ == "__main__":
-    main()
\ No newline at end of file
+    main()

RobinNet/rerunModels.py

@@ -19,7 +19,7 @@ from nets.Unet import *
 
 def main():
     models = ["12", "34", "56", "78", "910", "1112", "1314", "1516"]
-    folder_path = "finalResults/complete_segmr/mr_unet_cv_ctthresh/"
+    folder_path = "finalResults/complete_segmr/mr_unet_cv_unetpred/"
     #modeltype = "Cluster_"
     #modeltype = "Class_"
     #modeltype = "Cluster_class_"