d

RobinNet/threshunetpred_gts.py

@@ -21,7 +21,7 @@ def main():
 
     root = tk.Tk()
     root.withdraw()
-    file_path = filedialog.askopenfilename(initialdir="saves/mr_unet_cv_ctthresh")
+    file_path = filedialog.askopenfilename(initialdir="saves/unet_cv_thresh")
     file_path = file_path[:-9]
     print(file_path)
 
@@ -61,10 +61,8 @@ def main():
         print('GT Type:', gt_type)
 
         ### Load test patient
-        if gt_type == "thresh" or gt_type == "ctthresh_gt":
-            img_path = "data/npy_thresh/"
-        else:
-            img_path = "data/npy/"
+        img_path = "data/npy_thresh/"
+
         full_list = os.listdir(img_path)
         seg_list = os.listdir("data/npy/")
 
@@ -72,16 +70,15 @@ def main():
         GT_img_list = []
         ytrue_img_list = []
         # thresh_img_list = []
-        if "mr" in save_path:
-            for elem in full_list:
-                if elem.endswith("ct.gipl.npy") and (elem.startswith('P' + str(test_patients[0]).zfill(2)) or elem.startswith('P' + str(test_patients[1]).zfill(2))):
-                    X_img_list.append(elem)
+        for elem in full_list:
+            if elem.endswith("ct.gipl.npy") and (elem.startswith('P' + str(test_patients[0]).zfill(2)) or elem.startswith('P' + str(test_patients[1]).zfill(2))):
+                X_img_list.append(elem)
 
-                elif elem.endswith("250_thresh.gipl.npy") and (elem.startswith('P' + str(test_patients[0]).zfill(2)) or elem.startswith('P' + str(test_patients[1]).zfill(2))):
-                    GT_img_list.append(elem)
-            for elem in seg_list:
-                if elem.endswith("seg.gipl.npy") and (elem.startswith('P' + str(test_patients[0]).zfill(2)) or elem.startswith('P' + str(test_patients[1]).zfill(2))):
-                    ytrue_img_list.append(elem)
+            elif elem.endswith("250_thresh.gipl.npy") and (elem.startswith('P' + str(test_patients[0]).zfill(2)) or elem.startswith('P' + str(test_patients[1]).zfill(2))):
+                GT_img_list.append(elem)
+        for elem in seg_list:
+            if elem.endswith("seg.gipl.npy") and (elem.startswith('P' + str(test_patients[0]).zfill(2)) or elem.startswith('P' + str(test_patients[1]).zfill(2))):
+                ytrue_img_list.append(elem)
 
 
         list.sort(X_img_list)
@@ -98,6 +95,7 @@ def main():
             os.makedirs(img_savepath)
 
         for j in range(2):
+            print(img_path + X_img_list[j])
             X_img_npys = np.load(img_path + X_img_list[j])
             GT_img_npys = np.load(img_path + GT_img_list[j])
             ytrue_img_npys = np.load(img_path + ytrue_img_list[j])
@@ -181,6 +179,8 @@ def main():
 
             if npys3d:
                 y_pred3d = np.flip(y_pred3d)
+                filename = "P" + str(TP_num).zfill(2)
+                y_pred3d = cut_mr_ctunetpred(filename, y_pred3d)
                 #np.save(img_savepath + "P" + str(TP_num).zfill(2) + "_pred3D", y_pred3d)
                 np.save("data/npy_thresh/" + "P" + str(TP_num).zfill(2) + "_mr_ctunetpred.gipl", y_pred3d)
                 print("ypred shape: ", np.shape(y_pred3d))

RobinNet/utils/other_functions.py

@@ -95,6 +95,48 @@ def save_val_prediction(pred, save_path, val_patient):
         pred = np.append(npyload, pred, axis=0)
     np.save(str(valsavepath)+str(val_patient), pred)
 
+def cut_mr_ctunetpred(filename, patient_array):
+    if filename.startswith('P01'):
+        corr_patient_array = patient_array[2:27, :, :]
+
+    elif filename.startswith('P02'):
+        corr_patient_array = patient_array[5:, :, :]
+
+    elif filename.startswith('P03'):
+        corr_patient_array = patient_array[10:29, :, :]
+
+    elif filename.startswith('P04'):
+        corr_patient_array = patient_array[9:, :, :]
+
+    elif filename.startswith('P05'):
+        corr_patient_array = patient_array[5:31, :, :]
+
+    elif filename.startswith('P06'):
+        corr_patient_array = patient_array[7:, :, :]
+
+    elif filename.startswith('P07'):
+        corr_patient_array = patient_array[2:, :, :]
+
+    elif filename.startswith('P08'):
+        corr_patient_array = patient_array[3:, :, :]
+
+    elif filename.startswith('P09'):
+        corr_patient_array = patient_array[1:, :, :]
+
+    #elif filename.startswith('P11'):
+     #   corr_patient_array = patient_array[:, :, :]
+
+    elif filename.startswith('P12'):
+        corr_patient_array = patient_array[:36, :, :]
+
+    elif filename.startswith('P17'):
+        corr_patient_array = patient_array[6:, :, :]
+
+    else:
+        corr_patient_array = patient_array
+
+    corr_patient_array = np.flip(corr_patient_array)
+    return corr_patient_array