save

scripts/get_error.py

@@ -8,12 +8,13 @@ parser = argparse.ArgumentParser(description='')
 parser.add_argument('--name', type=str)
 parser.add_argument('--config', type=str)
 parser.add_argument('--debug', action='store_true')
-parser.add_argument('--iteration', type=str, default='')
+parser.add_argument('--iteration', type=str, default='190000')
 parser.add_argument('-g', '--gpu', type=str)
+parser.add_argument('-a', '--all', action='store_true')
 args = vars(parser.parse_args())
 
 if args['debug']:
-    from configs.iccvw.pyr_64_128_cape_f_2 import config_1
+    from configs.iccvw.pyr_64_128_256_512_cape_f_e2e import config as config_1
 else:
     config_module = importlib.import_module(args['config'])
     config_1 = config_module.config
@@ -32,8 +33,14 @@ from data.utils import Frame
 
 
 def calculate():
-    errors = dict()
-    errors_mean = dict()
+    all_levels = args['all']
+    if all_levels:
+        errors = {0: dict(), 1: dict(), 2: dict(), 3: dict()}
+        errors_mean = {0: dict(), 1: dict(), 2: dict(), 3: dict()}
+    else:
+        errors = dict()
+        errors_mean = dict()
+
 
     with open(f'{results_folder}/errors/{name}.csv', 'r') as f:
         lines = f.readlines()
@@ -41,18 +48,31 @@ def calculate():
     for line in lines:
         line = line.split(',')
         category = line[2]
-        if category not in errors:
-            errors[category] = []
-        errors[category].append(float(line[3]))
+        if all_levels:
+            level = int(line[3][-1])
+            if category not in errors:
+                errors[level][category] = []
+            errors[level][category].append(float(line[4]))
+        else:
+            if category not in errors:
+                errors[category] = []
+            errors[category].append(float(line[3]))
 
-    for category in errors:
-        errors_mean[category] = np.mean(errors[category])
+    if all_levels:
+        for i in range(4):
+            for category in errors[i]:
+                errors_mean[i][category] = round(np.mean(errors[i][category]), 5)
+            print(f'Level {i}: {errors_mean[i]}')
 
-    print(errors_mean) 
+            mean = np.mean(list(errors_mean[i].values()))
+            print(f'Final error level {i}: {mean}')
+    else:
+        for category in errors:
+            errors_mean[category] = round(np.mean(errors[category]), 5)
+        print(errors_mean) 
 
-    mean = np.mean(list(errors_mean.values()))
-
-    print(f'Final error: {mean}')
+        mean = np.mean(list(errors_mean.values()))
+        print(f'Final error: {mean}')