mod

cfg/config.yml

@@ -22,4 +22,4 @@ model_params:
   num_of_nonzero: 3  # number of nonzero (default: 3)
   cutoff_edge_width: 2
   num_of_ch: 896  # number of channels used for anomaly detection (1<=num_of_ch<=896)
-  output_npy: True
+  output_npy: False

cfg/sample_config.yml

@@ -22,4 +22,4 @@ model_params:
   num_of_nonzero: 3  # number of nonzero (default: 3)
   cutoff_edge_width: 2
   num_of_ch: 100  # number of channels used for anomaly detection (1<=num_of_ch<=896)
-  output_npy: True
+  output_npy: False

src/dataset_test.py

@@ -22,7 +22,7 @@ class TestDatasetandDataLoader(unittest.TestCase):
 
     def test_dataset(self):
         self.assertEqual(len(self.mvtec_dataset), 2)
-        self.assertEqual(len(self.mvtec_dataset[0]), 2)
+        self.assertEqual(len(self.mvtec_dataset[0]), 3)
 
     def test_dataloader(self):
         self.assertEqual(len(self.dataloader), 2)

src/models_test.py

@@ -18,13 +18,22 @@ class TestCalculateScore(unittest.TestCase):
 
     model = models.SparseCodingWithMultiDict([], model_params)
 
+    def output_np_array(self):
+        batch_path = "test"
+        batch_name = "sample.png"
+        f_diff = np.ones([1, 10, 10])
+        self.model.output_np_array(batch_path, batch_name, f_diff)
+        self.assertTrue(os.path.exists("test/sample.npy"))
+        shutil.rmtree("test")
+
     def test_output_image(self):
-        is_positive = True
+        batch_path = "good"
         batch_name = "image.png"
         ch_err = np.ones([896])
         output_img = np.zeros([10, 10, 3])
-        self.model.output_image(is_positive, batch_name, ch_err, output_img)
-        self.assertTrue(os.path.exists("visualized_results/pos/image-896.png"))
+        self.model.output_image(batch_path, batch_name, ch_err, output_img)
+        self.assertTrue(os.path.exists(
+            "visualized_results/good/image-896.png"))
         shutil.rmtree("visualized_results")
 
     def test_calclate_ssim(self):