Fix issue in tutorial (#997)

* Fix issue in tutorial * Fix lint issue --------- Co-authored-by: Samet Akcay <[email protected]>
openvinotoolkit · Apr 6, 2023 · 3e9a109 · 3e9a109
1 parent 730bdb6
commit 3e9a109
Showing 1 changed file with 35 additions and 32 deletions.
diff --git a/docs/source/how_to_guides/train_custom_data.rst b/docs/source/how_to_guides/train_custom_data.rst
@@ -69,38 +69,41 @@ Let's choose `Padim algorithm <https://arxiv.org/pdf/2011.08785.pdf>`_, copy the
 
     # Replace the dataset configs with the following.
     dataset:
-    name: hazelnut
-    format: folder
-    root: ./datasets/Hazelnut_toy
-    normal_dir: good # name of the folder containing normal images.
-    abnormal_dir: colour # name of the folder containing abnormal images.
-    task: classification # classification or segmentation
-    mask_dir: null #optional
-    normal_test_dir: null # optional
-    extensions: null
-    split_ratio: 0.2  # normal images ratio to create a test split
-    seed: 0
-    image_size: 256
-    train_batch_size: 32
-    eval_batch_size: 32
-    num_workers: 8
-    transform_config:
-        train: null
-        eval: null
-    val_split_mode: from_test # determines how the validation set is created, options [same_as_test, from_test]
-    tiling:
-        apply: false
-        tile_size: null
-        stride: null
-        remove_border_count: 0
-        use_random_tiling: False
-        random_tile_count: 16
-
-    model:
-        name: padim
-        backbone: resnet18
-        layer:
-        - layer1
+        name: hazelnut
+        format: folder
+        root: ./datasets/hazelnut_toy
+        normal_dir: good # name of the folder containing normal images.
+        abnormal_dir: colour # name of the folder containing abnormal images.
+        task: classification # classification or segmentation
+        mask_dir: null #optional
+        normal_test_dir: null # optional
+        extensions: null
+        split_ratio: 0.2  # normal images ratio to create a test split
+        seed: 0
+        image_size: 256
+        train_batch_size: 32
+        eval_batch_size: 32
+        num_workers: 8
+        normalization: imagenet # data distribution to which the images will be normalized
+        test_split_mode: from_dir # options [from_dir, synthetic]
+        val_split_ratio: 0.5 # fraction of train/test images held out for validation (usage depends on val_split_mode)
+        transform_config:
+            train: null
+            eval: null
+        val_split_mode: from_test # determines how the validation set is created, options [same_as_test, from_test]
+        tiling:
+            apply: false
+            tile_size: null
+            stride: null
+            remove_border_count: 0
+            use_random_tiling: False
+            random_tile_count: 16
+
+        model:
+            name: padim
+            backbone: resnet18
+            layer:
+            - layer1
         ...