Update README_TIMELINE_LABELS.md

update example labeling configs
HumanSignal · Sep 17, 2024 · 8a35e17 · 8a35e17
1 parent 2ee27d5
commit 8a35e17
Showing 1 changed file with 23 additions and 17 deletions.
diff --git a/label_studio_ml/examples/yolo/README_TIMELINE_LABELS.md b/label_studio_ml/examples/yolo/README_TIMELINE_LABELS.md
@@ -81,10 +81,13 @@ In the simple mode, the model uses pre-trained YOLO classes to generate predicti
 - **Example**:
 
   ```xml
-  <TimelineLabels name="label" toName="video" model_trainable="false">
-    <Label value="Ball" predicted_values="soccer_ball"/>
-    <Label value="tiger_shark" />
-  </TimelineLabels>
+  <View>
+    <Video name="video" value="$video" height="700" timelineHeight="200" frameRate="25.0" />
+    <TimelineLabels name="label" toName="video" model_trainable="false">
+      <Label value="Ball" predicted_values="soccer_ball"/>
+      <Label value="tiger_shark" />
+    </TimelineLabels>
+  </View>
   ```
 
 ### Trainable Mode
@@ -107,18 +110,21 @@ so it requires about 10-20 well-annotated videos 500 frames each (~20 seconds) t
 **Example**:
 
 ```xml
-<TimelineLabels name="label" toName="video"
-                model_trainable="true"
-                model_classifier_epochs="1000"
-                model_classifier_sequence_size="16"
-                model_classifier_hidden_size="32"
-                model_classifier_num_layers="1"
-                model_classifier_f1_threshold="0.95"
-                model_classifier_accuracy_threshold="0.99"
-                model_score_threshold="0.5">
-  <Label value="Ball in frame"/>
-  <Label value="Ball touch"/>
-</TimelineLabels>
+<View>
+    <Video name="video" value="$video" height="700" timelineHeight="200" frameRate="25.0" />
+    <TimelineLabels name="label" toName="video"
+                    model_trainable="true"
+                    model_classifier_epochs="1000"
+                    model_classifier_sequence_size="16"
+                    model_classifier_hidden_size="32"
+                    model_classifier_num_layers="1"
+                    model_classifier_f1_threshold="0.95"
+                    model_classifier_accuracy_threshold="0.99"
+                    model_score_threshold="0.5">
+      <Label value="Ball in frame"/>
+      <Label value="Ball touch"/>
+    </TimelineLabels>
+</View>
 ```
 
 ## How the trainable model works
@@ -502,4 +508,4 @@ The TimelineLabels ML backend integrates seamlessly with Label Studio to provide
 
 Understanding the class hierarchies and method flows is crucial for developers looking to extend or modify the backend. By following the starting points and execution flows outlined in this guide, developers can navigate the codebase more effectively and implement custom features or optimizations.
 
-**Note**: For further development or contributions, please refer to the [`README_DEVELOP.md`](./README_DEVELOP.md) file, which provides additional guidelines and architectural details.
+**Note**: For further development or contributions, please refer to the [`README_DEVELOP.md`](./README_DEVELOP.md) file, which provides additional guidelines and architectural details.