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docs/docs/configuration/custom_classification/object_classification.md
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@ -33,9 +33,9 @@ For object classification:
- Example: `cat` → `Leo`, `Charlie`, `None`. - Example: `cat` → `Leo`, `Charlie`, `None`.
- **Attribute**: - **Attribute**:
- Added as metadata to the object (visible in /events): `<model_name>: <predicted_value>`. - Added as metadata to the object, visible in the Tracked Object Details pane in Explore, `frigate/events` MQTT messages, and the HTTP API response as `<model_name>: <predicted_value>`.
- Ideal when multiple attributes can coexist independently. - Ideal when multiple attributes can coexist independently.
- Example: Detecting if a `person` in a construction yard is wearing a helmet or not. - Example: Detecting if a `person` in a construction yard is wearing a helmet or not, and if they are wearing a yellow vest or not.
:::note :::note
@ -81,6 +81,8 @@ classification:
classification_type: sub_label # or: attribute classification_type: sub_label # or: attribute
``` ```
An optional config, `save_attempts`, can be set as a key under the model name. This defines the number of classification attempts to save in the Recent Classifications tab. For object classification models, the default is 200.
## Training the model ## Training the model
Creating and training the model is done within the Frigate UI using the `Classification` page. The process consists of two steps: Creating and training the model is done within the Frigate UI using the `Classification` page. The process consists of two steps:
@ -89,6 +91,8 @@ Creating and training the model is done within the Frigate UI using the `Classif
Enter a name for your model, select the object label to classify (e.g., `person`, `dog`, `car`), choose the classification type (sub label or attribute), and define your classes. Include a `none` class for objects that don't fit any specific category. Enter a name for your model, select the object label to classify (e.g., `person`, `dog`, `car`), choose the classification type (sub label or attribute), and define your classes. Include a `none` class for objects that don't fit any specific category.
For example: To classify your two cats, create a model named "Our Cats" and create two classes, "Charlie" and "Leo". Create a third class, "none", for other neighborhood cats that are not your own.
### Step 2: Assign Training Examples ### Step 2: Assign Training Examples
The system will automatically generate example images from detected objects matching your selected label. You'll be guided through each class one at a time to select which images represent that class. Any images not assigned to a specific class will automatically be assigned to `none` when you complete the last class. Once all images are processed, training will begin automatically. The system will automatically generate example images from detected objects matching your selected label. You'll be guided through each class one at a time to select which images represent that class. Any images not assigned to a specific class will automatically be assigned to `none` when you complete the last class. Once all images are processed, training will begin automatically.

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docs/docs/configuration/custom_classification/state_classification.md
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@ -48,6 +48,8 @@ classification:
crop: [0, 180, 220, 400] crop: [0, 180, 220, 400]
``` ```
An optional config, `save_attempts`, can be set as a key under the model name. This defines the number of classification attempts to save in the Recent Classifications tab. For state classification models, the default is 100.
## Training the model ## Training the model
Creating and training the model is done within the Frigate UI using the `Classification` page. The process consists of three steps: Creating and training the model is done within the Frigate UI using the `Classification` page. The process consists of three steps: