Script the pipeline =================== All gaze analysis pipeline objects are accessible from Python script. This could be particularly useful for realtime gaze interaction applications. ## Load ArFrame configuration from dictionary First of all, [ArFrame](../../../argaze.md/#argaze.ArFeatures.ArFrame) configuration can be loaded from a python dictionary. ```python from argaze import ArFeatures # Edit a dict with ArFrame configuration configuration = { "name": "My FullHD screen", "size": (1920, 1080), ... "gaze_movement_identifier": { ... }, "scan_path": { ... }, "scan_path_analyzers": { ... }, "heatmap": { ... }, "layers": { "MyLayer": { ... }, ... }, "image_parameters": { ... } } # Load ArFrame ar_frame = ArFeatures.ArFrame.from_dict(configuration) # Do something with ArFrame ... ``` ## Access to ArFrame and ArLayers attributes Then, once the configuration is loaded, it is possible to access to its attributes: [read ArFrame code reference](../../../argaze.md/#argaze.ArFeatures.ArFrame) to get a complete list of what is available. Thus, the [ArFrame.layers](../../../argaze.md/#argaze.ArFeatures.ArFrame) attribute allows to access each loaded layer and so, access to their attributes: [read ArLayer code reference](../../../argaze.md/#argaze.ArFeatures.ArLayer) to get a complete list of what is available. ```python from argaze import ArFeatures # Assuming the ArFrame is loaded ... # Iterate over each ArFrame layers for name, ar_layer in ar_frame.layers.items(): ... ``` ## Pipeline execution outputs [ArFrame.look](../../../argaze.md/#argaze.ArFeatures.ArFrame.look) method returns many data about pipeline execution. ```python # Assuming that timestamped gaze positions are available ... # Look ArFrame at a timestamped gaze position gaze_movement, scan_path_analysis, layers_analysis, execution_times, exception = ar_frame.look(timestamp, gaze_position) # Check if a gaze movement has been identified if gaze_movement.valid and gaze_movement.finished: # Do something with identified fixation if GazeFeatures.is_fixation(gaze_movement): ... # Do something with identified saccade elif GazeFeatures.is_saccade(gaze_movement): ... # Do something with scan path analysis for module, analysis in scan_path_analysis.items(): for data, value in analysis.items(): ... # Do something with each layer AOI scan path analysis for layer_name, layer_aoi_scan_path_analysis in layers_analysis.items(): for module, analysis in layer_aoi_scan_path_analysis.items(): for data, value in analysis.items(): ... # Do something with pipeline execution times ... # Do something with pipeline exception if exception: ... ``` Let's understand the meaning of each returned data. ### Gaze movement A [GazeMovement](../../../argaze.md/#argaze.GazeFeatures.GazeMovement) once it have been identified by [ArFrame.gaze_movement_identifier](../../../argaze.md/#argaze.ArFeatures.ArFrame) object from incoming consecutive timestamped gaze positions. If no gaze movement have been identified, it returns an [UnvalidGazeMovement](../../../argaze.md/#argaze.GazeFeatures.UnvalidGazeMovement). This could also be the current gaze movement if [ArFrame.filter_in_progress_identification](../../../argaze.md/#argaze.ArFeatures.ArFrame) attribute is false. In that case, the returned gaze movement *finished* flag is false. Then, the returned gaze movement type can be tested thanks to [GazeFeatures.is_fixation](../../../argaze.md/#argaze.GazeFeatures.is_fixation) and [GazeFeatures.is_saccade](../../../argaze.md/#argaze.GazeFeatures.is_saccade) functions. ### Scan path analysis A dictionary with all last scan path analysis if new scan step have been added to the [ArFrame.scan_path](../../../argaze.md/#argaze.ArFeatures.ArFrame) object. ### Layers analysis A dictionary with all layers AOI scan path analysis if new AOI scan step have been added to an [ArLayer.aoi_scan_path](../../../argaze.md/#argaze.ArFeatures.ArLayer) object. ### Execution times A dictionary with each pipeline step execution time. ### Exception A [python Exception](https://docs.python.org/3/tutorial/errors.html#exceptions) object raised during pipeline execution. ## Setup ArFrame image parameters [ArFrame.image](../../../argaze.md/#argaze.ArFeatures.ArFrame.image) method parameters can be configured thanks to a python dictionary. ```python # Assuming ArFrame is loaded ... # Edit a dict with ArFrame image parameters image_parameters = { "draw_scan_path": { ... }, "draw_layers": { "MyLayer": { ... } }, ... } # Pass image parameters to ArFrame ar_frame_image = ar_frame.image(**image_parameters) # Do something with ArFrame image ... ```