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diff --git a/docs/user_guide/gaze_analysis_pipeline/logging.md b/docs/user_guide/gaze_analysis_pipeline/logging.md deleted file mode 100644 index 6ef3a85..0000000 --- a/docs/user_guide/gaze_analysis_pipeline/logging.md +++ /dev/null @@ -1,152 +0,0 @@ -Record gaze analysis -================= - -[ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and [ArLayer](../../argaze.md/#argaze.ArFeatures.ArLayer) analysis can be recorded by registering observers to their **look** method. - -## Export gaze analysis to CSV file - -[ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and [ArLayer](../../argaze.md/#argaze.ArFeatures.ArLayer) have an *observers* attribute to enable pipeline execution recording. - -Here is an extract from the JSON ArFrame configuration file where recording is enabled for the [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and for one [ArLayer](../../argaze.md/#argaze.ArFeatures.ArLayer) by loaded classes from Python files: - -```json -{ - "name": "My FullHD screen", - "size": [1920, 1080], - "observers": { - "my_recorders.ScanPathAnalysisRecorder": { - "path": "./scan_path_metrics.csv" - }, - ... - "layers": { - "MyLayer": { - "observers": { - "my_recorders.AOIScanPathAnalysisRecorder": { - "path": "./aoi_scan_path_metrics.csv" - } - }, - ... - } - } -} -``` - -!!! note - [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and its [ArLayers](../../argaze.md/#argaze.ArFeatures.ArLayer) automatically notify **look** method observers after each call. - -Here is *my_recorders.py* file: - -```python -from argaze.utils import UtilsFeatures - -class ScanPathAnalysisRecorder(UtilsFeatures.FileWriter): - - def __init__(self, **kwargs): - - # Init FileWriter - super().__init__(**kwargs) - - # Edit hearder line - self.header = "Timestamp (ms)", "Duration (ms)", "Steps number" - - def on_look(self, timestamp, ar_frame, exception): - """Record scan path metrics""" - - if ar_frame.is_analysis_available(): - - analysis = ar_frame.analysis() - - data = ( - timestamp, - analysis['argaze.GazeAnalysis.Basic.ScanPathAnalyzer'].path_duration, - analysis['argaze.GazeAnalysis.Basic.ScanPathAnalyzer'].steps_number - ) - - # Write to file - self.write(data) - -class AOIScanPathAnalysisRecorder(UtilsFeatures.FileWriter): - - def __init__(self, **kwargs): - - # Init FileWriter - super().__init__(**kwargs) - - # Edit header line - self.header = "Timestamp (ms)", "NGram counts" - - def on_look(self, timestamp, ar_layer, exception): - """Record aoi scan path metrics.""" - - if ar_layer.is_analysis_available(): - - data = ( - timestamp, - ar_layer.analysis['argaze.GazeAnalysis.NGram.AOIScanPathAnalyzer'].ngrams_count - ) - - # Write to file - self.write(data) -``` - -Assuming that [ArGaze.GazeAnalysis.Basic](../../argaze.md/#argaze.GazeAnalysis.Basic) scan path analysis module is enabled for 'My FullHD screen' ArFrame, a ***scan_path_metrics.csv*** file would be created: - -|Timestamp (ms)|Duration (ms)|Steps number| -|:-------------|:------------|:-----------| -|3460 |1750 |2 | -|4291 |2623 |3 | -|4769 |3107 |4 | -|6077 |4411 |5 | -|6433 |4760 |6 | -|7719 |6050 |7 | -|... |... |... | - -Assuming that [ArGaze.GazeAnalysis.NGram](../../argaze.md/#argaze.GazeAnalysis.NGram) AOI scan path analysis module is enabled for 'MyLayer' ArLayer, a ***aoi_scan_path_metrics.csv*** file would be created: - -|Timestamp (ms)|NGram counts| -|:-------------|:-----------| -|5687 |"{3: {}, 4: {}, 5: {}}"| -|6208 |"{3: {('LeftPanel', 'GeoSector', 'CircularWidget'): 1}, 4: {}, 5: {}}"| -|... |... | - -!!! note "" - - Learn to [script the pipeline](./advanced_topics/scripting.md) to know more about [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) and [ArLayers](../../argaze.md/#argaze.ArFeatures.ArLayer) attributes. - -### Export gaze analysis to video file - -As explained in [pipeline steps visualisation chapter](visualisation.md), it is possible to get [ArFrame.image](../../argaze.md/#argaze.ArFeatures.ArFrame.image) once timestamped gaze positions have been processed by [ArFrame.look](../../argaze.md/#argaze.ArFeatures.ArFrame.look) method. - -Here is the JSON ArFrame configuration file where [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) observers are extended with a new my_frame_logger.VideoRecorder instance: - -```json -{ - "name": "My FullHD screen", - "size": [1920, 1080], - "observers": { - ... - "my_frame_logger.VideoRecorder": { - "path": "./video.mp4", - "width": 1920, - "height": 1080, - "fps": 15 - }, - ... -} -``` - -Here is *my_frame_logger.py* file extended with a new VideoRecorder class: - -```python -... - -class VideoRecorder(DataFeatures.PipelineStepObserver, UtilsFeatures.VideoWriter): - - def on_look(self, timestamp, ar_frame, exception): - """Record frame image into video file.""" - - self.write(ar_frame.image()) - -``` - -Assuming that [ArFrame.image_parameters](../../argaze.md/#argaze.ArFeatures.ArFrame.image_parameters) are provided, ***video.mp4*** file would be created.
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