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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
An [ArFrame](../../../argaze.md/#argaze.ArFeatures.ArFrame) configuration can be loaded from a Python dictionary.
```python
from argaze import ArFeatures, DataFeatures
# Set working directory to enable relative file path loading
DataFeatures.set_working_directory('path/to/folder')
# 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
with ArFeatures.ArFrame(**configuration) as ar_frame:
# 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 updates
Calling [ArFrame.look](../../../argaze.md/#argaze.ArFeatures.ArFrame.look) method leads to update many data into the pipeline.
```python
# Assuming that timestamped gaze positions are available
...
try:
# Look ArFrame at a timestamped gaze position
ar_frame.look(timestamped_gaze_position):
# Do something with last gaze position
... ar_frame.last_gaze_position()
# Check if a gaze movement has been identified
if ar_frame.last_gaze_movement() and ar_frame.last_gaze_movement().is_finished():
# Do something with identified fixation
if GazeFeatures.is_fixation(ar_frame.last_gaze_movement()):
...
# Do something with identified saccade
elif GazeFeatures.is_saccade(ar_frame.last_gaze_movement()):
...
# Do something with scan path analysis
if ar_frame.is_analysis_available():
for scan_path_analyzer_name, analyses in ar_frame.analysis().items():
for analysis_name, analysis in analyses.items():
...
# Do something with layers aoi scan path analysis
for layer_name, ar_layer in ar_frame.layers.items():
# Do something with last looked aoi name
... ar_frame.last_looked_aoi_name()
if ar_layer.is_analysis_available():
for aoi_scan_path_analyzer_name, analyses in ar_frame.analysis().items():
for analysis_name, analysis in analyses.items():
...
# Do something with pipeline exception
except Exception as e:
...
```
Let's understand the meaning of each data.
### *ar_frame.last_gaze_position()*
This is the last calibrated [GazePosition](../../../argaze.md/#argaze.GazeFeatures.GazePosition) returned by [GazePositionCalibrator](../../../argaze.md/#argaze.GazeFeatures.GazePositionCalibrator) if one is instanciated else, it is the last given [GazePosition](../../../argaze.md/#argaze.GazeFeatures.GazePosition).
### *ar_frame.last_gaze_movement()*
Last [GazeMovement](../../../argaze.md/#argaze.GazeFeatures.GazeMovement) 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 empty [GazeMovement](../../../argaze.md/#argaze.GazeFeatures.GazeMovement).
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 last gaze movement *finished* flag is false.
Then, the last 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.
### *ar_frame.is_analysis_available()*
To know when new scan path analysis is available.
### *ar_frame.analysis().items()*
This an iterator to access to all scan path analysis. Notice that each scan path analyzer returns a dictionary containing possibly several analyses.
### *ar_layer.last_looked_aoi_name()*
The name of the last aoi matching done by [AoiMatcher](../../../argaze.md/#argaze.GazeFeatures.AoiMatcher) if one is instanciated else, it is a None value.
### *ar_layer.is_analysis_available()*
To know when new aoi scan path analysis is available.
### *ar_layer.analysis().items()*
This an iterator to access to all aoi scan path analysis. Notice that each aoi scan path analyzer returns a dictionary containing possibly several analyses.
## 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
...
```
|
