Visualize pipeline steps
========================

Visualisation is not a pipeline step but each [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) pipeline steps outputs can be drawn in real time or afterward, depending of application purpose.

![ArFrame visualisation](../../img/visualisation.png)

## Add image parameters to ArFrame JSON configuration file

[ArFrame.image](../../argaze.md/#argaze.ArFeatures.ArFrame.image) method parameters can be configured thanks to a dedicated JSON entry.

Here is an extract from the JSON ArFrame configuration file with a sample where image parameters are added:

```json
{
    "name": "My FullHD screen",
    "size": [1920, 1080],
    ...
    "image_parameters": {
        "draw_gaze_positions": {
            "color": [0, 255, 255],
            "size": 2
        },
        "draw_fixations": {
            "deviation_circle_color": [255, 255, 255],
            "duration_border_color": [127, 0, 127],
            "duration_factor": 1e-2,
            "draw_positions": {
                "position_color": [0, 255, 255],
                "line_color": [0, 0, 0]
            }
        }, 
        "draw_saccades": {
            "line_color": [255, 0, 255]
        },
        "draw_scan_path": {
            "draw_fixations": {
                "deviation_circle_color": [255, 0, 255],
                "duration_border_color": [127, 0, 127],
                "duration_factor": 1e-2
            }, 
            "draw_saccades": {
                "line_color": [255, 0, 255]
            }
        },
        "draw_layers": {
            "MyLayer": {
                "draw_aoi_scene": {
                    "draw_aoi": {
                        "color": [255, 255, 255],
                        "border_size": 1
                    }
                },
                "draw_aoi_matching": {
                    "draw_matched_fixation": {
                        "deviation_circle_color": [255, 255, 255],
                        "draw_positions": {
                            "position_color": [0, 255, 0],
                            "line_color": [0, 0, 0]
                        }
                    },
                    "draw_matched_region": {
                        "color": [0, 255, 0],
                        "border_size": 4
                    }, 
                    "draw_looked_aoi": {
                        "color": [0, 255, 0],
                        "border_size": 2
                    },
                    "looked_aoi_name_color": [255, 255, 255],
                    "looked_aoi_name_offset": [0, -10]
                }
            }
        }
    }
}
```

!!! warning
    Most of *image_parameters* entries work if related ArFrame/ArLayer pipeline steps are enabled.  
    For example, JSON *draw_scan_path* entry needs GazeMovementIdentifier and ScanPath steps to be enabled.

Then, [ArFrame.image](../../argaze.md/#argaze.ArFeatures.ArFrame.image) method can be called in various situations.

## Live window display

While timestamped gaze positions are processed by [ArFrame.look](../../argaze.md/#argaze.ArFeatures.ArFrame.look) method, it is possible to display [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) image thanks to [OpenCV package](https://pypi.org/project/opencv-python/).

```python
import cv2

def main():

	# Assuming ArFrame is loaded
	...

        # Create a window to display ArFrame
        cv2.namedWindow(ar_frame.name, cv2.WINDOW_AUTOSIZE)

        # Assuming that timestamped gaze positions are being processed by ArFrame.look method
        ...

            # Update ArFrame image display
            cv2.imshow(ar_frame.name, ar_frame.image())

            # Wait 10 ms
            cv2.waitKey(10)

if __name__ == '__main__':

    main()
```

!!! note "Export to video file"

    Video exportation is detailed in [gaze analysis recording chapter](recording.md).