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Visualize heatmap
=================
Heatmap is an optional [ArFrame](../../../argaze/#argaze.ArFeatures.ArFrame) pipeline step. It is executed at each new gaze position to update heatmap image.
## Enable ArFrame heatmap
[ArFrame](../../../argaze/#argaze.ArFeatures.ArFrame) heatmap visualization can be enabled thanks to a dedicated JSON entry.
Here is the JSON ArFrame configuration file example where heatmap visualization is enabled:
```json
{
"name": "My FullHD screen",
"size": [1920, 1080],
...
"heatmap": {
"size": [320, 180],
"sigma": 0.025,
"buffer": 0
}
}
```
Then, here is how to access to heatmap object:
```python
# Assuming an ArFrame is loaded
...
print("heatmap:", ar_frame.heatmap)
```
Finally, here is what the program writes in console:
```txt
heatmap: Heatmap(size=[320, 180], buffer=0, sigma=0.025)
```
Now, let's understand the meaning of each JSON entry.
### Size
The heatmap image size in pixel. Higher size implies higher CPU load.
### Sigma
The gaussian point spreading to draw at each gaze position.
### Buffer
The size of point spread images buffer (0 means no buffering) to visualize only last N gaze positions.
## Export heatmap to PNG file
Once timestamped gaze positions have been processed by [ArFrame.look](../../../argaze/#argaze.ArFeatures.ArFrame.look) method, it is possible to write heatmap image thanks to OpenCV package.
```python
import cv2
# Assuming that timestamped gaze positions have been processed by ArFrame.look method
...
# Export heatmap image
cv2.imwrite('./heatmap.png', ar_frame.heatmap.image)
```
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