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diff --git a/docs/user_guide/gaze_analysis_pipeline/heatmap_visualisation.md b/docs/user_guide/gaze_analysis_pipeline/heatmap_visualisation.md deleted file mode 100644 index a1f1672..0000000 --- a/docs/user_guide/gaze_analysis_pipeline/heatmap_visualisation.md +++ /dev/null @@ -1,71 +0,0 @@ -Visualize heatmap -================= - -Heatmap is an optional [ArFrame](../../argaze.md/#argaze.ArFeatures.ArFrame) pipeline step. It is executed at each new gaze position to update heatmap image. - - - -## Enable ArFrame heatmap - -[ArFrame](../../argaze.md/#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.md/#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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