Graphical user interface (GUI)¶
The idtracker.ai graphical user interface consists on a main panel and different secondary windows. Here, we explain the different features of the GUI and how to interact with them.
1. “Video” text box¶
The absolute path to the video that you are going to track will appear in this box.
3. “Resolution reduction” text box¶
Type a value between 0 and 1 to reduce the resolution of the video by that factor. You can change the value of the box by scrolling up/down or by clicking the arrows. Note that the output trajectories will be in full-frame resolution.
4. “Number of animals” text box¶
Type the number of animals in the video or scroll up/down to change the value of the number inside of the box.
5. “Segmented blobs” info checkbox¶
Check the box Graph to open a windows that will show the number of blobs segmented and their area in pixels.
The x-axis indicates the blob index and the y-axis the number of pixels of the given blob.
If the windws appears white, move to a different frame using the video player controls. This should upate the graph.
6. “Check segmentation” checkbox¶
Check this box to be warned if there are some frames in the videos contain more segmented blobs that animals. The warning will appear after pressing the Track video button and after the segmentation process id finished.
You will be shown a message with the path where a .csv file containing the frame numbers with more blobs than animals. You can use this .csv to explore your video again and readjust the preprocessing parameters.
NOTE: In the previous version a re-segmentation with the new preprocessing parameters would be performed only for those frames. In the current version, the segmentation will be run for the whole video again. We might implement this feature in the future.
7. “Intensity thresholds” sliders¶
Change the minimum and maximum values of the intensity thresholds to select the intensity range of the pixels representing the animals to be segmented. Values closer to 0 correspond to darker pixels and values closer to 255 correspond to brighter pixels. You can change the values either by typing them inside of the box, scrolling up/down with your cursor on top of the box, or by gliding the extremes of the blue bar.
8. Area thresholds¶
Change the minimum and maximum values of the blobs area threshold to discard blobs which intensity is in the same intensity range as the animals you want to track. Blobs with a number of pixels inside of the range will be considered for tracking.
9. “Apply ROI” checkbox¶
To select one or more ROIs check the box Apply ROI. New buttons and a text box will appear in the main window.
Click on the buttons Polygon, Rectangle or Ellipse to select the type of ROI that you want to draw.
To draw a rectangle, click in one of the corners of the rectangle, a drag the cursor to the opposite (diagonally) corner of the rectangle that you want to draw.
To draw a polygon, click on every vertex of the polygon.
To draw an ellipse, click in 5 different parts on the perimeter of the ellipse that you want to draw.
To delete and ROI click on the set of number representing a given ROI. They will be highligthed in blue. Then press the top right minus (-) sign to delete it.
Note that each frame is normalized by its average intensity. When an ROI is applied, the average intensity is computed only using values inside the ROI. This might cause changes in the segmentation and you might need to reajust the values of the intensity and area thresholds.
10. “Subtract background” checkbox¶
Check this box if you want to apply a background subtraction processing. Checking this box will compute a model of the background as the average of multiple equally spaced frames in the video. This can be used to remove static objects that are of the same size and color as the animals you are trying to track. If the video is very long, after clicking on the check box, it might take a while until the box is actually checked. This happens because while the background is being computed, the GUI is held on standby. Note that when this checkbox is marked, the segmentation might change and you might need to readjust intensity thresholds.
11. Tracking interval” slider¶
You can select a frames range for which the tracking will be performed. You can change the minimum and maximum values either by typing them inside of the box, scrolling up/down with your cursor on top of the box, or by gliding the extremes of the blue bar. The frames outside of this range will be ignored. This can be useful if, for example, you want to ignore certain parts of the video.
12. “Multiple” tracking intervals checkbox¶
Check the box Multiple ranges to add multiple tracking intervals. The blue bar will disappear and instead a text box with a Add range button will appear.
Click the Add range button to add the starting and ending frames of a new tracking interval.
Alternatively you can add the different intervals by typing inside of the text box. Tracking intervals should be expressed with square brackets and separated by commas.
Adding tracking intervals can be useful to separated multiple no-consecutive videos, or to discard parts of the video that don’t have to be considered for tracking.
13. “Add setup info” checkbox¶
In this new version (v4), we added a feature to annotate groups of points in the video frame. We named this feature “Add setup info”, becuase we originally used it to add information about different points (or landmarks) of the experimental setup that were important for the behaviour analysis.
To add a new group of points press the button “Add setup points”. A new window will appear where you should write the name of the list of points to be annotatoted.
You can annotate the points by cleacking on the frame in the preview window.
This will add the points in pixels coordinates to the text box on the left.
This list of points will be stored in the trajectories.npy and trajectories_wo_gaps.npy files.
14. “Session name” text box¶
Type here the name of the tracking session (e.g. test, avoid using spaces in the session name, use underscores instead). A folder with the name session_test will be created in the same folder where the video is. All the data generated for the tracking of the video and the tracking results will be output in this folder.
16. “Track without identities” checkbox¶
Check this box if you want to obtain trajectories of the animals for which the identities (columns in the trajectories array) do not necessarily correspond to the same animal. The algorithm will skip the core of the tracking where the convolutional neural network is trained to identify the animals. Also, be aware that the algorithm also skips the interpolation step where the trajectories of the individuals in blobs belonging to multiple animals (crossings, touches, …) are assigned.
18. “Progress” bar¶
The progress bar will advance as the different steps of the algorithm are computed.
22. Video preview¶
This window will show the video that you are going to track and the effects of the different preprocessing parameters. Segmented blobs of pixels will be marked in red color. Regions of interest (ROIs) will be marked in light green (see the point 19 to learn how to set ROIs). Zoom in/out by scrolling down/up on top of the video image. Click the wheel button (central button on most mice) on top of the frame to drag the frame around in the preview window. By clicking with the right botton of the mouse on the preview image, you can activate the “Use scroll to move between frames” freature.
Press the PLAY button to play the video and see the effect of the preprocessing parameters for the different frames. By pressing any number from 1-9 the video will be fast-forwarded at the respective speed. This will allow you to explore the video more quickly. Press the PAUSE button to pause the video.
24. “Frame number” text box and track bar¶
This box will show the current frame number. Place the cursor on top of the box and scroll up/down to increase/decrease the frame number.
You can move to different frames of the video using the track bar. Drag the gray square to move to different frames in the video. The numbers next to the track bar indicate the time of the video.