class value and export coordinates to csv

[nachonacho2]

Hi, I have a question related to issue # 19:
I'm working through the detectron2 demo (detectron2_cars.py) to understand the code and wanted to change the detected class from cars to person. I found that changing row 32 to "if c == 0" does this. How do I export/print a list of the detected classes?

Also, I would like to export to a csv file the centroid/center coordinates for each tracked object for each frame (similar to print_objects_as_table, but ideally with the data from each frame in one row). Any suggestions?

[joaqo]

Hi.

For the first question, you would need to get a list of the mapping between class number and class name from the official COCO website, and then print them to the user.

For the second question, you would need to continously store the results you get from norfair as you iterate over a video in some data structure in memory, and then convert it into a CSV when you finish processing the video. Or you could just append to an CSV file on disk on each frame processed. It should be quite easy.

[nachonacho2]

Thanks for your reply joaqo.

Following up on the second question, could you please help me understand the norfair results? I may well be approaching this in the wrong way (I am completely new to python).
I think the coordinates I want to export are saved as a numpy array within detection.points and possibly also last_detection of tracked_objects. For each frame, printing detections or tracked_objects gives me a list containing items like this: <norfair.tracker.Detection object at 0x7f792baa0940>
I assume this hexadecimal contains the coordinates and object ID? How to convert to 'human readable' format? (Or is there a better way to obtain the data?)
Otherwise, as you recommended, I think I'm okay with saving the results from each frame and converting into a CSV afterwards.

[joaqo]

Hi nacho!

On each frame processed, Norfair takes as inputs a list of Detection objects and returns as output a list of TrackedObjects. Your detector is in charge of producing the list of Detections to feed into norfair, and then it is your job to take the list of TrackedObject that Norfair produces and do something useful with them.

With regards to how to use these TrackedObjects, here you can see their attributes. The one you probably will be more interested in is estimate, as it is a numpy array containing the position Norfair estimates each point in that object to be in.

Regarding that hexadecimal number, its just the memory address of that object, just an internal python implementation detail and not really related to Norfair.

Please feel free to ask more questions.

[nachonacho2]

Thanks again Joaqo! You helped push me in the right direction to have a working implementation using TrackedObject's estimate :)

It would be nice to have the actual Detection's coordinates whilst maintaining Norfair's ID for each object, but I can manage with the slight loss of accuracy.

I have another question unrelated to the above, so I'll open as a new issue...

[joaqo]

Hey @nachonacho2, you actually can access the Detection's coordinates, its listed in the link to TrackedObject's arguments I linked above, under last_detection.

[nachonacho2]

Hey Joaqo, took me awhile but I got there...
Might be helpful for others in future:
Accessing last_detection just gave me the memory address as noted above. The x, y coordinates can be obtained from: obj.last_detection.points[0], obj.last_detection.points[1]
Their storage shape is slightly different to that of 'estimate', from which the x, y can be obtained from: obj.estimate[:, 0], obj.estimate[:, 1]

Thanks!

[joaqo]

Oh I now understand what you meant.

The property last_detection returns a Detection object, which contains several things inside it, among others is the points attribute, which stores the coordinates you needed. You can look at this part of the documentation to see what other attributes it contains.

Regarding the memory address you mention, last_detection wasn't returning its memory address to you, it was returning a Detection object, which python prints to console as a string, which among other things contains its memory address. Look into python's __repr__ method if you want to look deeper into this.