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Detection output in coco format #621
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@Pari-singh this functionality is not available currently. Note that detect.py always runs at batch-size 1 also. The file is simply a demo of what's possible, so that you can use it as a starting point for your own development. |
Ok I can modify this file, but where can I access the data needed to save the following metrics in COCO Format. (I understand I may have to do some math, but where is the raw data located for each of the following):
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@joehoeller I don't understand your question. test.py returns all metrics on the selected dataset. See https://github.com/ultralytics/yolov3#map |
@joehoeller, data can be any on which you want to do the detection. I was working with FLIR dataset, it is available on the FLIR website. |
Are you asking for a new post training grader .py file? |
Ultralytics seems a lot better, I was previously using a Darknet fork that had very poor documentation. A lot of what you can do, and how to do it is (mostly) well documented here. So I think that was my main problem, was working in a forked repo. I will look at test.py. Thank you all for your responses. |
@Pari-singh excellent work btw. |
@glenn-jocher Please see - #650 |
How do we get labels for our own images? The directions are below but do not make sense to me. Train On Custom Data
Each image's label file must be locatable by simply replacing /images/.jpg with /labels/.txt in its pathname. An example image and label pair would be:
One file per image (if no objects in image, no label file is required). |
UPDATE: I fixed the PR and updated the math, the COCO JSON -> Darknet conversion tool (Dark Chocolate) works now: daddydrac/Dark-Chocolate#2 |
We should merge Dark Chocolate into Ultralytics repo and close this out now that its vetted and tested. |
I'll close this issue for now as the original issue appears to have been resolved, and/or no activity has been seen for some time. Feel free to comment if this is not the case. |
Hi @glenn-jocher, we have the option of getting our test.py results in coco (json) format. Is there a way to get the detection output as well in json format? Format like mentioned here http://cocodataset.org/#format-results
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