Comments (7)
Both stuff and thing labels are included in the JSON. Just open it in your editor and you will see that the category_id fields correspond to integers 1-182 from: https://raw.githubusercontent.com/nightrome/cocostuff/master/dataset/cocostuff-labels.txt
from cocostuff10k.
this is true for the json provided in this repo. However you refer to http://cocodataset.org/#stuff-challenge2017 for more images and in this json it starts at 1 with banner and ends with the category other representing everyting from the thing class.
from cocostuff10k.
Yes, but this repo does not have anything to do with the challenge, where all thing classes are merged into a single class. The code for that can be found here, where you can also find and modify the script that merged the stuff and things: https://github.com/nightrome/cocoapi/blob/master/PythonAPI/cocostuff/internalToCocoGTDemo.py
Note that banner has the index 92, so the thing indices (1-91) are still usable and you could just add the original thing annotations from COCO to the same file.
from cocostuff10k.
ok thank you. Do you know if the Img ID's in both sets match? Or even the AnnIds? Or do I have to match the filenames?
from cocostuff10k.
The image ids certainly match. The annotation ids are somewhat arbitrary. Just remove annotations with the new thing category id from the challenge annotations and add all annotations from COCO.
from cocostuff10k.
Ok that should be easy to do thanks! Do you know if the train val split is the same in the stuff and the coco set? Or should I combine them and split them after adding the annotations?
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The split is the same, but since the current version does not include all 165k images from COCO yet, the training set of the challenge is a subset of all training images. Val is complete and hence identical.
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Related Issues (20)
- error occured when extracting the file HOT 10
- is it possible to add an additional class on the dataset ? HOT 1
- Annotation tool HOT 11
- .mat to .png conversion on dataset annotation files HOT 6
- Could you share the trained Deeplab models? HOT 1
- prepare my own data as cocostuff HOT 1
- Loading this dataset by using pycocotools HOT 5
- Convert to Yolo forman HOT 2
- extractThings Problem HOT 2
- Can I use this on an image ? HOT 2
- stuff annotation tool HOT 1
- gasonMex undefined HOT 1
- How can I use this tool to annotate another dataset? HOT 3
- Matlab command convertAnnotationsDeeplab() doesn't work HOT 1
- How can I visualize my DeepLab test results? HOT 1
- How about the full class list of older cocostuff1.0? HOT 1
- How to extract only the png from mat ? HOT 1
- How many total classes show I consider during one-hot encoding the segmentation maps? HOT 1
- why isn`t download data coco now ? HOT 1
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