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Simple tool to split COCO annotations into train/test datasets.

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ids are supposed to start from 1 and increase sequentially. Many dataloaders and libraries for COCO will give errors and not work with this haphazard id indexing.

I am wondering does your code reproduce same results every time if executed with the same parameters I mean by same results images I find in train.json will be the...

When training and testing sets are generated in an 80/20 ratio, if there is more than one category they are balanced, that is, would each category in the json file...

- Add option to split the images into ```train``` and ```test``` subfolders; - Fix error when there are no *'licences'* and *'info'* in the json.

I encounter this issue, please help me to solve it: ****- When I type the full command:**** `python cocosplit.py --having-annotaions -s 0.8 D:/IMG_from_VID/COCO_Datasets/data/trainval.json train.json test.json` **It shows this mess:** >...

When running the program I get the error: `FileNotFoundError: [Errno 2] No such file or directory: 'data/coco/images/frame_014171_d3.PNG'` Is there a way for the script to ignore missing images?

It is possible to do cross validation with this? My first question is if the split is random? My second question is: Say, I have 1000 annotations in ONE json...

for coco format, the image dir requires split too for some models. This branch inherited from the existing implementation to split images into train2017 and test2017 set

I would like to use the --multi-class option, but I noticed that it would only split the image and the first bounding box declaration into the validation set. If the...