Comments (4)
I'll be adding custom dataset support soon. I'm currently travelling so I can't do it right now, but I'll follow up when I can.
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So uh that turned out to be a lot longer than "soon", but I finally added support for custom datasets (latest commit). I've updated the readme with directions, but I'll paste them here for convenience:
- Create a COCO-style Object Detection JSON annotation file for your dataset. The specification for this can be found here. Note that we don't use some fields, so the following may be omitted:
info
liscense
- Under
image
:license, flickr_url, coco_url, date_captured
categories
(we use our own format for categories, see below)
- Create a definition for your dataset under
dataset_base
indata/config.py
(see the comments indataset_base
for an explanation of each field):
my_custom_dataset = dataset_base.copy({
'name': 'My Dataset',
'train_images': 'path_to_training_images',
'train_info': 'path_to_training_annotation',
'valid_images': 'path_to_validation_images',
'valid_info': 'path_to_validation_annotation',
'has_gt': True,
'class_names': ('my_class_id_1', 'my_class_id_2', 'my_class_id_3', ...)
})
- A couple things to note:
- Class IDs in the annotation file should start at 1 and increase sequentially on the order of
class_names
. If this isn't the case for your annotation file (like in COCO), see the fieldlabel_map
indataset_base
. - If you do not want to create a validation split, use the same image path and annotations file for validation. By default (see
python train.py --help
),train.py
will output validation mAP for the first 5000 images in the dataset every 2 epochs.
- Class IDs in the annotation file should start at 1 and increase sequentially on the order of
- Finally, in
yolact_base_config
in the same file, change the value for'dataset'
to'my_custom_dataset'
or whatever you named the config object above. Then you can use any of the training commands in the previous section.
Note that I haven't done a lot of testing with this, so I might have broken some things. Let me know if you have any issues with this and I'll get back to you within my stellar, industry-leading 19 day response window.
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Need the training steps on my own datasets too.
from yolact.
I also need the training steps on my own datasets.
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Related Issues (20)
- Hyperparameter tuning
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