uoais
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how to label my own data
how to label my own data
Do you mean to load the data into a format in order to run the training pipeline?
Do you mean to load the data into a format in order to run the training pipeline?
Well,I mean how to use the labelme to label my data and then load the data into a format in order to run the training pipeline.Thank you.
I think if you convert any dataset into the following format, it should work in training:
datasets: list = [
{
"file_name": str,
"depth_file_name": str,
"height": img_height,
"width": img_width,
"image_id": int,
"annotations": [
{
"iscrowd": 0,
"bbox": [x, y, w, h],
"category_id": 0,
"segmentation": {"size": [img_width, img_height], "count": rle_string}, # Created using pycocotools.mask.encode()
"visible_mask": {"size": [img_width, img_height], "count": rle_string}, # Created using pycocotools.mask.encode()
"occluded_mask": {"size": [img_width, img_height], "count": rle_string}, # Created using pycocotools.mask.encode()
"occluded_rate": float,
"bbox_mode": BoxMode.XYWH_ABS, # from detectron2.structures import BoxMode
}, ...
]
}, ...
]
Use detectron2.data.DatasetCatalog.register()
to register the function which outputs the format above.
I hope this could help :)
I believe the issue has been resolved, and I am closing this now. Thanks to @YueBro for addressing it.