The code for "Deep Level Set for Box-supervised Instance Segmentation in Aerial Images".

Related tags

Deep Learning instance-segmentation box-supervised
Overview

Deep Levelset for Box-supervised Instance Segmentation in Aerial Images

Wentong Li, Yijie Chen, Wenyu Liu, Jianke Zhu*

This code is based on MMdetection and AerialDetection. The code is coming soon.

Visualization

Instance segmentation results on the iSAID test set with the supervision of box annotations.

Citation

@article{li2021deep,
	title="Deep Level Set for Box-supervised Instance Segmentation in Aerial Images.",
	author="Wentong {Li}, Yijie {Chen}, Wenyu {Liu}, Jianke {Zhu}.",
	journal="arXiv preprint arXiv:2112.03451",
	year="2021"
}
Comments
  • Pretrained Weights for iSAID dataset

    Pretrained Weights for iSAID dataset

    @LiWentomng hi thanks for sharing the work can y ou please share the pretrained weights for iSAID dataset on google drive or one drive THanks in advance

    opened by abhigoku10 3
  • The code about levelset

    The code about levelset

    Thank you for your great work. I want to know about the specific implementation of level sets, but I don't know where the code is about level sets. Can you point me to the exact location of the level set code? Thanks!

    opened by sutiankang 1
  • Question regarding the LevelSetLoss implementation

    Question regarding the LevelSetLoss implementation

    Thanks for your awesome work.

    I found in the implementation of LevelSetLoss that the term of length regularization is not calculated. Would you like to share the reason for it?

    Besides that, what is the motivation that only calculates the loss for the positive samples in Eqn.(11) in the paper?

    Best

    opened by QianyiWu 1
  • training time

    training time

    Hello, how long does it take to use 2080ti for training? I have two 2080tis, so I want to know the length of training. Or what graphics card do you use and how long does it take to train？think you

    opened by liuguol 1
  • Instance Segmentation on the Whole Image

    Instance Segmentation on the Whole Image

    @LiWentomng In your paper, you mentioned restricting the level set to gt bounding box for segmentation and also mentioned that the training result is poor on the whole image. How can I get the boxlevelset to run on the whole image?

    opened by zhaoyangwei123 0
  • IndexError: list index out of range

    IndexError: list index out of range

    I ran into this problem when training with a custom data set.How to solve it? Traceback (most recent call last): File "tools/train.py", line 191, in main() File "tools/train.py", line 187, in main meta=meta) File "/content/drive/MyDrive/boxlevelset/mmdet/apis/train.py", line 172, in train_detector runner.run(data_loaders, cfg.workflow) File "/usr/local/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 127, in run epoch_runner(data_loaders[i], **kwargs) File "/usr/local/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 54, in train self.call_hook('after_train_epoch') File "/usr/local/lib/python3.7/site-packages/mmcv/runner/base_runner.py", line 307, in call_hook getattr(hook, fn_name)(self) File "/content/drive/MyDrive/boxlevelset/mmdet/core/evaluation/eval_hooks.py", line 147, in after_train_epoch key_score = self.evaluate(runner, results) File "/content/drive/MyDrive/boxlevelset/mmdet/core/evaluation/eval_hooks.py", line 177, in evaluate results, logger=runner.logger, **self.eval_kwargs) File "/content/drive/MyDrive/boxlevelset/mmdet/datasets/dcm.py", line 482, in evaluate cocoEval.evaluate() File "/usr/local/lib/python3.7/site-packages/pycocotools/cocoeval.py", line 149, in evaluate self._prepare() File "/usr/local/lib/python3.7/site-packages/pycocotools/cocoeval.py", line 110, in _prepare _toMask(gts, self.cocoGt) File "/usr/local/lib/python3.7/site-packages/pycocotools/cocoeval.py", line 95, in _toMask rle = coco.annToRLE(ann) File "/usr/local/lib/python3.7/site-packages/pycocotools/coco.py", line 497, in annToRLE rles = maskUtils.frPyObjects(segm, h, w) File "pycocotools/_mask.pyx", line 292, in pycocotools._mask.frPyObjects IndexError: list index out of range

    opened by ccdongxu 3
  • Instance and Panoptic segmentation

    Instance and Panoptic segmentation

    @LiWentomng thanks for thsi toolbox it shall be very helpfull to the community, just had few queries

    can we use this to train instance segmentation using BDD100k dataset for all the scenes Panpotic based segmentation dataset Thanks in adavance

    opened by abhigoku10 1
  • no module named tree_filter_cuda

    no module named tree_filter_cuda

    Traceback (most recent call last): File "./train.py", line 15, in from mmdet.apis import set_random_seed, train_detector File "/workspace/boxlevelset/mmdet/apis/init.py", line 1, in from .inference import (async_inference_detector, inference_detector, File "/workspace/boxlevelset/mmdet/apis/inference.py", line 11, in from mmdet.datasets import replace_ImageToTensor File "/workspace/boxlevelset/mmdet/datasets/init.py", line 10, in from .utils import (NumClassCheckHook, get_loading_pipeline, File "/workspace/boxlevelset/mmdet/datasets/utils.py", line 9, in from mmdet.models.dense_heads import GARPNHead, RPNHead File "/workspace/boxlevelset/mmdet/models/init.py", line 6, in from .dense_heads import * # noqa: F401,F403 File "/workspace/boxlevelset/mmdet/models/dense_heads/init.py", line 30, in from .box_solov2_head import BoxSOLOv2Head File "/workspace/boxlevelset/mmdet/models/dense_heads/box_solov2_head.py", line 12, in from mmdet.ops.tree_filter.modules.tree_filter import MinimumSpanningTree, TreeFilter2D File "/workspace/boxlevelset/mmdet/ops/tree_filter/modules/tree_filter.py", line 5, in from ..functions.mst import mst File "/workspace/boxlevelset/mmdet/ops/tree_filter/functions/mst.py", line 7, in import tree_filter_cuda as _C ModuleNotFoundError: No module named 'tree_filter_cuda'

    opened by shanghangjiang 8
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