跑出来结果之后怎么在结果图片上获取各个语意部分的区域信息？ #2578
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We recommend using English or English & Chinese for issues so that we could have broader discussion. |
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Hi, you need to post process your result on your own. Currently we do not support any tool to acquire region information of every semantic part class. |
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Closing the issue, as there is no activity for a while. |
xiexinch
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Aug 1, 2023
…on results (#3229) Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers. ## Motivation [Add semantic label to the segmentation visualization results 分割可视化结果中加上语义信息 #154](open-mmlab/OpenMMLabCamp#154) corresponding issue: [跑出来结果之后怎么在结果图片上获取各个语意部分的区域信息？ #2578](#2578) ## Modification 1. mmseg/apis/inference.py, add withLabels in visualizer.add_datasample call, to indicate whether add semantic label 2. mmseg/visualization/local_visualizer.py, add semantic labels by opencv; modify the demo comment description 3. mmseg/utils/__init__.py, add bdd100k datasets to test local_visualizer.py **Current visualize result** <img width="637" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/6ef6ce02-1d82-46f8-bde9-a1d69ff62df8"> **Add semantic label** <img width="637" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/00716679-b43a-4794-8499-9bfecdb4b78b"> ## Test results **tests/test_visualization/test_local_visualizer.py** test results：（MMSegmentation/tests/data/pseudo_cityscapes_dataset/leftImg8bit/val/frankfurt/frankfurt_000000_000294_leftImg8bit.png） <img width="643" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/6792b7d2-2512-4ea9-8500-1a7ed2d5e0dc"> **demo/inference_demo.ipynb** test results： <img width="966" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/dfc0147e-fb1a-490a-b6ff-a8b209352d9b"> ----- ## Drawbacks config opencv thickness according to image size <img width="496" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/0a54d72c-62b1-422c-89ae-69dc753fe0fc"> I have no idea of dealing with label overlapping for the time being
angiecao
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Aug 31, 2023
…on results (open-mmlab#3229) Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers. ## Motivation [Add semantic label to the segmentation visualization results 分割可视化结果中加上语义信息 open-mmlab#154](open-mmlab/OpenMMLabCamp#154) corresponding issue: [跑出来结果之后怎么在结果图片上获取各个语意部分的区域信息？ open-mmlab#2578](open-mmlab#2578) ## Modification 1. mmseg/apis/inference.py, add withLabels in visualizer.add_datasample call, to indicate whether add semantic label 2. mmseg/visualization/local_visualizer.py, add semantic labels by opencv; modify the demo comment description 3. mmseg/utils/__init__.py, add bdd100k datasets to test local_visualizer.py **Current visualize result** <img width="637" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/6ef6ce02-1d82-46f8-bde9-a1d69ff62df8"> **Add semantic label** <img width="637" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/00716679-b43a-4794-8499-9bfecdb4b78b"> ## Test results **tests/test_visualization/test_local_visualizer.py** test results：（MMSegmentation/tests/data/pseudo_cityscapes_dataset/leftImg8bit/val/frankfurt/frankfurt_000000_000294_leftImg8bit.png） <img width="643" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/6792b7d2-2512-4ea9-8500-1a7ed2d5e0dc"> **demo/inference_demo.ipynb** test results： <img width="966" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/dfc0147e-fb1a-490a-b6ff-a8b209352d9b"> ----- ## Drawbacks config opencv thickness according to image size <img width="496" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/0a54d72c-62b1-422c-89ae-69dc753fe0fc"> I have no idea of dealing with label overlapping for the time being
emily-lin
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Nov 18, 2023
…on results (open-mmlab#3229) Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers. ## Motivation [Add semantic label to the segmentation visualization results 分割可视化结果中加上语义信息 open-mmlab#154](open-mmlab/OpenMMLabCamp#154) corresponding issue: [跑出来结果之后怎么在结果图片上获取各个语意部分的区域信息？ open-mmlab#2578](open-mmlab#2578) ## Modification 1. mmseg/apis/inference.py, add withLabels in visualizer.add_datasample call, to indicate whether add semantic label 2. mmseg/visualization/local_visualizer.py, add semantic labels by opencv; modify the demo comment description 3. mmseg/utils/__init__.py, add bdd100k datasets to test local_visualizer.py **Current visualize result** <img width="637" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/6ef6ce02-1d82-46f8-bde9-a1d69ff62df8"> **Add semantic label** <img width="637" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/00716679-b43a-4794-8499-9bfecdb4b78b"> ## Test results **tests/test_visualization/test_local_visualizer.py** test results：（MMSegmentation/tests/data/pseudo_cityscapes_dataset/leftImg8bit/val/frankfurt/frankfurt_000000_000294_leftImg8bit.png） <img width="643" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/6792b7d2-2512-4ea9-8500-1a7ed2d5e0dc"> **demo/inference_demo.ipynb** test results： <img width="966" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/dfc0147e-fb1a-490a-b6ff-a8b209352d9b"> ----- ## Drawbacks config opencv thickness according to image size <img width="496" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/0a54d72c-62b1-422c-89ae-69dc753fe0fc"> I have no idea of dealing with label overlapping for the time being
nahidnazifi87
pushed a commit
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Apr 5, 2024
…on results (open-mmlab#3229) Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers. ## Motivation [Add semantic label to the segmentation visualization results 分割可视化结果中加上语义信息 open-mmlab#154](open-mmlab/OpenMMLabCamp#154) corresponding issue: [跑出来结果之后怎么在结果图片上获取各个语意部分的区域信息？ open-mmlab#2578](open-mmlab#2578) ## Modification 1. mmseg/apis/inference.py, add withLabels in visualizer.add_datasample call, to indicate whether add semantic label 2. mmseg/visualization/local_visualizer.py, add semantic labels by opencv; modify the demo comment description 3. mmseg/utils/__init__.py, add bdd100k datasets to test local_visualizer.py **Current visualize result** <img width="637" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/6ef6ce02-1d82-46f8-bde9-a1d69ff62df8"> **Add semantic label** <img width="637" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/00716679-b43a-4794-8499-9bfecdb4b78b"> ## Test results **tests/test_visualization/test_local_visualizer.py** test results：（MMSegmentation/tests/data/pseudo_cityscapes_dataset/leftImg8bit/val/frankfurt/frankfurt_000000_000294_leftImg8bit.png） <img width="643" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/6792b7d2-2512-4ea9-8500-1a7ed2d5e0dc"> **demo/inference_demo.ipynb** test results： <img width="966" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/dfc0147e-fb1a-490a-b6ff-a8b209352d9b"> ----- ## Drawbacks config opencv thickness according to image size <img width="496" alt="image" src="https://github.com/open-mmlab/mmsegmentation/assets/35064479/0a54d72c-62b1-422c-89ae-69dc753fe0fc"> I have no idea of dealing with label overlapping for the time being
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