[Feature] Add OS16 DeepLab #154
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Task linked: CU-4fp4ga DeepLabV3/DeepLabV3+ OS16 models |
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## master #154 +/- ##
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+ Coverage 83.32% 83.38% +0.06%
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Files 83 83
Lines 3921 3937 +16
Branches 617 619 +2
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+ Hits 3267 3283 +16
Misses 520 520
Partials 134 134
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hellock
approved these changes
Sep 29, 2020
bowenroom
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Feb 25, 2022
* Add D16-MG124 models * Use MMCV DepthSepConv * add OHEM * add warmup * fixed test * fixed test * change to bs 16 * revert config * add models
aravind-h-v
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Mar 27, 2023
* begin text2img conversion script * add fn to convert config * create config if not provided * update imports and use UNet2DConditionModel * fix imports, layer names * fix unet coversion * add function to convert VAE * fix vae conversion * update main * create text model * update config creating logic for unet * fix config creation * update script to create and save pipeline * remove unused imports * fix checkpoint loading * better name * save progress * finish * up * up Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
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
pushed a commit
to emily-lin/mmsegmentation
that referenced
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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
to nahidnazifi87/mmsegmentation_playground
that referenced
this pull request
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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