[Feature] Add OS16 DeepLab #154
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Task linked: CU-4fp4ga DeepLabV3/DeepLabV3+ OS16 models |
Codecov Report
@@ Coverage Diff @@
## master #154 +/- ##
==========================================
+ Coverage 83.32% 83.38% +0.06%
==========================================
Files 83 83
Lines 3921 3937 +16
Branches 617 619 +2
==========================================
+ Hits 3267 3283 +16
Misses 520 520
Partials 134 134
Flags with carried forward coverage won't be shown. Click here to find out more.
Continue to review full report at Codecov.
|
|
There are conflicts now. |
hellock
approved these changes
Sep 29, 2020
bowenroom
pushed a commit
to bowenroom/mmsegmentation
that referenced
this pull request
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
pushed a commit
to aravind-h-v/mmsegmentation
that referenced
this pull request
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 <[email protected]>
xiexinch
pushed a commit
that referenced
this pull request
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
pushed a commit
to angiecao/mmsegmentation
that referenced
this pull request
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
this pull request
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
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.