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mmsegmentation/model-index.yml

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[Feature] support mim (#549) * dice loss * format code, add docstring and calculate denominator without valid_mask * minor change * restore * add metafile * add manifest.in and add config at setup.py * add requirements * modify manifest * modify manifest * Update MANIFEST.in * add metafile * add metadata * fix typo * Update metafile.yml * Update metafile.yml * minor change * Update metafile.yml * add subfix * fix mmshow * add more metafile * add config to model_zoo * fix bug * Update mminstall.txt * [fix] Add models * [Fix] Add collections * [fix] Modify collection name * [Fix] Set datasets to unet metafile * [Fix] Modify collection names * complement inference time
2021-06-01 06:07:24 +08:00
Import:
[Dev] update update-model-index pre-commit hook (#2667)
2023-03-17 19:12:58 +08:00
- configs/ann/metafile.yaml
- configs/apcnet/metafile.yaml
- configs/beit/metafile.yaml
- configs/bisenetv1/metafile.yaml
- configs/bisenetv2/metafile.yaml
- configs/ccnet/metafile.yaml
- configs/cgnet/metafile.yaml
- configs/convnext/metafile.yaml
- configs/danet/metafile.yaml
[Feature] Support DDRNet (#2855) 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 Support DDRNet Paper: [Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes](https://arxiv.org/pdf/2101.06085) official Code: https://github.com/ydhongHIT/DDRNet There is already a PR https://github.com/open-mmlab/mmsegmentation/pull/1722 , but it has been inactive for a long time. ## Current Result ### Cityscapes #### inference with converted official weights | Method | Backbone | mIoU(official) | mIoU(converted weight) | | ------ | ------------- | -------------- | ---------------------- | | DDRNet | DDRNet23-slim | 77.8 | 77.84 | | DDRNet | DDRNet23 | 79.5 | 79.53 | #### training with converted pretrained backbone | Method | Backbone | Crop Size | Lr schd | Inf time(fps) | Device | mIoU | mIoU(ms+flip) | config | download | | ------ | ------------- | --------- | ------- | ------- | -------- | ----- | ------------- | ------------ | ------------ | | DDRNet | DDRNet23-slim | 1024x1024 | 120000 | 85.85 | RTX 8000 | 77.85 | 79.80 | [config](https://github.com/whu-pzhang/mmsegmentation/blob/ddrnet/configs/ddrnet/ddrnet_23-slim_in1k-pre_2xb6-120k_cityscapes-1024x1024.py) | model \| log | | DDRNet | DDRNet23 | 1024x1024 | 120000 | 33.41 | RTX 8000 | 79.53 | 80.98 | [config](https://github.com/whu-pzhang/mmsegmentation/blob/ddrnet/configs/ddrnet/ddrnet_23_in1k-pre_2xb6-120k_cityscapes-1024x1024.py) | model \| log | The converted pretrained backbone weights download link: 1. [ddrnet23s_in1k_mmseg.pth](https://drive.google.com/file/d/1Ni4F1PMGGjuld-1S9fzDTmneLfpMuPTG/view?usp=sharing) 2. [ddrnet23_in1k_mmseg.pth](https://drive.google.com/file/d/11rsijC1xOWB6B0LgNQkAG-W6e1OdbCyJ/view?usp=sharing) ## To do - [x] support inference with converted official weights - [x] support training on cityscapes dataset --------- Co-authored-by: xiexinch <xiexinch@outlook.com>
2023-04-27 09:44:30 +08:00
- configs/ddrnet/metafile.yaml
[Dev] update update-model-index pre-commit hook (#2667)
2023-03-17 19:12:58 +08:00
- configs/deeplabv3/metafile.yaml
- configs/deeplabv3plus/metafile.yaml
- configs/dmnet/metafile.yaml
- configs/dnlnet/metafile.yaml
- configs/dpt/metafile.yaml
- configs/emanet/metafile.yaml
- configs/encnet/metafile.yaml
- configs/erfnet/metafile.yaml
- configs/fastfcn/metafile.yaml
- configs/fastscnn/metafile.yaml
- configs/fcn/metafile.yaml
- configs/gcnet/metafile.yaml
- configs/hrnet/metafile.yaml
- configs/icnet/metafile.yaml
- configs/isanet/metafile.yaml
- configs/knet/metafile.yaml
- configs/mae/metafile.yaml
- configs/mask2former/metafile.yaml
- configs/maskformer/metafile.yaml
- configs/mobilenet_v2/metafile.yaml
- configs/mobilenet_v3/metafile.yaml
- configs/nonlocal_net/metafile.yaml
- configs/ocrnet/metafile.yaml
- configs/pidnet/metafile.yaml
- configs/point_rend/metafile.yaml
- configs/poolformer/metafile.yaml
- configs/psanet/metafile.yaml
- configs/pspnet/metafile.yaml
- configs/resnest/metafile.yaml
[Dev] add san metafile (#3353)
2023-09-26 18:39:21 +08:00
- configs/san/metafile.yaml
[Dev] update update-model-index pre-commit hook (#2667)
2023-03-17 19:12:58 +08:00
- configs/segformer/metafile.yaml
- configs/segmenter/metafile.yaml
- configs/segnext/metafile.yaml
- configs/sem_fpn/metafile.yaml
- configs/setr/metafile.yaml
- configs/stdc/metafile.yaml
- configs/swin/metafile.yaml
- configs/twins/metafile.yaml
- configs/unet/metafile.yaml
- configs/upernet/metafile.yaml
- configs/vit/metafile.yaml
[Feature] Support inference and visualization of VPD (#3331) 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 Support inference and visualization of VPD ## Modification 1. add a new VPD model that does not generate black border in predictions 2. update `SegLocalVisualizer` to support depth visualization 3. update `MMSegInferencer` to support save predictions of depth estimation in method `postprocess` ## BC-breaking (Optional) Does the modification introduce changes that break the backward-compatibility of the downstream repos? If so, please describe how it breaks the compatibility and how the downstream projects should modify their code to keep compatibility with this PR. ## Use cases (Optional) Run inference with VPD using the this command ```sh python demo/image_demo_with_inferencer.py demo/classroom__rgb_00283.jpg vpd_depth --out-dir vis_results ``` The following image will be saved under `vis_results/vis` ![classroom__rgb_00283](https://github.com/open-mmlab/mmsegmentation/assets/26127467/051e8c4b-8f92-495f-8c3e-f249aac888e3) ## Checklist 1. Pre-commit or other linting tools are used to fix the potential lint issues. 4. The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness. 5. If the modification has potential influence on downstream projects, this PR should be tested with downstream projects, like MMDet or MMDet3D. 6. The documentation has been modified accordingly, like docstring or example tutorials.
2023-09-18 20:27:24 +08:00
- configs/vpd/metafile.yaml