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# ADE20K
Introduced by Zhou et al. in [Scene Parsing Through ADE20K Dataset](https://paperswithcode.com/paper/scene-parsing-through-ade20k-dataset).
The ADE20K semantic segmentation dataset contains more than 20K scene-centric images exhaustively annotated with pixel-level objects and object parts labels. There are totally 150 semantic categories, which include stuffs like sky, road, grass, and discrete objects like person, car, bed.
## Model Zoo
### UperNet + InternImage
| backbone | resolution | mIoU (ss/ms) | Config | Download |
|:--------------:|:----------:|:-----------:|:-----------:|:----------:
| FlashInternImage-T | 512x512 | 49.3 / 50.3 | [config](./upernet_flash_internimage_t_512_160k_ade20k.py) | [ckpt](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/upernet_flash_internimage_t_512_160k_ade20k.pth) \| [log](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/upernet_flash_internimage_t_512_160k_ade20k.log) |
| FlashInternImage-S | 512x512 | 50.6 / 51.6 | [config](./upernet_flash_internimage_s_512_160k_ade20k.py) | [ckpt](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/upernet_flash_internimage_s_512_160k_ade20k.pth) \| [log](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/upernet_flash_internimage_s_512_160k_ade20k.log) |
| FlashInternImage-B | 512x512 | 52.0 / 52.6 | [config](./upernet_flash_internimage_b_512_160k_ade20k.py) | [ckpt](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/upernet_flash_internimage_b_512_160k_ade20k.pth) \| [log](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/upernet_flash_internimage_s_512_160k_ade20k.log) |
| FlashInternImage-L | 640x640 | 55.6 / 56.0 | [config](./upernet_flash_internimage_l_640_160k_ade20k.py)| [ckpt](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/upernet_flash_internimage_l_640_160k_ade20k.pth) \| [log](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/upernet_flash_internimage_l_640_160k_ade20k.log) |
- Training speed is measured with A100 GPU.
- Please set `with_cp=True` to save memory if you meet `out-of-memory` issues.
- The logs are our recent newly trained ones. There are slight differences between the results in logs and our paper.
### Mask2Former + InternImage
| backbone | resolution | mIoU (ss) | Config | Download |
|:--------------:|:----------:|:-----------:|:-----------:|:----------:
| FlashInternImage-T | 512x512 | 51.2 | [config](./mask2former_flash_internimage_t_512_160k_ade20k_ss.py) | [ckpt](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/mask2former_flash_internimage_t_512_160k_ade20k_ss.pth) \| [log](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/mask2former_flash_internimage_t_512_160k_ade20k_ss.log) |
| FlashInternImage-S | 640x640 | 52.2 | [config](./mask2former_flash_internimage_s_640_160k_ade20k_ss.py) | [ckpt](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/mask2former_flash_internimage_s_640_160k_ade20k_ss.pth) \| [log](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/mask2former_flash_internimage_s_640_160k_ade20k_ss.log) |
| FlashInternImage-B | 640x640 | 53.4 | [config](./mask2former_flash_internimage_b_640_160k_ade20k_ss.py) | [ckpt](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/mask2former_flash_internimage_b_640_160k_ade20k_ss.pth) \| [log](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/mask2former_flash_internimage_b_640_160k_ade20k_ss.log) |
| FlashInternImage-L | 640x640 | 56.7 | [config](./mask2former_flash_internimage_l_640_160k_ade20k_ss.py)| [ckpt](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/mask2former_flash_internimage_l_640_160k_ade20k_ss.pth) \| [log](https://huggingface.co/OpenGVLab/DCNv4/resolve/main/mask2former_flash_internimage_l_640_160k_ade20k_ss.log) |