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4.13 kB
| Collections: | |
| - Name: Segmenter | |
| Metadata: | |
| Training Data: | |
| - ADE20K | |
| Paper: | |
| URL: https://arxiv.org/abs/2105.05633 | |
| Title: 'Segmenter: Transformer for Semantic Segmentation' | |
| README: configs/segmenter/README.md | |
| Code: | |
| URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.21.0/mmseg/models/decode_heads/segmenter_mask_head.py#L15 | |
| Version: v0.21.0 | |
| Converted From: | |
| Code: https://github.com/rstrudel/segmenter | |
| Models: | |
| - Name: segmenter_vit-t_mask_8x1_512x512_160k_ade20k | |
| In Collection: Segmenter | |
| Metadata: | |
| backbone: ViT-T_16 | |
| crop size: (512,512) | |
| lr schd: 160000 | |
| inference time (ms/im): | |
| - value: 35.74 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (512,512) | |
| Training Memory (GB): 1.21 | |
| Results: | |
| - Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 39.99 | |
| mIoU(ms+flip): 40.83 | |
| Config: configs/segmenter/segmenter_vit-t_mask_8x1_512x512_160k_ade20k.py | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-t_mask_8x1_512x512_160k_ade20k/segmenter_vit-t_mask_8x1_512x512_160k_ade20k_20220105_151706-ffcf7509.pth | |
| - Name: segmenter_vit-s_linear_8x1_512x512_160k_ade20k | |
| In Collection: Segmenter | |
| Metadata: | |
| backbone: ViT-S_16 | |
| crop size: (512,512) | |
| lr schd: 160000 | |
| inference time (ms/im): | |
| - value: 35.63 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (512,512) | |
| Training Memory (GB): 1.78 | |
| Results: | |
| - Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 45.75 | |
| mIoU(ms+flip): 46.82 | |
| Config: configs/segmenter/segmenter_vit-s_linear_8x1_512x512_160k_ade20k.py | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_linear_8x1_512x512_160k_ade20k/segmenter_vit-s_linear_8x1_512x512_160k_ade20k_20220105_151713-39658c46.pth | |
| - Name: segmenter_vit-s_mask_8x1_512x512_160k_ade20k | |
| In Collection: Segmenter | |
| Metadata: | |
| backbone: ViT-S_16 | |
| crop size: (512,512) | |
| lr schd: 160000 | |
| inference time (ms/im): | |
| - value: 40.32 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (512,512) | |
| Training Memory (GB): 2.03 | |
| Results: | |
| - Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 46.19 | |
| mIoU(ms+flip): 47.85 | |
| Config: configs/segmenter/segmenter_vit-s_mask_8x1_512x512_160k_ade20k.py | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-s_mask_8x1_512x512_160k_ade20k/segmenter_vit-s_mask_8x1_512x512_160k_ade20k_20220105_151706-511bb103.pth | |
| - Name: segmenter_vit-b_mask_8x1_512x512_160k_ade20k | |
| In Collection: Segmenter | |
| Metadata: | |
| backbone: ViT-B_16 | |
| crop size: (512,512) | |
| lr schd: 160000 | |
| inference time (ms/im): | |
| - value: 75.76 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (512,512) | |
| Training Memory (GB): 4.2 | |
| Results: | |
| - Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 49.6 | |
| mIoU(ms+flip): 51.07 | |
| Config: configs/segmenter/segmenter_vit-b_mask_8x1_512x512_160k_ade20k.py | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-b_mask_8x1_512x512_160k_ade20k/segmenter_vit-b_mask_8x1_512x512_160k_ade20k_20220105_151706-bc533b08.pth | |
| - Name: segmenter_vit-l_mask_8x1_512x512_160k_ade20k | |
| In Collection: Segmenter | |
| Metadata: | |
| backbone: ViT-L_16 | |
| crop size: (640,640) | |
| lr schd: 160000 | |
| inference time (ms/im): | |
| - value: 381.68 | |
| hardware: V100 | |
| backend: PyTorch | |
| batch size: 1 | |
| mode: FP32 | |
| resolution: (640,640) | |
| Training Memory (GB): 16.56 | |
| Results: | |
| - Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 52.16 | |
| mIoU(ms+flip): 53.65 | |
| Config: configs/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k.py | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segmenter/segmenter_vit-l_mask_8x1_512x512_160k_ade20k/segmenter_vit-l_mask_8x1_512x512_160k_ade20k_20220105_162750-7ef345be.pth | |