Spaces:
Runtime error
Runtime error
| Models: | |
| - Name: mobilenet-v2-d8_fcn_4xb2-80k_cityscapes-512x1024 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 71.19 | |
| mIoU(ms+flip): 73.34 | |
| Config: configs/mobilenet_v2/mobilenet-v2-d8_fcn_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - M-V2-D8 | |
| - FCN | |
| Training Resources: 4x A100 GPUS | |
| Memory (GB): 3.4 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/mobilenet-v2-d8_fcn_4xb2-80k_cityscapes-512x1024/mobilenet-v2-d8_fcn_4xb2-80k_cityscapes-512x1024-20230224_185436-13fef4ea.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/mobilenet-v2-d8_fcn_4xb2-80k_cityscapes-512x1024/mobilenet-v2-d8_fcn_4xb2-80k_cityscapes-512x1024_20230224_185436.json | |
| Paper: | |
| Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks' | |
| URL: https://arxiv.org/abs/1801.04381 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mobilenet_v2.py#L14 | |
| Framework: PyTorch | |
| - Name: mobilenet-v2-d8_pspnet_4xb2-80k_cityscapes-512x1024 | |
| In Collection: PSPNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 70.23 | |
| Config: configs/mobilenet_v2/mobilenet-v2-d8_pspnet_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - M-V2-D8 | |
| - PSPNet | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 3.6 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/pspnet_m-v2-d8_512x1024_80k_cityscapes/pspnet_m-v2-d8_512x1024_80k_cityscapes_20200825_124817-19e81d51.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/pspnet_m-v2-d8_512x1024_80k_cityscapes/pspnet_m-v2-d8_512x1024_80k_cityscapes-20200825_124817.log.json | |
| Paper: | |
| Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks' | |
| URL: https://arxiv.org/abs/1801.04381 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mobilenet_v2.py#L14 | |
| Framework: PyTorch | |
| - Name: mobilenet-v2-d8_deeplabv3_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 73.84 | |
| Config: configs/mobilenet_v2/mobilenet-v2-d8_deeplabv3_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - M-V2-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 3.9 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3_m-v2-d8_512x1024_80k_cityscapes/deeplabv3_m-v2-d8_512x1024_80k_cityscapes_20200825_124836-bef03590.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3_m-v2-d8_512x1024_80k_cityscapes/deeplabv3_m-v2-d8_512x1024_80k_cityscapes-20200825_124836.log.json | |
| Paper: | |
| Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks' | |
| URL: https://arxiv.org/abs/1801.04381 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mobilenet_v2.py#L14 | |
| Framework: PyTorch | |
| - Name: mobilenet-v2-d8_deeplabv3plus_4xb2-80k_cityscapes-512x1024 | |
| In Collection: DeepLabV3+ | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: Cityscapes | |
| Metrics: | |
| mIoU: 75.2 | |
| Config: configs/mobilenet_v2/mobilenet-v2-d8_deeplabv3plus_4xb2-80k_cityscapes-512x1024.py | |
| Metadata: | |
| Training Data: Cityscapes | |
| Batch Size: 8 | |
| Architecture: | |
| - M-V2-D8 | |
| - DeepLabV3+ | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 5.1 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes_20200825_124836-d256dd4b.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes-20200825_124836.log.json | |
| Paper: | |
| Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks' | |
| URL: https://arxiv.org/abs/1801.04381 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mobilenet_v2.py#L14 | |
| Framework: PyTorch | |
| - Name: mobilenet-v2-d8_fcn_4xb4-160k_ade20k-512x512 | |
| In Collection: FCN | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 19.71 | |
| Config: configs/mobilenet_v2/mobilenet-v2-d8_fcn_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - M-V2-D8 | |
| - FCN | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.5 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/fcn_m-v2-d8_512x512_160k_ade20k/fcn_m-v2-d8_512x512_160k_ade20k_20200825_214953-c40e1095.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/fcn_m-v2-d8_512x512_160k_ade20k/fcn_m-v2-d8_512x512_160k_ade20k-20200825_214953.log.json | |
| Paper: | |
| Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks' | |
| URL: https://arxiv.org/abs/1801.04381 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mobilenet_v2.py#L14 | |
| Framework: PyTorch | |
| - Name: mobilenet-v2-d8_pspnet_4xb4-160k_ade20k-512x512 | |
| In Collection: PSPNet | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 29.68 | |
| Config: configs/mobilenet_v2/mobilenet-v2-d8_pspnet_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - M-V2-D8 | |
| - PSPNet | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.5 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k/pspnet_m-v2-d8_512x512_160k_ade20k_20200825_214953-f5942f7a.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k/pspnet_m-v2-d8_512x512_160k_ade20k-20200825_214953.log.json | |
| Paper: | |
| Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks' | |
| URL: https://arxiv.org/abs/1801.04381 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mobilenet_v2.py#L14 | |
| Framework: PyTorch | |
| - Name: mobilenet-v2-d8_deeplabv3_4xb4-160k_ade20k-512x512 | |
| In Collection: DeepLabV3 | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 34.08 | |
| Config: configs/mobilenet_v2/mobilenet-v2-d8_deeplabv3_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - M-V2-D8 | |
| - DeepLabV3 | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 6.8 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3_m-v2-d8_512x512_160k_ade20k/deeplabv3_m-v2-d8_512x512_160k_ade20k_20200825_223255-63986343.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3_m-v2-d8_512x512_160k_ade20k/deeplabv3_m-v2-d8_512x512_160k_ade20k-20200825_223255.log.json | |
| Paper: | |
| Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks' | |
| URL: https://arxiv.org/abs/1801.04381 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mobilenet_v2.py#L14 | |
| Framework: PyTorch | |
| - Name: mobilenet-v2-d8_deeplabv3plus_4xb4-160k_ade20k-512x512 | |
| In Collection: DeepLabV3+ | |
| Results: | |
| Task: Semantic Segmentation | |
| Dataset: ADE20K | |
| Metrics: | |
| mIoU: 34.02 | |
| Config: configs/mobilenet_v2/mobilenet-v2-d8_deeplabv3plus_4xb4-160k_ade20k-512x512.py | |
| Metadata: | |
| Training Data: ADE20K | |
| Batch Size: 16 | |
| Architecture: | |
| - M-V2-D8 | |
| - DeepLabV3+ | |
| Training Resources: 4x V100 GPUS | |
| Memory (GB): 8.2 | |
| Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3plus_m-v2-d8_512x512_160k_ade20k/deeplabv3plus_m-v2-d8_512x512_160k_ade20k_20200825_223255-465a01d4.pth | |
| Training log: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v2/deeplabv3plus_m-v2-d8_512x512_160k_ade20k/deeplabv3plus_m-v2-d8_512x512_160k_ade20k-20200825_223255.log.json | |
| Paper: | |
| Title: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks' | |
| URL: https://arxiv.org/abs/1801.04381 | |
| Code: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mobilenet_v2.py#L14 | |
| Framework: PyTorch | |