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PaddleSeg
提交 12017afd 编写于 作者: C chenguowei01
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add resnet_vd backbone

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docs/model_zoo.md
浏览文件 @ 12017afd
...@@ -37,6 +37,7 @@ PaddleSeg对所有内置的分割模型都提供了公开数据集下的预训 ...@@ -37,6 +37,7 @@ PaddleSeg对所有内置的分割模型都提供了公开数据集下的预训
|---|---|---|---| |---|---|---|---|
| ResNet50（适配PSPNet） | ImageNet | [resnet50_v2_pspnet](https://paddleseg.bj.bcebos.com/resnet50_v2_pspnet.tgz)| -- | | ResNet50（适配PSPNet） | ImageNet | [resnet50_v2_pspnet](https://paddleseg.bj.bcebos.com/resnet50_v2_pspnet.tgz)| -- |
| ResNet101（适配PSPNet） | ImageNet | [resnet101_v2_pspnet](https://paddleseg.bj.bcebos.com/resnet101_v2_pspnet.tgz)| -- | | ResNet101（适配PSPNet） | ImageNet | [resnet101_v2_pspnet](https://paddleseg.bj.bcebos.com/resnet101_v2_pspnet.tgz)| -- |
| ResNet50_vd | ImageNet | [ResNet50_vd_ssld_pretrained.tgz](https://paddleseg.bj.bcebos.com/models/ResNet50_vd_ssld_pretrained.tgz) | 83.0%/96.4% |
## COCO预训练模型 ## COCO预训练模型
...@@ -58,7 +59,8 @@ train数据集合为Cityscapes训练集合，测试为Cityscapes的验证集合 ...@@ -58,7 +59,8 @@ train数据集合为Cityscapes训练集合，测试为Cityscapes的验证集合
|---|---|---|---|---|---| |---|---|---|---|---|---|
| DeepLabv3+/MobileNetv2/bn | Cityscapes |[mobilenet_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/mobilenet_cityscapes.tgz) |16|false| 0.698| | DeepLabv3+/MobileNetv2/bn | Cityscapes |[mobilenet_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/mobilenet_cityscapes.tgz) |16|false| 0.698|
| DeepLabv3+/Xception65/gn | Cityscapes |[deeplabv3p_xception65_gn_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/deeplabv3p_xception65_cityscapes.tgz) |16|false| 0.7824 | | DeepLabv3+/Xception65/gn | Cityscapes |[deeplabv3p_xception65_gn_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/deeplabv3p_xception65_cityscapes.tgz) |16|false| 0.7824 |
| DeepLabv3+/Xception65/bn | Cityscapes |[deeplabv3p_xception65_bn_cityscapes_.tgz](https://paddleseg.bj.bcebos.com/models/xception65_bn_cityscapes.tgz) | 16 | false | 0.7930 | | DeepLabv3+/Xception65/bn | Cityscapes |[deeplabv3p_xception65_bn_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/xception65_bn_cityscapes.tgz) | 16 | false | 0.7930 |
| DeepLabv3+/ResNet50_vd/bn | Cityscapes |[deeplabv3p_resnet50_vd_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/deeplabv3p_resnet50_vd_cityscapes.tgz) | 16 | false | 0.8006 |
| ICNet/bn | Cityscapes |[icnet_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/icnet_cityscapes.tar.gz) |16|false| 0.6831 | | ICNet/bn | Cityscapes |[icnet_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/icnet_cityscapes.tar.gz) |16|false| 0.6831 |
| PSPNet/bn | Cityscapes |[pspnet50_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/pspnet50_cityscapes.tgz) |16|false| 0.7013 | | PSPNet/bn | Cityscapes |[pspnet50_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/pspnet50_cityscapes.tgz) |16|false| 0.7013 |
| PSPNet/bn | Cityscapes |[pspnet101_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/pspnet101_cityscapes.tgz) |16|false| 0.7734 | | PSPNet/bn | Cityscapes |[pspnet101_cityscapes.tgz](https://paddleseg.bj.bcebos.com/models/pspnet101_cityscapes.tgz) |16|false| 0.7734 |
......
pretrained_model/download_model.py
浏览文件 @ 12017afd
...@@ -42,6 +42,8 @@ model_urls = { ...@@ -42,6 +42,8 @@ model_urls = {
"https://paddleseg.bj.bcebos.com/models/Xception41_pretrained.tgz", "https://paddleseg.bj.bcebos.com/models/Xception41_pretrained.tgz",
"xception65_imagenet": "xception65_imagenet":
"https://paddleseg.bj.bcebos.com/models/Xception65_pretrained.tgz", "https://paddleseg.bj.bcebos.com/models/Xception65_pretrained.tgz",
"resnet50_vd_imagenet":
"https://paddleseg.bj.bcebos.com/models/ResNet50_vd_ssld_pretrained.tgz",
"hrnet_w18_bn_imagenet": "hrnet_w18_bn_imagenet":
"https://paddleseg.bj.bcebos.com/models/hrnet_w18_imagenet.tar", "https://paddleseg.bj.bcebos.com/models/hrnet_w18_imagenet.tar",
"hrnet_w30_bn_imagenet": "hrnet_w30_bn_imagenet":
...@@ -76,6 +78,8 @@ model_urls = { ...@@ -76,6 +78,8 @@ model_urls = {
"https://paddleseg.bj.bcebos.com/models/deeplabv3p_xception65_cityscapes.tgz", "https://paddleseg.bj.bcebos.com/models/deeplabv3p_xception65_cityscapes.tgz",
"deeplabv3p_xception65_bn_cityscapes": "deeplabv3p_xception65_bn_cityscapes":
"https://paddleseg.bj.bcebos.com/models/xception65_bn_cityscapes.tgz", "https://paddleseg.bj.bcebos.com/models/xception65_bn_cityscapes.tgz",
"deeplabv3p_resnet50_vd_cityscapes":
"https://paddleseg.bj.bcebos.com/models/deeplabv3p_resnet50_vd_cityscapes.tgz",
"unet_bn_coco": "unet_bn_coco":
"https://paddleseg.bj.bcebos.com/models/unet_coco_v3.tgz", "https://paddleseg.bj.bcebos.com/models/unet_coco_v3.tgz",
"icnet_bn_cityscapes": "icnet_bn_cityscapes":
......
turtorial/finetune_deeplabv3plus.md
浏览文件 @ 12017afd
...@@ -145,8 +145,10 @@ PaddleSeg在AI Studio平台上提供了在线体验的DeepLabv3+图像分割教 ...@@ -145,8 +145,10 @@ PaddleSeg在AI Studio平台上提供了在线体验的DeepLabv3+图像分割教
|mobilenetv2-0-25_bn_imagenet|MobileNetV2|bn|ImageNet|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: mobilenetv2 <br> MODEL.DEEPLAB.DEPTH_MULTIPLIER: 0.25 <br> MODEL.DEFAULT_NORM_TYPE: bn| |mobilenetv2-0-25_bn_imagenet|MobileNetV2|bn|ImageNet|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: mobilenetv2 <br> MODEL.DEEPLAB.DEPTH_MULTIPLIER: 0.25 <br> MODEL.DEFAULT_NORM_TYPE: bn|
|xception41_imagenet|Xception41|bn|ImageNet|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_41 <br> MODEL.DEFAULT_NORM_TYPE: bn| |xception41_imagenet|Xception41|bn|ImageNet|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_41 <br> MODEL.DEFAULT_NORM_TYPE: bn|
|xception65_imagenet|Xception65|bn|ImageNet|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_65 <br> MODEL.DEFAULT_NORM_TYPE: bn| |xception65_imagenet|Xception65|bn|ImageNet|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_65 <br> MODEL.DEFAULT_NORM_TYPE: bn|
|ResNet50_vd_ssld_pretrained|ResNet50_vd|bn|ImageNet|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: resnet50_vd <br> MODEL.DEFAULT_NORM_TYPE: bn|
|deeplabv3p_mobilenetv2-1-0_bn_coco|MobileNetV2|bn|COCO|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: mobilenetv2 <br> MODEL.DEEPLAB.DEPTH_MULTIPLIER: 1.0 <br> MODEL.DEEPLAB.ENCODER_WITH_ASPP: False <br> MODEL.DEEPLAB.ENABLE_DECODER: False <br> MODEL.DEFAULT_NORM_TYPE: bn| |deeplabv3p_mobilenetv2-1-0_bn_coco|MobileNetV2|bn|COCO|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: mobilenetv2 <br> MODEL.DEEPLAB.DEPTH_MULTIPLIER: 1.0 <br> MODEL.DEEPLAB.ENCODER_WITH_ASPP: False <br> MODEL.DEEPLAB.ENABLE_DECODER: False <br> MODEL.DEFAULT_NORM_TYPE: bn|
|**deeplabv3p_xception65_bn_coco**|Xception65|bn|COCO|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_65 <br> MODEL.DEFAULT_NORM_TYPE: bn | |**deeplabv3p_xception65_bn_coco**|Xception65|bn|COCO|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_65 <br> MODEL.DEFAULT_NORM_TYPE: bn |
|deeplabv3p_mobilenetv2-1-0_bn_cityscapes|MobileNetV2|bn|Cityscapes|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: mobilenetv2 <br> MODEL.DEEPLAB.DEPTH_MULTIPLIER: 1.0 <br> MODEL.DEEPLAB.ENCODER_WITH_ASPP: False <br> MODEL.DEEPLAB.ENABLE_DECODER: False <br> MODEL.DEFAULT_NORM_TYPE: bn| |deeplabv3p_mobilenetv2-1-0_bn_cityscapes|MobileNetV2|bn|Cityscapes|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: mobilenetv2 <br> MODEL.DEEPLAB.DEPTH_MULTIPLIER: 1.0 <br> MODEL.DEEPLAB.ENCODER_WITH_ASPP: False <br> MODEL.DEEPLAB.ENABLE_DECODER: False <br> MODEL.DEFAULT_NORM_TYPE: bn|
|deeplabv3p_xception65_gn_cityscapes|Xception65|gn|Cityscapes|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_65 <br> MODEL.DEFAULT_NORM_TYPE: gn| |deeplabv3p_xception65_gn_cityscapes|Xception65|gn|Cityscapes|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_65 <br> MODEL.DEFAULT_NORM_TYPE: gn|
|deeplabv3p_xception65_bn_cityscapes|Xception65|bn|Cityscapes|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_65 <br> MODEL.DEFAULT_NORM_TYPE: bn| |deeplabv3p_xception65_bn_cityscapes|Xception65|bn|Cityscapes|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: xception_65 <br> MODEL.DEFAULT_NORM_TYPE: bn|
|deeplabv3p_resnet50_vd_cityscapes|resnet50_vd|bn|Cityscapes|MODEL.MODEL_NAME: deeplabv3p <br> MODEL.DEEPLAB.BACKBONE: resnet50_vd <br> MODEL.DEFAULT_NORM_TYPE: bn|
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