未验证 提交 634ac9f9 编写于 作者: W wangguanzhong 提交者: GitHub

update doc on develop, test=document_fix (#2705)

* update doc on develop, test=document_fix

* update dependency of ppdet and paddle, test=document_fix

* update docs, test=document_fix
上级 765e80c0
...@@ -219,7 +219,8 @@ PaddleDetection模块化地实现了多种主流目标检测算法,提供了 ...@@ -219,7 +219,8 @@ PaddleDetection模块化地实现了多种主流目标检测算法,提供了
- [PP-YOLO模型](configs/ppyolo/README_cn.md) - [PP-YOLO模型](configs/ppyolo/README_cn.md)
- [676类目标检测](static/docs/featured_model/LARGE_SCALE_DET_MODEL.md) - [676类目标检测](static/docs/featured_model/LARGE_SCALE_DET_MODEL.md)
- [两阶段实用模型PSS-Det](configs/rcnn_enhance/README.md) - [两阶段实用模型PSS-Det](configs/rcnn_enhance/README.md)
- [TTFNet](configs/ttfnet/README.md) - [增强版Anchor Free模型TTFNet](configs/ttfnet/README.md)
- [半监督知识蒸馏预训练检测模型](docs/feature_models/SSLD_PRETRAINED_MODEL.md)
- 通用实例分割 - 通用实例分割
- [SOLOv2](configs/solov2/README.md) - [SOLOv2](configs/solov2/README.md)
- 旋转框检测 - 旋转框检测
......
...@@ -232,7 +232,8 @@ The relationship between COCO mAP and FPS on Tesla V100 of representative models ...@@ -232,7 +232,8 @@ The relationship between COCO mAP and FPS on Tesla V100 of representative models
- [PP-YOLO](configs/ppyolo/README.md) - [PP-YOLO](configs/ppyolo/README.md)
- [676 classes of object detection](static/docs/featured_model/LARGE_SCALE_DET_MODEL.md) - [676 classes of object detection](static/docs/featured_model/LARGE_SCALE_DET_MODEL.md)
- [Two-stage practical PSS-Det](configs/rcnn_enhance/README.md) - [Two-stage practical PSS-Det](configs/rcnn_enhance/README.md)
- [TTFNet](configs/ttfnet/README.md) - [Enhanced Anchor Free model--TTFNet](configs/ttfnet/README.md)
- [SSLD pretrained models](docs/feature_models/SSLD_PRETRAINED_MODEL_en.md)
- Universal instance segmentation - Universal instance segmentation
- [SOLOv2](configs/solov2/README.md) - [SOLOv2](configs/solov2/README.md)
- Rotation object detection - Rotation object detection
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...@@ -10,12 +10,11 @@ FCOS (Fully Convolutional One-Stage Object Detection) is a fast anchor-free obje ...@@ -10,12 +10,11 @@ FCOS (Fully Convolutional One-Stage Object Detection) is a fast anchor-free obje
## Model Zoo ## Model Zoo
| 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 | | Backbone | Model | images/GPU | lr schedule |FPS | Box AP | download | config |
| :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: | | :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
| ResNet50-FPN | FCOS | 2 | 1x | ---- | 39.6 | [下载链接](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_r50_fpn_1x_coco.yml) | | ResNet50-FPN | FCOS | 2 | 1x | ---- | 39.6 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_r50_fpn_1x_coco.yml) |
| ResNet50-FPN | FCOS+DCN | 2 | 1x | ---- | 44.3 | [下载链接](https://paddledet.bj.bcebos.com/models/fcos_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_dcn_r50_fpn_1x_coco.yml) | | ResNet50-FPN | FCOS+DCN | 2 | 1x | ---- | 44.3 | [download](https://paddledet.bj.bcebos.com/models/fcos_dcn_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_dcn_r50_fpn_1x_coco.yml) |
| ResNet50-FPN | FCOS+multiscale_train | 2 | 2x | ---- | 41.8 | [下载链接](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_multiscale_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_r50_fpn_multiscale_2x_coco.yml) | | ResNet50-FPN | FCOS+multiscale_train | 2 | 2x | ---- | 41.8 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_multiscale_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/fcos/fcos_r50_fpn_multiscale_2x_coco.yml) |
**Notes:** **Notes:**
- FCOS is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`. - FCOS is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
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...@@ -18,6 +18,17 @@ For general information about PaddleDetection, please see [README.md](https://gi ...@@ -18,6 +18,17 @@ For general information about PaddleDetection, please see [README.md](https://gi
- cuDNN >= 7.6 - cuDNN >= 7.6
Dependency of PaddleDetection and PaddlePaddle:
| PaddleDetection version | PaddlePaddle version | tips |
| :----------------: | :---------------: | :-------: |
| release/2.0 | >= 2.0.1 | Dygraph mode is set as default |
| release/2.0-rc | >= 2.0.1 | -- |
| release/0.5 | >= 1.8.4 | Cascade R-CNN and SOLOv2 depends on 2.0.0.rc |
| release/0.4 | >= 1.8.4 | PP-YOLO depends on 1.8.4 |
| release/0.3 | >=1.7 | -- |
## Instruction ## Instruction
### 1. Install PaddlePaddle ### 1. Install PaddlePaddle
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...@@ -14,6 +14,15 @@ ...@@ -14,6 +14,15 @@
- CUDA >= 9.0 - CUDA >= 9.0
- cuDNN >= 7.6 - cuDNN >= 7.6
PaddleDetection 依赖 PaddlePaddle 版本关系:
| PaddleDetection版本 | PaddlePaddle版本 | 备注 |
| :------------------: | :---------------: | :-------: |
| release/2.0 | >= 2.0.1 | 默认使用动态图模式 |
| release/2.0-rc | >= 2.0.1 | -- |
| release/0.5 | >= 1.8.4 | 大部分模型>=1.8.4即可运行,Cascade R-CNN系列模型与SOLOv2依赖2.0.0.rc版本 |
| release/0.4 | >= 1.8.4 | PP-YOLO依赖1.8.4 |
| release/0.3 | >=1.7 | -- |
## 安装说明 ## 安装说明
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...@@ -68,7 +68,7 @@ def parse_args(): ...@@ -68,7 +68,7 @@ def parse_args():
"--use_vdl", "--use_vdl",
type=bool, type=bool,
default=False, default=False,
help="whether to record the data to VisualDL.") help="Whether to record the data to VisualDL.")
parser.add_argument( parser.add_argument(
'--vdl_log_dir', '--vdl_log_dir',
type=str, type=str,
...@@ -78,7 +78,7 @@ def parse_args(): ...@@ -78,7 +78,7 @@ def parse_args():
"--save_txt", "--save_txt",
type=bool, type=bool,
default=False, default=False,
help="whether to record the data to VisualDL.") help="Whether to save inference result in txt.")
args = parser.parse_args() args = parser.parse_args()
return args return args
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