提交 ba365ae8 编写于 作者: C chenguowei01

update README.md

上级 7892521b
......@@ -18,14 +18,15 @@ $ pip install -r requirements.txt
## 模型
| 模型类型 | 预训练模型 | 导出模型 | 量化模型 | 说明 |
| --- | --- | --- | --- | --- |
| HumanSegServer | [humanseg_server]() | [humanseg_server_export]() | [humanseg_server_quant]() | 服务端GPU环境 |
| HumanSegMobile | [humanseg_mobile]() | [humanseg_mobile_export]() | [humanseg_mobile_quant]() | 小模型, 适合轻量级计算环境 |
| HumanSegLite | [humanseg_lite]() | [humanseg_lite_export]() | [humanseg_lite_quant]() | 小模型, 适合轻量级计算环境 |
| HumanSegServer | [humanseg_server](https://paddleseg.bj.bcebos.com/humanseg/models/humanseg_server.zip) | [humanseg_server_export](https://paddleseg.bj.bcebos.com/humanseg/models/humanseg_server_export.zip) | [humanseg_server_quant](https://paddleseg.bj.bcebos.com/humanseg/models/humanseg_server_quant.zip) | 服务端GPU环境 |
| HumanSegMobile | [humanseg_mobile](https://paddleseg.bj.bcebos.com/humanseg/models/humanseg_mobile.zip) | [humanseg_mobile_export](https://paddleseg.bj.bcebos.com/humanseg/models/humanseg_mobile_export.zip) | [humanseg_mobile_quant](https://paddleseg.bj.bcebos.com/humanseg/models/humanseg_mobile_quant.zip) | 小模型, 适合轻量级计算环境 |
| HumanSegLite | [humanseg_lite](https://paddleseg.bj.bcebos.com/humanseg/models/humanseg_lite.zip) | [humanseg_lite_export](https://paddleseg.bj.bcebos.com/humanseg/models/humanseg_lite_export.zip) | [humanseg_lite_quant](https://paddleseg.bj.bcebos.com/humanseg/models/humanseg_lite_quant.zip) | 小模型, 适合轻量级计算环境 |
## 视频流分割
## 指定运行设备
```bash
python video_infer.py --model_dir path/to/model_dir
export CUDA_VISIBLE_DEVICES=0
```
当CUDA_VISIBLE_DEVICES变量有效时,使用相应的显卡进行计算,无效时使用CPU进行计算
## 准备训练数据
我们提供了一份demo数据集,通过运行以下代码进行下载,该数据集是从supervise.ly抽取的一个小数据集。
......@@ -40,10 +41,15 @@ python data/download_data.py
python pretrained_weights/download_pretrained_weights.py
```
## 视频流分割
```bash
python video_infer.py --model_dir path/to/model_dir
```
## 训练
使用下述命令进行训练
```bash
CUDA_VISIBLE_DEVICES=0 && python train.py --model_type HumanSegMobile \
python train.py --model_type HumanSegMobile \
--save_dir output/ \
--data_dir data/mini_supervisely \
--train_list data/mini_supervisely/train.txt \
......
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