提交 a52ee64d 编写于 作者: L LDOUBLEV

fix lite readme

上级 2ee12253
......@@ -18,7 +18,7 @@ Paddle Lite是飞桨轻量化推理引擎,为手机、IOT端提供高效推理
1. [Docker](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#docker)
2. [Linux](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#android)
3. [MAC OS](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#id13)
4. [Windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#windows)
4. [Windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#id4)
### 1.2 准备预测库
......@@ -84,7 +84,7 @@ Paddle-Lite 提供了多种策略来自动优化原始的模型,其中包括
|模型简介|检测模型|识别模型|Paddle-Lite版本|
|-|-|-|-|
|超轻量级中文OCR opt优化模型|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_det_mv3_db_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_rec_mv3_crnn_opt.nb)|2.6.1|
|超轻量级中文OCR opt优化模型|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_det_mv3_db_opt.nb)|[下载地址](https://paddleocr.bj.bcebos.com/deploy/lite/ch_rec_mv3_crnn_opt.nb)|develop|
如果直接使用上述表格中的模型进行部署,可略过下述步骤,直接阅读 [2.2节](#2.2与手机联调)
......
......@@ -17,7 +17,7 @@ deployment solutions for end-side deployment issues.
[build for Docker](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#docker)
[build for Linux](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#android)
[build for MAC OS](https://paddle-lite.readthedocs.io/zh/latest/user_guides/source_compile.html#id13)
[build for windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#windows)
[build for windows](https://paddle-lite.readthedocs.io/zh/latest/demo_guides/x86.html#id4)
## 3. Download prebuild library for android and ios
......
......@@ -78,7 +78,7 @@ class MobileNetV3():
supported_scale = [0.35, 0.5, 0.75, 1.0, 1.25]
assert self.scale in supported_scale, \
"supported scale are {} but input scale is {}".format(supported_scale, scale)
"supported scale are {} but input scale is {}".format(supported_scale, self.scale)
def __call__(self, input):
scale = self.scale
......
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