Add docs for keras2ncnn tools (#2286)

* Add readme for keras2ncnn

* Add supported model variants

* Fix supported model variants

README.md

@@ -107,7 +107,7 @@ ncnn 是一个为手机端极致优化的高性能神经网络前向计算框架
 * Supports multi-core parallel computing acceleration, ARM big.LITTLE cpu scheduling optimization
 * Supports GPU acceleration via the next-generation low-overhead vulkan api
 * The overall library size is less than 700K, and can be easily reduced to less than 300K
-* Extensible model design, supports 8bit quantization and half-precision floating point storage, can import caffe/pytorch/mxnet/onnx/darknet models
+* Extensible model design, supports 8bit quantization and half-precision floating point storage, can import caffe/pytorch/mxnet/onnx/darknet/keras/tensorflow(mlir) models
 * Support direct memory zero copy reference load network model
 * Can be registered with custom layer implementation and extended
 * Well, it is strong, not afraid of being stuffed with 卷   QvQ
@@ -122,7 +122,7 @@ ncnn 是一个为手机端极致优化的高性能神经网络前向计算框架
 * 支持多核并行计算加速，ARM big.LITTLE cpu 调度优化
 * 支持基于全新低消耗的 vulkan api GPU 加速
 * 整体库体积小于 700K，并可轻松精简到小于 300K
-* 可扩展的模型设计，支持 8bit 量化和半精度浮点存储，可导入 caffe/pytorch/mxnet/onnx/darknet 模型
+* 可扩展的模型设计，支持 8bit 量化和半精度浮点存储，可导入 caffe/pytorch/mxnet/onnx/darknet/keras/tensorflow(mlir) 模型
 * 支持直接内存零拷贝引用加载网络模型
 * 可注册自定义层实现并扩展
 * 恩，很强就是了，不怕被塞卷 QvQ

tools/keras/readme.md

@@ -0,0 +1,10 @@
+## You can find keras2ncnn tools here
+
+[https://github.com/MarsTechHAN/keras2ncnn](https://github.com/MarsTechHAN/keras2ncnn)  
+[https://github.com/azeme1/keras2ncnn](https://github.com/azeme1/keras2ncnn)
+
+----
+### From tensorflow 2.x, you can also export mlir and use mlir2ncnn which is maintaince by the official.
+
+The source code is located here: [https://github.com/Tencent/ncnn/tree/master/tools/mlir](https://github.com/Tencent/ncnn/tree/master/tools/mlir)  
+For Chinese, you can refer the guide here [https://zhuanlan.zhihu.com/p/152535430](https://zhuanlan.zhihu.com/p/152535430)