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Update README.md (#82)

Lutz Roeder vor 8 Jahren
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      README.md

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README.md

@@ -1,9 +1,11 @@
 
 <p align='center'><img width='400' src='media/logo.png'/></p>
 
-Netron is a viewer for neural network and machine learning models.
+Netron is a viewer for neural network and machine learning models. 
 
-Netron loads **[ONNX](http://onnx.ai)** models (`.onnx` or `.pb`), **Keras** models (`.keras`, `.h5` or `.json`) and **TensorFlow Lite** models (`.tflite`) and has experimental support for **TensorFlow** models (`.pb` and `.meta`).
+Netron supports **[ONNX](http://onnx.ai)** models (`.onnx`, `.pb`), **Keras** models (`.keras`, `.h5`) and **TensorFlow Lite** models (`.tflite`).
+
+Netron has experimental support for **CoreML** models (`.mlmodel`) and **TensorFlow** models (`.pb`, `.meta`).
 
 <p align='center'><a href='https://www.lutzroeder.com/ai'><img src='media/screenshot.png' width='800'></a></p>
 
@@ -15,55 +17,51 @@ Netron loads **[ONNX](http://onnx.ai)** models (`.onnx` or `.pb`), **Keras** mod
 
 **Linux**
 
-[**Download**](https://github.com/lutzroeder/Netron/releases/latest) the `.AppImage` or `.deb` file. The `.AppImage` needs to be made [executable](http://discourse.appimage.org/t/how-to-make-an-appimage-executable/80) after download.
+[**Download**](https://github.com/lutzroeder/Netron/releases/latest) the `.AppImage` or `.deb` file. 
 
 **Windows**
 
-[**Download**](https://github.com/lutzroeder/Netron/releases/latest) the `.exe` file.
+[**Download**](https://github.com/lutzroeder/Netron/releases/latest) the `.exe` installer.
+
+**Browser**
+
+[**Start**](https://www.lutzroeder.com/ai/netron) the browser version.
+
+
+**Python Server**
+
+Run `pip install netron` and `netron [MODEL_FILE]`.  
+Serve a model in Python using `import netron; netron.serve_file('my_model.onnx')`.
 
 ## Download Models
 
-Below are a few model files you can download and open:
+Sample model files you can download and open:
 
 **ONNX Models**
 
 * [Inception v1](https://s3.amazonaws.com/download.onnx/models/inception_v1.tar.gz)
 * [Inception v2](https://s3.amazonaws.com/download.onnx/models/inception_v2.tar.gz)
 * [ResNet-50](https://s3.amazonaws.com/download.onnx/models/resnet50.tar.gz)
-* [ShuffleNet](https://s3.amazonaws.com/download.onnx/models/shufflenet.tar.gz)
 * [SqueezeNet](https://s3.amazonaws.com/download.onnx/models/squeezenet.tar.gz)
-* [VGG-19](https://s3.amazonaws.com/download.onnx/models/vgg19.tar.gz)
-* [BVLC AlexNet](https://s3.amazonaws.com/download.onnx/models/bvlc_alexnet.tar.gz)
+
+**Keras Models**
+
+* [tiny-yolo-voc](https://github.com/hollance/YOLO-CoreML-MPSNNGraph/raw/master/Convert/yad2k/model_data/tiny-yolo-voc.h5)
 
 **TensorFlow Lite Models**
 
 * [Smart Reply 1.0 ](https://storage.googleapis.com/download.tensorflow.org/models/tflite/smartreply_1.0_2017_11_01.zip)
 * [Mobilenet 1.0 224 Float](https://storage.googleapis.com/download.tensorflow.org/models/tflite/mobilenet_v1_1.0_224_float_2017_11_08.zip)
-* [Inception v3 2015](https://storage.googleapis.com/download.tensorflow.org/models/tflite/inception_v3_2015_2017_11_10.zip)
-* [Inception v3 2016 Slim](https://storage.googleapis.com/download.tensorflow.org/models/tflite/inception_v3_slim_2016_android_2017_11_10.zip)
+* [Inception v3 2016](https://storage.googleapis.com/download.tensorflow.org/models/tflite/inception_v3_slim_2016_android_2017_11_10.zip)
+
+**CoreML Models**
+
+* [MobileNet](https://docs-assets.developer.apple.com/coreml/models/MobileNet.mlmodel)
+* [Places205-GoogLeNet](https://docs-assets.developer.apple.com/coreml/models/GoogLeNetPlaces.mlmodel)
+* [Inception v3](https://docs-assets.developer.apple.com/coreml/models/Inceptionv3.mlmodel)
 
 **TensorFlow models**
 
 * [Inception v3](https://storage.googleapis.com/download.tensorflow.org/models/inception_v3_2016_08_28_frozen.pb.tar.gz)
 * [Inception v4](https://storage.googleapis.com/download.tensorflow.org/models/inception_v4_2016_09_09_frozen.pb.tar.gz)
 * [Inception 5h](https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip)
-
-## Install Python Model Server 
-
-To run Netron in a web browser, install the Python web server using pip: 
-```
-pip install netron
-```
-
-Launch the model server:
-
-```
-netron my_model.onnx
-```
-
-To serve a model from Python code:
-```
-import netron
-
-netron.serve_file('my_model.onnx')
-```