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README.md

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+---
+language: en
+license: apache-2.0
+model_name: inception-v2-3.onnx
+tags:
+- validated
+- vision
+- classification
+- inception_and_googlenet
+- inception_v2
+---
+<!--- SPDX-License-Identifier: MIT -->
+
+# Inception v2
+
+|Model        |Download  |Download (with sample test data)| ONNX version |Opset version|
+| ------------- | ------------- | ------------- | ------------- | ------------- |
+|Inception-2| [44 MB](model/inception-v2-3.onnx)  |  [44 MB](model/inception-v2-3.tar.gz) |  1.1 | 3|
+|Inception-2| [44 MB](model/inception-v2-6.onnx)  |  [44 MB](model/inception-v2-6.tar.gz) |  1.1.2 | 6|
+|Inception-2| [44 MB](model/inception-v2-7.onnx)  |  [44 MB](model/inception-v2-7.tar.gz) |  1.2 | 7|
+|Inception-2| [44 MB](model/inception-v2-8.onnx)  |  [44 MB](model/inception-v2-8.tar.gz) |  1.3 | 8|
+|Inception-2| [44 MB](model/inception-v2-9.onnx)  |  [44 MB](model/inception-v2-9.tar.gz) |  1.4 | 9|
+
+## Description
+Inception v2 is a deep convolutional networks for classification.
+
+### Paper
+[Rethinking the Inception Architecture for Computer Vision](https://arxiv.org/abs/1512.00567)
+
+### Dataset
+[ILSVRC2012](http://www.image-net.org/challenges/LSVRC/2012/)
+
+## Source
+Caffe2 Inception v2 ==> ONNX Inception v2
+
+## Model input and output
+### Input
+```
+data_0: float[1, 3, 224, 224]
+```
+### Output
+```
+prob_1: float[1, 1000]
+```
+### Pre-processing steps
+### Post-processing steps
+### Sample test data
+random generated sampe test data:
+- test_data_0.npz
+- test_data_1.npz
+- test_data_2.npz
+- test_data_set_0
+- test_data_set_1
+- test_data_set_2
+
+## Results/accuracy on test set
+
+## License
+MIT
+