Add ONNX models

The model was converted from PyTorch weights using standard ONNX methods. The pipeline for conversion and checking can be found [here](https://colab.research.google.com/drive/1kvf72PsC4LxSrAqnGvmW_ogFxc3qp_Pg?usp=sharing).

`model.onnx` is an optimized version of the exported model. `model_quant.onnx` is a quantized optimized model.

I checked the difference between the original predictions and the ones from the exported models on a portion of the `scene_parse_150` dataset:

1. `model.onnx` - the absolute difference is 127.364 on a 10x150x128x128 matrix, which looks reasonable. The effective difference (difference in per-pixel class predictions) is 0, which is good.
2. `model_quant.onnx` - the absolute difference is 7876547, which is huge. But the effective difference is only 182, which means that the classes are different for only 182 of 10x128x128 pixels (0.1%).

model.onnx

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model_quant.onnx

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