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README.md

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 # Unet-Segmentation: Optimized for Mobile Deployment
 ## Real-time segmentation optimized for mobile and edge
 
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 UNet is a machine learning model that produces a segmentation mask for an image. The most basic use case will label each pixel in the image as being in the foreground or the background. More advanced usage will assign a class label to each pixel. This version of the model was trained on the data from Kaggle's Carvana Image Masking Challenge (see https://www.kaggle.com/c/carvana-image-masking-challenge) and is used for vehicle segmentation.
 
-This model is an implementation of Unet-Segmentation found [here]({source_repo}).
+This model is an implementation of Posenet-Mobilenet found [here](https://github.com/milesial/Pytorch-UNet). 
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 This repository provides scripts to run Unet-Segmentation on Qualcomm® devices.
 More details on model performance across various devices, can be found
 [here](https://aihub.qualcomm.com/models/unet_segmentation).