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# PicsArtHack-binary-segmentation
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The goal of the hackathon was to build some image processing algorithm which can be helpful for [PicsArt](https://picsart.com/?hl=en) applications.
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Here I publish results of the first stage: segmenting people on selfies.
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PicsArt gave labeled [dataset](https://drive.google.com/file/d/1_e2DcZnjufx35uSmQElN5mpdo-Rlv7ZI/view?usp=sharing). [Dice](https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient) coef. was used as evaluation metric.
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Here I publish results of the first stage: segmenting people on selfies.
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PicsArt gave us labeled dataset. [Dice](https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient) coef. was used as evaluation metric.
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I noticed that a lot of images has been labeled by another segmentation model due to a lot of artifacts around the masks borders. Also in test dataset appears copies of train set images. So after training, I did not expect good results on images "from the wild".
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### 1. Loss

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