rayheberer

4 ms·

1. 1.▲
   by rayheberer 9y ago

   That's exactly how we had the app work in the demo. The "facade" part of things is that our trained model was not used as the backend or exposed on an API in any way. We used it to generate our best transformation on an image
2. 2.▲
   by rayheberer 9y ago

   Hey, so the idea behind the app would be that users would constantly upload photos of themselves, thereby generating a lot of data, that includes their personal information, time of uploads, and hopefully lifestyle information, which would
3. 3.▲
   by rayheberer 9y ago

   I'll be honest, this sort of thing didn't cross my mind when I was gathering my small dataset. To me, if someone had willingly let an organization publish their photo on the internet, it was free game. That said, having considered
4. 4.▲
   by rayheberer 9y ago

   When it comes to the short color, I think this an instance of the model "overfitting" to the data. I noticed that images generated during training gradually learned to map changes in shorts colors for each of the ~130 people in th
5. 5.▲
   by rayheberer 9y ago

   Great question! My intuition tells me that L1 regularization could indeed be impacting the performance of the model, but for me personally, the only way to find out for certain would be to test this empirically.