Yeah, his baldness detector is not robust as it just checks the average color of the area above the forehead, but you could make a robust one through transfer learning a deep model trained on ImageNet further finetuned on a small dataset of a few dozen images of bald and non-bald.
Since trained classifiers are already being used, and therefore fair game, a trained baldness classifier would be a better choice, I think. Of course you would need a dataset for that.
Deep learning with a 100 samples can do this completely with the body too. This is a similar project I did: https://comic2gif.com where I remove the speech written on the images, the same technology can be used here.
But edge detection is a lot easier on comics than on photos I would think. The background on a comic would also have a mostly solid color background which makes it easier.
> But edge detection is a lot easier on comics than on photos I would think
That should be true. But deep learning based models work quite good on natural images as Vgg dataset is mostly natural. This is perhaps one-off usage/application on comics.
hey, author here, thanks for the attention on this post, especially the feedback regarding CV techniques. i wanted to write about some basic computer vision tools in the context of a Seinfeld reference. it was intended as a joke, but i realize it could be hurtful. i'm sorry if i hurt anybody's feelings.
As a photo store clerk I can confirm that this is indeed one of the most frequent requests we get, so this could be a huge timesaver. But you really need to work on the removal part, it’s practically unusable as it is!
Readit News
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[1]: https://www.youtube.com/watch?v=qadw0BRKeMk&t=3m43s
Something like this: https://www.kaggle.com/dansbecker/transfer-learning
This method gets good, robust performance with just a few minutes of training.
Worked well for Amazon!
https://www.reuters.com/article/us-amazon-com-jobs-automatio...
That should be true. But deep learning based models work quite good on natural images as Vgg dataset is mostly natural. This is perhaps one-off usage/application on comics.
Well done!