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citnaj's profile
Jason Antic
Jason Antic
Jason Antic
@citnaj

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Jason Antic

@citnaj

Obsessively pursuing the perfection of image and video colorization/restoration using deep learning. Creator of DeOldify.

Ocean Beach, San Diego
deoldify.ai
Joined January 2010

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    1. Rani Horev‏ @rani_horev 4 Jan 2019
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      @citnaj is there an online version of DeOldify that I can upload and deoldify images with?

      1 reply 0 retweets 1 like
    2. Jason Antic‏ @citnaj 4 Jan 2019
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      Replying to @rani_horev

      Yes in fact there is- multiple options! @alexpolymath recently created this slick site that uses DeOldify: https://colorize.cc/  . The only drawback to it is that it's currently GPU limited, which will mean certain renders won't look -as- good. But it's hella convenient.

      1 reply 0 retweets 1 like
    3. Jason Antic‏ @citnaj 4 Jan 2019
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      Replying to @citnaj @alexpolymath

      If you want to take a shot at using a beefier GPU, you can use the Colab notebook: https://colab.research.google.com/github/jantic/DeOldify/blob/master/DeOldify_colab.ipynb … . It's not as user friendly as @alexpolymath 's website though, as it's Python code that you run in a notebook. But still- a free GPU and hassle free VM comes with it.

      2 replies 0 retweets 1 like
    4. Rani Horev‏ @rani_horev 4 Jan 2019
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      Replying to @citnaj @alexpolymath

      It's was surprising easy to run the notebook, but the results are kind of greenish :) Any ideas why?pic.twitter.com/ZS6X6BiQZ0

      3 replies 0 retweets 0 likes
    5. Jason Antic‏ @citnaj 5 Jan 2019
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      Replying to @rani_horev @alexpolymath

      Have you tried it playing around with the render_factor variable? Sometime it’s just a matter of hitting the sweet spot with that as to whether or not image elements are interpreted accurately. Generally higher is better but not always

      1 reply 0 retweets 0 likes
    6. Rani Horev‏ @rani_horev 5 Jan 2019
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      Replying to @citnaj @alexpolymath

      Nope, but I can try. What's the render factor? (or where can I read about it?) Thanks a lot!

      1 reply 0 retweets 0 likes
    7. Jason Antic‏ @citnaj 5 Jan 2019
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      Replying to @rani_horev @alexpolymath

      In the notebook code. There’s a comment in there that describes what it does and the max value of 42.

      1 reply 0 retweets 0 likes
    8. Rani Horev‏ @rani_horev 5 Jan 2019
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      Replying to @citnaj @alexpolymath

      I should've searched there before asking 🤦‍♂️

      2 replies 0 retweets 0 likes
    9. Rani Horev‏ @rani_horev 5 Jan 2019
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      Replying to @rani_horev @citnaj @alexpolymath

      Looks like the sweet spot is different for each image (between 10 to 25). I wonder if we can add a designated module that colorize people in the image, as many times they are the main object in old photos.pic.twitter.com/BwsS9jXOLS

      1 reply 0 retweets 0 likes
      Jason Antic‏ @citnaj 5 Jan 2019
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      Replying to @rani_horev @alexpolymath

      Usually with images like this the optimal factor is around 38-42. Have you tried that? On model improvements: They’re coming! Right now I’m focused on trying to make the model better as a whole rather than trying to specialize anything (like people).

      9:45 AM - 5 Jan 2019
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      • Rani Horev
      2 replies 0 retweets 1 like
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        1. Jason Antic‏ @citnaj 5 Jan 2019
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          Replying to @citnaj @alexpolymath

          You can look at examples of improvements on this front in images I posted a few weeks ago. The Cork, Ireland 1905 crowd photo is a good example. Basically it amounts to bigger model==better. Seems like the same lessons as talked about in the BigGAN paper.

          1 reply 0 retweets 0 likes
        2. Jason Antic‏ @citnaj 5 Jan 2019
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          Replying to @citnaj @alexpolymath

          Note: I haven’t committed the latest models I’ve experimented with to master yet. So you’re still using an older model.

          1 reply 0 retweets 1 like
        3. Show replies
        1. Rani Horev‏ @rani_horev 5 Jan 2019
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          Replying to @citnaj @alexpolymath

          There was almost no difference between 38 and 42

          0 replies 0 retweets 0 likes
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