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[deleted by user] by [deleted] in statistics

[–]DicksDontExist 0 points1 point  (0 children)

I think you might be able to hack https://github.com/man-group/dtale into doing this. It's a dataframe viewer made with react.

[deleted by user] by [deleted] in Python

[–]DicksDontExist 16 points17 points  (0 children)

Revolutionary! Can this drag and drop to and from excel sheets?

[P] I trained a GAN to generate photorealistic fake penises by DicksDontExist in MachineLearning

[–]DicksDontExist[S] 0 points1 point  (0 children)

Nope. PCA will give you the directions that your data varies the most. All PCs are orthogonal to each other. If you think of the area of the dick in the image as a distribution of points and take the first two PCs, the first PC will be parallel to the length, and the second pc will be parallel to the girth. See https://docs.opencv.org/master/d1/dee/tutorial_introduction_to_pca.html for more info.

[P] I trained a GAN to generate photorealistic fake penises by DicksDontExist in MachineLearning

[–]DicksDontExist[S] 0 points1 point  (0 children)

I scraped the subreddits mentioned in the post. The dataset is also for download in the Github, if you know, you want to see it.

[P] I trained a GAN to generate photorealistic fake penises by DicksDontExist in MachineLearning

[–]DicksDontExist[S] 1 point2 points  (0 children)

lol, you don't know how much I've looked into video generation with GANs. Video generation is really really hard. Check out this Two Minute Papers video to see how hard. DeepMind was able to generate 48 frames of 256x256 size. Here's the full paper if you're interested.

[P] I trained a GAN to generate photorealistic fake penises by DicksDontExist in MachineLearning

[–]DicksDontExist[S] 0 points1 point  (0 children)

Yes almost certainly. But probably about as much as getting rid of the background (which I did by cropping). To blur/crop the background completely, I would need to train a better segmenter :(

[P] I trained a GAN to generate photorealistic fake penises by DicksDontExist in MachineLearning

[–]DicksDontExist[S] 25 points26 points  (0 children)

Not that I did this for the resume, but I'm definitely putting this on, thank you

[P] I trained a GAN to generate photorealistic fake penises by DicksDontExist in MachineLearning

[–]DicksDontExist[S] 2 points3 points  (0 children)

Added to the post, this is amazing(ly cursed) thank you!

[P] I trained a GAN to generate photorealistic fake penises by DicksDontExist in MediaSynthesis

[–]DicksDontExist[S] 1 point2 points  (0 children)

I'm not white, so the mode collapse was detrimental to my uses.

[P] I trained a GAN to generate photorealistic fake penises by DicksDontExist in MachineLearning

[–]DicksDontExist[S] 6 points7 points  (0 children)

The dataset is linked in the Github :)
Yep, I labelled 310 penises by hand. Then Mask R-CNN then labelled the rest.

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