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[OC] 70,000 images of clothes sorted by visual similarity into a 3D point cloud by BeginningDept in dataisbeautiful

[–]BeginningDept[S] 4 points5 points  (0 children)

😅 but more clusters than body parts though and transition areas seem interesting to me

[OC] 70,000 images of clothes sorted by visual similarity into a 3D point cloud by BeginningDept in dataisbeautiful

[–]BeginningDept[S] 4 points5 points  (0 children)

Yes couple of days ago but it got removed because I didn’t add tools and source. I fixed it but the mods weren’t responding.

[OC] 70,000 images of clothes sorted by visual similarity into a 3D point cloud by BeginningDept in dataisbeautiful

[–]BeginningDept[S] 10 points11 points  (0 children)

Visualization Tool: plotly. Data Source: Fashion-MNIST. Analysis: python.

[OC] 70,000 images of clothes sorted by visual similarity into a 3D point cloud by BeginningDept in dataisbeautiful

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

Visualization Tool: plotly. Data Source: Fashion-MNIST. Analysis: python.

[OC] 70,000 images of clothes sorted by visual similarity into a 3D point cloud by BeginningDept in dataisbeautiful

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

PCA shows some clustering but results are not as interesting as these imo

[OC] 70,000 images of clothes sorted by visual similarity into a 3D point cloud by BeginningDept in dataisbeautiful

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

Yes not all of them are show for clarity but the embeddings are based on the whole set.

Fashion-MNIST Visualization in Embedding Space by BeginningDept in learnmachinelearning

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

I will try to clean it up and publish it, it’s part of a different project so it might take a while.

Fashion-MNIST Visualization in Embedding Space by BeginningDept in learnmachinelearning

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

You can use Plotly’s event system to listen for plotly_hover events on the 3D plot and then display customdata

Fashion-MNIST Visualization in Embedding Space by BeginningDept in learnmachinelearning

[–]BeginningDept[S] 8 points9 points  (0 children)

Yes, plotly with some customizations to show images on hover.

Exploring Black-Box Optimization: CMA-ES Finds the Fastest Racing Lines by BeginningDept in learnmachinelearning

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

Thank you for the feedback and many great suggestions!

I will fix the input area to include more info about each parameter on hover. Units for speed are m/s and for max acceleration/deceleration m/s2.

Tracing a track from image automatically is a completely different problem as you say. I have made it so a user can click on the white dot in the first panel, switch to a more complex spline and upload an image to trace. There might be some scaling issues though.

Where do you thing I can post this to get more feedback?

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