[smandava]

Note:

Will attach more example outputs and make a detailed document about how the model was built and the research behind it. If this is interesting to you, feel free to sign up to the waitlist on www.climbing.ai (and make sure to sign up for our Discord!)

I originally planned on open sourcing the model, data, weights, and code. Only a few people (me and a couple friends) have access to the hosted model on the web app.

If enough people are on the waitlist, I will consider releasing access. This is very expensive to run so was only considering open sourcing it.

Note: the model works well sometimes, but most of the times it does not. This is an early research preview. Please tamper any expectations. A really good general model requires millions of videos and much more training time so it is really prohibitively expensive. As mentioned before, if someone has the compute, all they have to do is scale the existing dataset and training pipeline (which I will publish open-source in the coming weeks).

[ethbr1]

High-level details about how you tackled the various sub-problems would be useful.

I assume, at minimum, there's:

   - Segmentation of moving elements
   - 3d reconstruction from 2d video
   - Reverse kinematics
   - Identification of holds
   - Search for potential climbing path
   - Generation of kinematics for path

[hirako2000]

Likely looking to see a 100k emails list before really thinking about all these problems to solve and well.

Worst case able to build this, scenario, author builds something else entirely.

[ethbr1]

Afaict, author already built a proof of concept.

[icpmacdo]

I've been working on the same thing, there is an interesting quote from back in the day and its either make your program faster or wait 6 months for the computers to get faster. I look at it the same way now with Key Point Analysis and Pose Estimation libraries.

I think OSS is best for this category right now.

[crabmusket]

*temper expectations!

[smandava]

typo :) thanks