nins_ t1_j5xjw35 wrote on January 26, 2023 at 6:25 AM

Reply to [D] Pretraining for CNN by Dense-Smf-6032

Do you mean self-supervised learning for CNNs? SimCLR does work on CNNs. Also check out SOCO, SCRL, BYOL - there's a lot.

nins_ t1_j38fh4v wrote on January 6, 2023 at 7:25 PM

Reply to [D] Best way to package Pytorch models as a standalone application by Atom_101

I found the portable binaries of Real ESRGAN extremely easy to use (no setup involved). Just a command line tool. It does not use CUDA though. https://github.com/xinntao/Real-ESRGAN

They're using NCNN to package the model. Have a look. https://github.com/Tencent/NCNN

nins_ t1_iyl5j1t wrote on December 2, 2022 at 4:59 AM

Reply to [R] Where can I rent hardware to train my models on? by HarryPlopperOMG

That's the entire business model for aws, Azure, gcp. There are several small players out there as well.

nins_ t1_iwlhcbk wrote on November 16, 2022 at 2:59 PM

Reply to [P] Thoughts on representing a Real world data by snairgit

So it seems like you have 8 * 5 * 2 = 80 features per training sample if you want to use all 8 sides to predict your binary label. Is this representation causing problems?

nins_ t1_iuwwdrw wrote on November 3, 2022 at 4:41 PM

Reply to [P] How to reverse engineer a neural network to get inputs from the outputs by ojiber

Any chance this is your friend? :)

https://www.reddit.com/r/MachineLearning/comments/yfqhsm/d_predicting_input_values_from_taget_value/?utm_source=share&utm_medium=android_app&utm_name=androidcss&utm_term=1&utm_content=share_button

You can see my answer there for an alternative approach but in short, you can't just do a reverse pass to get the inputs.

nins_ t1_iuen1e3 wrote on October 30, 2022 at 7:18 PM

Reply to comment by ChaosAdm in [D] How do I get certain number of frames before every point-of-impact in a tennis game video? by ChaosAdm

The manual annotation would involve you noting down the timestamps in a csv. Then you write a short script (I would do it with OpenCV) to read the video files, get 20 frames prior to each timestamp, save them as images into whatever directory structure you need.

Edit: MoviePy package will probably be easier than OpenCV for you.

nins_ t1_iu5na8f wrote on October 28, 2022 at 6:56 PM

Reply to [D] Predicting input values from taget value by ARFGHA

Is the input space very large?

What if you train a model to predict the actual value using your dataset and then simply run an exhaustive prediction over your input space? Then lookup the closest model output value whenever you need it and check the corresponding input parameters.