3d-ken-burns
pyhpc-benchmarks
| 3d-ken-burns | pyhpc-benchmarks | |
|---|---|---|
| 5 | 6 | |
| 1,496 | 301 | |
| - | - | |
| 3.8 | 3.2 | |
| 2 months ago | 4 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | The Unlicense |
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3d-ken-burns
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Making a trailer for my book with midjourney. What do you think?
I guess you could use a free video editor (Davinci resolve is free with less features than payed version). And then try to use this open source script: https://github.com/sniklaus/3d-ken-burns, but it would definitely be harder.
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It's time to upscale FSR 2 even further: Meet FSR 2.1
installing ROCm is bit of a pain (there is little packaging, so you have to rebuild it yourself)
Search who's running Stable Diffusion on Nvidia and who's running on AMD: if you are using AMD, you are kind of on your own.
Finally, you have model with custom CUDA code (e.g. https://github.com/sniklaus/3d-ken-burns )
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Are there any websites that create an .mp4 of simple parallax effect movement from a jpg using machine learning?
There's a great Github with a script that I run on Google Colab that does a decent parallax effect in about 30 seconds through ML... but it just takes a while to get the instance spun up, and I've yet to figure out how to push out a 4k .mp4 from it. Surely someone has coding chops and can do this for parallax and monetize it like the Dall-E bot?
- How are people taking still photos and making these stereoscopic videos out of them? [READ COMMENTS]
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Battle Round 1: 3D Ken Burns Effect using PyTorch
Making use of: https://github.com/sniklaus/3d-ken-burns
pyhpc-benchmarks
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Supercharged high-resolution ocean simulation with Jax
True, but unfortunately Pytorch is not quite there yet when it comes to more complex benchmarks:
https://github.com/dionhaefner/pyhpc-benchmarks#example-resu...
JAX really is the only library that comes close to low-level code on CPU, almost always.
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[D] Does working with Tensorflow affect my chances of getting research internships?
https://github.com/dionhaefner/pyhpc-benchmarks begs to differ.
- GitHub - dionhaefner/pyhpc-benchmarks: A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python
- HPC Benchmarks for Python
- Pyhpc: Benchmarks for CPU and GPU of the most popular high-perf Python libs
What are some alternatives?
stable-diffusion-rocm
tf-quant-finance - High-performance TensorFlow library for quantitative finance.
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
pyopencl - OpenCL integration for Python, plus shiny features
cupy - NumPy & SciPy for GPU
sqloxide - Python bindings for sqlparser-rs
halutmatmul - Hashed Lookup Table based Matrix Multiplication (halutmatmul) - Stella Nera accelerator
MATDaemon.jl
XNOR-popcount-GEMM-PyTorch-CPU-CUDA - A PyTorch implemenation of real XNOR-popcount (1-bit op) GEMM Linear PyTorch extension support both CPU and CUDA
XLA.jl - "Maybe we have our own magic."
NewsMTSC - Target-dependent sentiment classification in news articles reporting on political events. Includes a high-quality data set of over 11k sentences and a state-of-the-art classification model.
XLA.jl - Julia on TPUs