LibtorchTutorials
awesome-project-ideas
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| LibtorchTutorials | awesome-project-ideas | |
|---|---|---|
| 1 | 3 | |
| 639 | 7,404 | |
| - | - | |
| 0.0 | 4.2 | |
| over 2 years ago | about 1 year ago | |
| C++ | ||
| Apache License 2.0 | MIT License |
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LibtorchTutorials
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C++ trainable semantic segmentation models
Visit Libtorch Tutorials Project if you want to know more about Libtorch Segment library.
awesome-project-ideas
- Project Ideas
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Procedurally generated rocks in my software "Proc-rock"
My best recommendation I could give you is to simply create things. Start small, for example create a small program in the field you're interested in and then go from there. You can check this for ideas on what to create. There's a lot of resources in there.
- Do you guys have any ideas for website ideas?
What are some alternatives?
SegmentationCpp - A c++ trainable semantic segmentation library based on libtorch (pytorch c++). Backbone: VGG, ResNet, ResNext. Architecture: FPN, U-Net, PAN, LinkNet, PSPNet, DeepLab-V3, DeepLab-V3+ by now.
500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code - 500 AI Machine learning Deep learning Computer vision NLP Projects with code
yolo-tensorrt - TensorRT8.Support Yolov5n,s,m,l,x .darknet -> tensorrt. Yolov4 Yolov3 use raw darknet *.weights and *.cfg fils. If the wrapper is useful to you,please Star it.
awesome-deep-learning - A curated list of awesome Deep Learning tutorials, projects and communities.
Drogon-torch-serve - Serve pytorch / torch models using Drogon
awesome-ocr
tensorrtx - Implementation of popular deep learning networks with TensorRT network definition API
awesome-explainable-graph-reasoning - A collection of research papers and software related to explainability in graph machine learning.
muzero-cpp - A C++ pytorch implementation of MuZero
datasets-for-good - List of datasets to apply stats/machine learning/technology to the world of social good.
torchRL - TorchRL is a C++ reinforcement library using PyTorch C++ backend LibTorch
proc-rock - Procedural Generation of Realistic-looking Rocks using Geological and Visual Clues