glasses
HugsVision
glasses | HugsVision | |
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2 | 1 | |
413 | 188 | |
- | - | |
1.8 | 0.0 | |
over 1 year ago | 9 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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glasses
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Are Open-sourced Implementations Sometimes Over-engineered?
Yes, they are. Take with a grain of salt, but researchers (usually) do not know how to code and (or) they don't care to properly share their work. Things that are learned in the first Computer Science bachelor year, like OOP, DRY, packages, good variables/function naming, are apparently not used in ml research. This is why I created my own library (https://github.com/FrancescoSaverioZuppichini/glasses), for me, good code means less time I have to spend working and more free time.
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[N] Facebook announced a new AI open-source called DeiT (A new technique to train computer vision models)
I have implemented most of the sota models in my library (https://github.com/FrancescoSaverioZuppichini/glasses). These are my 2 cents:
HugsVision
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[R] HugsVision: A easy-to-use HuggingFace wrapper for computer vision
Find more tutorials and informations about HugsVision on GitHub
What are some alternatives?
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
poolformer - PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)
monodepth2 - [ICCV 2019] Monocular depth estimation from a single image
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
fashionpedia-api - Python API for Fashionpedia Dataset
One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.
ganspace - Discovering Interpretable GAN Controls [NeurIPS 2020]
gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
CoordConv
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
Transformer-Explainability - [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.