Face Recognition
Kornia
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Face Recognition | Kornia | |
---|---|---|
34 | 11 | |
51,755 | 9,364 | |
- | 2.5% | |
0.0 | 9.4 | |
2 months ago | 8 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Face Recognition
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Security Image Recognition
Camera connected to a PI? Something like this could run locally: https://github.com/ageitgey/face_recognition
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Facial recognition software/API for face-blind teacher?
Have you tried this repo: github
- GitHub - ageitgey/face_recognition: The world's simplest facial recognition api for Python and the command line
- The simplest facial recognition API for Python
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Every thing you need to know about Machine Learning Pipeline
One of the most common challenges is the black-box problem, when the pipeline becomes too complex to understand it would happen. This can make it difficult to identify issues with the system or to understand why it isn't working as we expected or make accurate predictions that saiwa company find out the solution for Face Recognition. Another challenge is the time required for organizations to deploy a machine learning model, which is increasing and make real-time computing difficult . To overcome these challenges, it's important to have an efficient and rigorous ML pipeline . ML level 0 involves a manual process with its own set of challenges, while ML level 1 involves ML pipeline automation and additional components . A well-defined machine learning pipeline can help to abstract the complex process into a series of steps, allowing each team to work independently on specific tasks such as data collection, data preparation, model training, model evaluation, and model deployment.
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Reverse image search / facial recognition
Second link is an easy to implement python library is you want to build it yourself https://github.com/ageitgey/face_recognition
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Made a easy to use face recognition library
It is similar to https://github.com/ageitgey/face_recognition, except that Ageitgey's cli only compares the first face found in the image to the first one found the the second.
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Salisbury council meeting minutes addressing conspiracy theorist councillors
You'd have alot more luck with something like DLIB or an open source implementation such as: https://github.com/ageitgey/face_recognition
- Face comparison in Stable Diffusion
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Understanding different Algorithms for Facial Recognition
To know more about face_recognition module https://github.com/ageitgey/face_recognition
Kornia
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[News] Kornia 0.6.6: ParametrizedLine API, load_image support for Apple Windows Developer, integration demos with Hugging Face and many more.
👉 https://github.com/kornia/kornia/releases/tag/v0.6.6
- [P] Kornia: Differential Computer Vision
- Kornia: Differential Computer Vision
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Hacker News top posts: May 10, 2022
Kornia: Differential Computer Vision\ (3 comments)
- Preprocessing for NN on GPU
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Top 5 Python libraries for Computer vision
Kornia - Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions.
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[D] CPU choice for machine learning server (Epyc vs. Threadripper)
Between "not being sure yet" about GPU operations in pre-processing and choosing high-end CPUs, I think you are overthinking the wrong alternative. Besides DALI, check whether you are using codecs besides nvidia/torchvision-supported jpeg and png, and if other GPU CV libraries meet your needs: torchvision kornia
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[P] Using PyTorch + NumPy? A bug that plagues thousands of open-source ML projects.
Use kornia.augmentation where this problem is solved doing the augmentations in batch outside the dataloader. https://github.com/kornia/kornia
What are some alternatives?
insightface - State-of-the-art 2D and 3D Face Analysis Project
OpenCV - Open Source Computer Vision Library
CompreFace - Leading free and open-source face recognition system
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
Milvus - A cloud-native vector database, storage for next generation AI applications
SimpleCV - The Open Source Framework for Machine Vision
multi-object-tracker - Multi-object trackers in Python
tesseract-ocr - Tesseract Open Source OCR Engine (main repository)
gaps - A Genetic Algorithm-Based Solver for Jigsaw Puzzles :cyclone:
Dlib - A toolkit for making real world machine learning and data analysis applications in C++
tesserocr - A Python wrapper for the tesseract-ocr API