facetorch
bearid
facetorch | bearid | |
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6 | 3 | |
408 | 46 | |
- | - | |
8.7 | 3.3 | |
3 months ago | 4 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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.
facetorch
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facetorch - Python library for face analysis using neural networks written in PyTorch
facetorch:
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Models for facial identification?
You can use embeddings produced by facetorch library to represent faces. The next step is to build a database of faces and face embedding similarity engine. https://github.com/tomas-gajarsky/facetorch
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facetorch
facetorch is a Python library for analysing faces using TorchScript
- facetorch: analyze faces using TorchScript
- facetorch - analyze faces using TorchScript
bearid
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Bearcam Companion: GitHub, User Groups and Rekognition
By the end of my previous post, I had reached a good baseline for the Bearcam Companion app. It was past time to start tracking the code in a version control system. Since we already have the BearID Project on GitHub, I decided to use the same for this project.
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BearCam Companion
We initially focused on building a photo dataset of the bears at Brooks Falls. We collected photos from individuals and a large set from the National Parks Service's bear monitoring program at Katmai. From there we got involved with Dr. Melanie Clapham, a conservation scientist in British Columbia, studying the bears of Glendale Cove. We built a computer to run our ML training and developed an open source application, bearid, which we provided to Melanie as a Docker container she could run in the field on a laptop.
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AWS Community Builders: My First Step
The BearID Project application bearid runs on a server. It takes photos or videos as inputs and outputs a sequence of boxes labeled with the bear's name. This can only happen after someone goes into the field (or, forest), collects a bunch of SD cards from trail cameras, and uploads them to the server. This happens a few times a year. If the trail camera was connected, it could send data to the cloud, but the connection would probably be expensive. If the camera could detect and identify the bear and send only the metadata to a server, we could update the researcher in real time. I have less experience in this area, so connecting it all together with AWS services will be a real learning experience for me.
What are some alternatives?
pytorch-ssim - pytorch structural similarity (SSIM) loss
facenet - Face recognition using Tensorflow
deepface - A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
insightface - State-of-the-art 2D and 3D Face Analysis Project
Face Recognition - The world's simplest facial recognition api for Python and the command line
Jetson-Nano-Ubuntu-20-image - Jetson Nano with Ubuntu 20.04 image
SpeciesClassification - To gain access, please finish setting up this repository now at: https://repos.opensource.microsoft.com/microsoft/wizard?existingreponame=SpeciesClassification&existingrepoid=169153301
bittensor - Internet-scale Neural Networks
courses - This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
torchgeo - TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
desktop - Focus on what matters instead of fighting with Git.