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nude.js - Nudity detection with JavaScript and HTMLCanvas
nude.js is a JavaScript implementation of a nudity scanner based on approaches from research papers. HTMLCanvas makes it possible to analyse image data and afterwards decide whether it should be displayed or not. The detection algorithm runs at the client, therefore it's possible (with user interaction) to display the image even if it's identified as nude (false positive) The real world usage for client side nudity detection could be in webproxies with child security filters, and maybe even more (e.g. on social media plattforms) nude.js is Open Source. Contributions are very welcome, the goal is to build a reliable client-side nudity scanner.Test the nudity detection script on several predefined images, I didn't have enough time to build a nice demo with flickr image support but feel free to test some of your images too. nude.js is currently supported in IE9(excanvas), FF 3.6+, Chrome, Safari and Opera. For really fast results try Chrome.
image-processing image-classification nudity-detection html5-canvashave-fun-with-machine-learning - An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks
Also available in Chinese (Traditional). This is a hands-on guide to machine learning for programmers with no background in AI. Using a neural network doesn’t require a PhD, and you don’t need to be the person who makes the next breakthrough in AI in order to use what exists today. What we have now is already breathtaking, and highly usable. I believe that more of us need to play with this stuff like we would any other open source technology, instead of treating it like a research topic.
neural-network image-classification machine-learning caffe tutorialgluon-cv - Gluon CV Toolkit
GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in computer vision.
deep-learning computer-vision neural-network gluon mxnet machine-learning image-classification object-detection semantic-segmentationpytorch-book - PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation
pytorch pytorch-tutorials pytorch-tutorials-cn deep-learning neural-style charrnn gan caption neuraltalk image-classification visdom tensorboard nn tensor autograd jupyter-notebookawesome-project-ideas - Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
deep-learning forecasting machine-learning classification series-forecasting image-classification awesome-list awesome dataset multi-label-classificationlabelImg - :metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images
LabelImg is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface.
python2 python3 annotations tools imagenet deep-learning detection recognition image-classificationdarts - Differentiable architecture search for convolutional and recurrent networks
DARTS: Differentiable Architecture Search Hanxiao Liu, Karen Simonyan, Yiming Yang. arXiv:1806.09055. NOTE: PyTorch 0.4 is not supported at this moment and would lead to OOM.
deep-learning automl image-classification language-modeling pytorch convolutional-networks recurrent-networks neural-architecture-searchalbumentations - fast image augmentation library and easy to use wrapper around other libraries
You can use this Google Colaboratory notebook to adjust image augmentation parameters and see the resulting images.
image-augmentation machine-learning augmentation deep-learning detection fast-augmentations segmentation image-segmentation image-processing image-classification object-detectiontf_trt_models - TensorFlow models accelerated with NVIDIA TensorRT
This repository contains scripts and documentation to use TensorFlow image classification and object detection models on NVIDIA Jetson. The models are sourced from the TensorFlow models repository and optimized using TensorRT. Flash your Jetson TX2 with JetPack 3.2 (including TensorRT).
neural-network tensorflow models realtime inference optimize nvidia image-classification object-detection train tx1 jetson tensorrt tx2mmclassification - OpenMMLab Image Classification Toolbox and Benchmark
MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. This project is released under the Apache 2.0 license.
pytorch imagenet image-classification resnet resnext mobilenet shufflenet senet regnetCV-pretrained-model - A collection of computer vision pre-trained models.
A pre-trained model is a model created by some one else to solve a similar problem. Instead of building a model from scratch to solve a similar problem, we can use the model trained on other problem as a starting point. A pre-trained model may not be 100% accurate in your application. For example, if you want to build a self learning car. You can spend years to build a decent image recognition algorithm from scratch or you can take inception model (a pre-trained model) from Google which was built on ImageNet data to identify images in those pictures.
data-science image computer-vision deep-learning neural-network mxnet tensorflow model models keras python3 pytorch model-selection image-classification awesome-list object-detection pretrained-models pretrained video-analysisPaddleClas - A treasure chest for visual recognition powered by PaddlePaddle
PaddleClas is an image recognition toolset for industry and academia, helping users train better computer vision models and apply them in real scenarios. A practical image recognition system consist of detection, feature learning and retrieval modules, widely applicable to all types of image recognition tasks. Four sample solutions are provided, including product recognition, vehicle recognition, logo recognition and animation character recognition.
image-classification image-recognition pretrained-models knowledge-distillation product-recognition autoaugment cutmix randaugment gridmask deit repvgg swin-transformer image-retrieval-systemECCV2020-Code - ECCV 2020 论文开源项目合集，同时欢迎各位大佬提交issue，分享ECCV 2020开源项目
ECCV 2020 论文开源项目合集，同时欢迎各位大佬提交issue，分享ECCV 2020开源项目
computer-vision deep-learning neural-network image-classification object-detection image-segmentation eccv eccv2020 eccv-2020catalyst - Accelerated deep learning R&D
Accelerated deep learning R&D
infrastructure machine-learning natural-language-processing information-retrieval research reinforcement-learning computer-vision deep-learning text-classification distributed-computing image-processing pytorch image-classification metric-learning recommender-system object-detection image-segmentation reproducibility text-segmentationAutoGluon - AutoML for Text, Image, and Tabular Data
AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on image, text, and tabular data.
data-science machine-learning natural-language-processing computer-vision deep-learning mxnet scikit-learn tabular-data pytorch image-classification ensemble-learning object-detectionLabelbox - The most versatile data labeling platform for training expert AI.
Labelbox is a data labeling tool that's purpose built for machine learning applications. Start labeling data in minutes using pre-made labeling interfaces, or create your own pluggable interface to suit the needs of your data labeling task. Labelbox is lightweight for single users or small teams and scales up to support large teams and massive data sets. Simple image labeling: Labelbox makes it quick and easy to do basic image classification or segmentation tasks. To get started, simply upload your data or a CSV file containing URLs pointing to your data hosted on a server, select a labeling interface, (optional) invite collaborators and start labeling.
image-classification image-segmentation computer-vision tensorflow labeling annotations deep-learning recognition tools image-annotationcvat - Computer Vision Annotation Tool (CVAT) is a web-based tool which helps to annotate video and images for Computer Vision algorithms
CVAT is completely re-designed and re-implemented version of Video Annotation Tool from Irvine, California tool. It is free, online, interactive video and image annotation tool for computer vision. It is being used by our team to annotate million of objects with different properties. Many UI and UX decisions are based on feedbacks from professional data annotation team. Code released under the MIT License.
video-annotation computer-vision computer-vision-annotation deep-learning image-annotation annotation-tool annotation labeling labeling-tool image-labeling image-labelling-tool bounding-boxes boundingbox image-classification annotations imagenet detection recognition tensorflowtensornets - High level network definitions with pre-trained weights in TensorFlow
High level network definitions with pre-trained weights in TensorFlow (tested with >= 1.1.0). You can install TensorNets from PyPI (pip install tensornets) or directly from GitHub (pip install git+https://github.com/taehoonlee/tensornets.git).
tensorflow zoo pretrained-models machine-learning deep-learning image-classification object-detection yolo yolov2 yolov3 faster-rcnn resnet inception nasnet pnasnet vgg densenet mobilenet mobilenetv2 squeezenetchannel-pruning - Channel Pruning for Accelerating Very Deep Neural Networks
Please have a look at AMC: AutoML for Model Compression and Acceleration on Mobile Devices ECCV'18, which combines channel pruning and reinforcement learning to further accelerate CNN.
image-recognition model-compression acceleration object-detection image-classification channel-pruning deep-neural-networksbootcamp - Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc
Embed everything, thanks to AI, we can use neural networks to extract feature vectors from unstructured data, such as image, audio and vide etc. Then analyse the unstructured data by calculating the feature vectors, for example calculating the Euclidean or Cosine distance of the vectors to get the similarity. Milvus Bootcamp is designed to expose users to both the simplicity and depth of the Milvus vector database. Discover how to run benchmark tests as well as build similarity search applications like chatbots, recommender systems, reverse image search, molecular search, video search, audio search, and more.
nlp deep-learning question-answering image-classification image-recognition image-search hacktoberfest unstructured-data audio-search milvus benchmark-testing
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