OpenVisionAPI server

Overview

Open Vision API

Status License: AGPL v3 security: bandit

🚀 Quick start

An instance of ova-server is free and publicly available here:

https://api.openvisionapi.com

Checkout ova-client for a quick demo.

Installing

  1. Setup a local enviroment using tensorflow lite as backend framework
$ make setup-tensorflow-lite

See the documentation for the list of supported deep learning frameworks.

  1. Download the models:
$ ./cli.py download --model=yolov4 --framework=tensorflow_lite --hardware=cpu

Usage

Run the ova-server

$ make run

[2021-03-26 19:45:37 +0100] [396769] [INFO] Starting gunicorn 20.0.4
[2021-03-26 19:45:37 +0100] [396769] [INFO] Listening at: http://0.0.0.0:8000 (396769)
[2021-03-26 19:45:37 +0100] [396769] [INFO] Using worker: sync
[2021-03-26 19:45:37 +0100] [396771] [INFO] Booting worker with pid: 396771

Get the official client

$ git clone https://github.com/openvisionapi/ova-client
$ cd ova-client
$ make setup
$ source .venv/bin/activate
$ DETECTION_URL=http://localhost:8000/api/v1/detection ./ova_client.py detection images/cat.jpeg

More information about the ova-client https://github.com/openvisionapi/ova-client

⛏️ Built Using

✍️ Author

Badr BADRI

🤝 Contributing

Your contributions are welcome !

Setting up development environment

To setup the development environment, simply run this command

$ make dev

Code-style checks

black is used for code formatting.

mypy is used for static typing.

🔧 Tests

To run the tests, simply run those commands

$ make dev
$ make test

📄 Documentation

Full documentation can be found here:

https://openvisionapi-documentation.readthedocs.io/en/latest/

⚖️ License

AGPLv3

Copyright © 2021 Badr BADRI @pythops

Owner
Open Vision API
Open source computer vision API based on open source models
Open Vision API
A general python framework for single object tracking in LiDAR point clouds, based on PyTorch Lightning.

Open3DSOT A general python framework for single object tracking in LiDAR point clouds, based on PyTorch Lightning. The official code release of BAT an

Kangel Zenn 172 Dec 23, 2022
NIMA: Neural IMage Assessment

PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from

Kyryl Truskovskyi 293 Dec 30, 2022
House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects

House-GAN++ Code and instructions for our paper: House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent

122 Dec 28, 2022
Localization Distillation for Object Detection

Localization Distillation for Object Detection This repo is based on mmDetection. This is the code for our paper: Localization Distillation

274 Dec 26, 2022
Python package to generate image embeddings with CLIP without PyTorch/TensorFlow

imgbeddings A Python package to generate embedding vectors from images, using OpenAI's robust CLIP model via Hugging Face transformers. These image em

Max Woolf 81 Jan 04, 2023
Neural network chess engine trained on Gary Kasparov's games.

Neural Chess It's not the best chess engine, but it is a chess engine. Proof of concept neural network chess engine (feed-forward multi-layer perceptr

3 Jun 22, 2022
This repo implements several applications of the proposed generalized Bures-Wasserstein (GBW) geometry on symmetric positive definite matrices.

GBW This repo implements several applications of the proposed generalized Bures-Wasserstein (GBW) geometry on symmetric positive definite matrices. Ap

Andi Han 0 Oct 22, 2021
Run Keras models in the browser, with GPU support using WebGL

**This project is no longer active. Please check out TensorFlow.js.** The Keras.js demos still work but is no longer updated. Run Keras models in the

Leon Chen 4.9k Dec 29, 2022
Spam your friends and famly and when you do your famly will disown you and you will have no friends.

SpamBot9000 Spam your friends and family and when you do your family will disown you and you will have no friends. Terms of Use Disclaimer: Please onl

DJ15 0 Jun 09, 2022
Code for Learning to Segment The Tail (LST)

Learning to Segment the Tail [arXiv] In this repository, we release code for Learning to Segment The Tail (LST). The code is directly modified from th

47 Nov 07, 2022
Implementation of the state of the art beat-detection, downbeat-detection and tempo-estimation model

The ISMIR 2020 Beat Detection, Downbeat Detection and Tempo Estimation Model Implementation. This is an implementation in TensorFlow to implement the

Koen van den Brink 1 Nov 12, 2021
PyTorch and GPyTorch implementation of the paper "Conditioning Sparse Variational Gaussian Processes for Online Decision-making."

Conditioning Sparse Variational Gaussian Processes for Online Decision-making This repository contains a PyTorch and GPyTorch implementation of the pa

Wesley Maddox 16 Dec 08, 2022
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

CatBoost 6.9k Jan 04, 2023
《Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching》(CVPR 2020)

This contains the codes for cross-view geo-localization method described in: Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching, CVPR2020.

41 Oct 27, 2022
CLIP+FFT text-to-image

Aphantasia This is a text-to-image tool, part of the artwork of the same name. Based on CLIP model, with FFT parameterizer from Lucent library as a ge

vadim epstein 690 Jan 02, 2023
Official Implementation of "Designing an Encoder for StyleGAN Image Manipulation"

Designing an Encoder for StyleGAN Image Manipulation (SIGGRAPH 2021) Recently, there has been a surge of diverse methods for performing image editing

749 Jan 09, 2023
Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective

Unofficial pytorch implementation of the paper "Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective"

16 Nov 21, 2022
Anomaly Localization in Model Gradients Under Backdoor Attacks Against Federated Learning

Federated_Learning This repo provides a federated learning framework that allows to carry out backdoor attacks under varying conditions. This is a ker

Arçelik ARGE Açık Kaynak Yazılım Organizasyonu 0 Nov 30, 2021
Scalable, event-driven, deep-learning-friendly backtesting library

...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on

Andrew 922 Dec 27, 2022
Pytorch implementation of One-Shot Affordance Detection

One-shot Affordance Detection PyTorch implementation of our one-shot affordance detection models. This repository contains PyTorch evaluation code, tr

46 Dec 12, 2022