OpenVisionAPI server

Overview

Open Vision API

Status License: AGPL v3 security: bandit

๐Ÿš€ 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

โ›๏ธ Built Using

โœ๏ธ Author

Badr BADRI

๐Ÿค 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.

๐Ÿ”ง Tests

To run the tests, simply run those commands

$ make dev
$ make test

๐Ÿ“„ Documentation

Full documentation can be found here:

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

โš–๏ธ License

AGPLv3

Copyright ยฉ 2021 Badr BADRI @pythops

Owner
Open Vision API
Open source computer vision API based on open source models
Open Vision API
"Domain Adaptive Semantic Segmentation without Source Data" (ACM MM 2021)

LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.

benfour 16 Sep 28, 2022
Job-Recommend-Competition - Vectorwise Interpretable Attentions for Multimodal Tabular Data

SiD - Simple Deep Model Vectorwise Interpretable Attentions for Multimodal Tabul

Jungwoo Park 40 Dec 22, 2022
Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.

Summary Explorer Summary Explorer is a tool to visually inspect the summaries from several state-of-the-art neural summarization models across multipl

Webis 42 Aug 14, 2022
1st-in-MICCAI2020-CPM - Combined Radiology and Pathology Classification

Combined Radiology and Pathology Classification MICCAI 2020 Combined Radiology a

22 Dec 08, 2022
Code for Multiple Instance Active Learning for Object Detection, CVPR 2021

MI-AOD Language: ็ฎ€ไฝ“ไธญๆ–‡ | English Introduction This is the code for Multiple Instance Active Learning for Object Detection (The PDF is not available tem

Tianning Yuan 269 Dec 21, 2022
YOLO-v5 ๊ธฐ๋ฐ˜ ๋‹จ์•ˆ ์นด๋ฉ”๋ผ์˜ ์˜์ƒ์„ ํ™œ์šฉํ•ด ์ฐจ๊ฐ„ ๊ฑฐ๋ฆฌ๋ฅผ ์ผ์ •ํ•˜๊ฒŒ ์œ ์ง€ํ•˜๋ฉฐ ์ฃผํ–‰ํ•˜๋Š” Adaptive Cruise Control ๊ธฐ๋Šฅ ๊ตฌํ˜„

์ž์œจ ์ฃผํ–‰์ฐจ์˜ ์˜์ƒ ๊ธฐ๋ฐ˜ ์ฐจ๊ฐ„๊ฑฐ๋ฆฌ ์œ ์ง€ ๊ฐœ๋ฐœ Table of Contents ํ”„๋กœ์ ํŠธ ์†Œ๊ฐœ ์ฃผ์š” ๊ธฐ๋Šฅ ์‹œ์Šคํ…œ ๊ตฌ์กฐ ๋””๋ ‰ํ† ๋ฆฌ ๊ตฌ์กฐ ๊ฒฐ๊ณผ ์‹คํ–‰ ๋ฐฉ๋ฒ• ์ฐธ์กฐ ํŒ€์› ํ”„๋กœ์ ํŠธ ์†Œ๊ฐœ YOLO-v5 ๊ธฐ๋ฐ˜์œผ๋กœ ๋‹จ์•ˆ ์นด๋ฉ”๋ผ์˜ ์˜์ƒ์„ ํ™œ์šฉํ•ด ์ฐจ๊ฐ„ ๊ฑฐ๋ฆฌ๋ฅผ ์ผ์ •ํ•˜๊ฒŒ ์œ ์ง€ํ•˜๋ฉฐ ์ฃผํ–‰ํ•˜๋Š” Adap

14 Jun 29, 2022
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"

CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We

Hui Wu 19 Oct 21, 2022
An energy estimator for eyeriss-like DNN hardware accelerator

Energy-Estimator-for-Eyeriss-like-Architecture- An energy estimator for eyeriss-like DNN hardware accelerator This is an energy estimator for eyeriss-

HEXIN BAO 2 Mar 26, 2022
Transformer part of 12th place solution in Riiid! Answer Correctness Prediction

kaggle_riiid Transformer part of 12th place solution in Riiid! Answer Correctness Prediction. Please see here for more information. Execution You need

Sakami Kosuke 2 Apr 23, 2022
scikit-learn: machine learning in Python

scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The project was started

scikit-learn 52.5k Jan 08, 2023
PyTorch implementation for our paper "Deep Facial Synthesis: A New Challenge"

FSGAN Here is the official PyTorch implementation for our paper "Deep Facial Synthesis: A New Challenge". This project achieve the translation between

Deng-Ping Fan 32 Oct 10, 2022
[ACL 20] Probing Linguistic Features of Sentence-level Representations in Neural Relation Extraction

REval Table of Contents Introduction Overview Requirements Installation Probing Usage Citation License ๐ŸŽ“ Introduction REval is a simple framework for

13 Jan 06, 2023
Pytorch implementation of DeePSiM

Pytorch implementation of DeePSiM

1 Nov 05, 2021
Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI 2021)

T2Net Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI 2021) [Paper][Code] Dependencies numpy==1.18.5 scikit_image==

64 Nov 23, 2022
YoloV3 Implemented in Tensorflow 2.0

YoloV3 Implemented in TensorFlow 2.0 This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. Key Features

Zihao Zhang 2.5k Dec 26, 2022
Train an imgs.ai model on your own dataset

imgs.ai is a fast, dataset-agnostic, deep visual search engine for digital art history based on neural network embeddings.

Fabian Offert 5 Dec 21, 2021
Tutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3

Python-for-Epidemiologists This repository is an introduction to epidemiology analyses in Python. Additionally, the tutorials for my library zEpid are

Paul Zivich 120 Nov 17, 2022
DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks

English | ็ฎ€ไฝ“ไธญๆ–‡ Introduction DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks Reference Pat

CV Newbie 28 Dec 13, 2022
REGTR: End-to-end Point Cloud Correspondences with Transformers

REGTR: End-to-end Point Cloud Correspondences with Transformers This repository contains the source code for REGTR. REGTR utilizes multiple transforme

Zi Jian Yew 108 Dec 17, 2022
Rainbow DQN implementation that outperforms the paper's results on 40% of games using 20x less data ๐ŸŒˆ

Rainbow ๐ŸŒˆ An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat

Dominik Schmidt 31 Dec 21, 2022