A simple OCR API server, seriously easy to be deployed by Docker, on Heroku as well

Overview

ocrserver

Go CI codecov Go Report Card

Simple OCR server, as a small working sample for gosseract.

Try now here https://ocr-example.herokuapp.com/, and deploy your own now.

Deploy to Heroku

# Get the code
% git clone [email protected]:otiai10/ocrserver.git
% cd ocrserver
# Make your app
% heroku login
% heroku create
# Deploy the container
% heroku container:login
% heroku container:push web
# Enjoy it!
% heroku open

cf. heroku cli

Quick Start

Ready-Made Docker Image

% docker run -p 8080:8080 otiai10/ocrserver
# open http://localhost:8080

cf. docker

Development with Docker Image

% docker-compose up
# open http://localhost:8080

You need more languages?

% docker-compose build --build-arg LOAD_LANG=rus
% docker-compose up

cf. docker-compose

Manual Setup

If you have tesseract-ocr and library files on your machine

% go get github.com/otiai10/ocrserver/...
% PORT=8080 ocrserver
# open http://localhost:8080

cf. gosseract

Documents

Owner
Hiromu OCHIAI
🙋 ❤️ 🍣
Hiromu OCHIAI
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A general list of resources to image text localization and recognition 场景文本位置感知与识别的论文资源与实现合集 シーンテキストの位置認識と識別のための論文リソースの要約

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(CVPR 2021) ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection

ST3D Code release for the paper ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection, CVPR 2021 Authors: Jihan Yang*, Shaoshu

CVMI Lab 224 Dec 28, 2022
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treeform 65 Dec 30, 2022
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Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks? Artifact Detection/Correction - Offcial PyTorch Implementation This rep

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Give a solution to recognize MaoYan font.

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[BMVC'21] Official PyTorch Implementation of Grounded Situation Recognition with Transformers

Grounded Situation Recognition with Transformers Paper | Model Checkpoint This is the official PyTorch implementation of Grounded Situation Recognitio

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deployment of a hybrid model for automatic weapon detection/ anomaly detection for surveillance applications

Automatic Weapon Detection Deployment of a hybrid model for automatic weapon detection/ anomaly detection for surveillance applications. Loved the pro

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