sporada/ocr
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fix image tag

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Patrick Jentsch 2022-01-04 12:10:26 +01:00
parent e1b78b6ba4
commit 8a3816121c
2 changed files with 2 additions and 2 deletions
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README.md
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@ -14,7 +14,7 @@ This software implements a heavily parallelized pipeline to recognize text in PD
1. Install Docker and Python 3. 1. Install Docker and Python 3.
2. Clone this repository: `git clone https://gitlab.ub.uni-bielefeld.de/sfb1288inf/ocr.git` 2. Clone this repository: `git clone https://gitlab.ub.uni-bielefeld.de/sfb1288inf/ocr.git`
2. Build the Docker image: `docker build -t gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:0.1.0 ocr` 2. Build the Docker image: `docker build -t gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:v0.1.0 ocr`
2. Add the wrapper script (`wrapper/ocr` relative to this README file) to your `${PATH}`. 2. Add the wrapper script (`wrapper/ocr` relative to this README file) to your `${PATH}`.
3. Create working directories for the pipeline: `mkdir -p /<my_data_location>/{input,models,output}`. 3. Create working directories for the pipeline: `mkdir -p /<my_data_location>/{input,models,output}`.
4. Place your Tesseract OCR model(s) inside `/<my_data_location>/models`. 4. Place your Tesseract OCR model(s) inside `/<my_data_location>/models`.

2
wrapper/ocr
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@ -6,7 +6,7 @@ import os
import subprocess import subprocess
import sys import sys
CONTAINER_IMAGE = 'gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:0.1.0' CONTAINER_IMAGE = 'gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/ocr:v0.1.0'
CONTAINER_INPUT_DIR = '/input' CONTAINER_INPUT_DIR = '/input'
CONTAINER_OUTPUT_DIR = '/output' CONTAINER_OUTPUT_DIR = '/output'
CONTAINER_MODELS_DIR = '/usr/local/share/tessdata' CONTAINER_MODELS_DIR = '/usr/local/share/tessdata'