diff --git a/README.md b/README.md
index 412e9c5..85624d9 100644
--- a/README.md
+++ b/README.md
@@ -14,7 +14,7 @@ This software implements a heavily parallelized pipeline to recognize text in PD
 
 1. Install Docker and Python 3.
 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}`.
 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`.
diff --git a/wrapper/ocr b/wrapper/ocr
index 37dad98..58a0bca 100755
--- a/wrapper/ocr
+++ b/wrapper/ocr
@@ -6,7 +6,7 @@ import os
 import subprocess
 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_OUTPUT_DIR = '/output'
 CONTAINER_MODELS_DIR = '/usr/local/share/tessdata'