CLI Reference

Complete reference for the VIESUS image enhancement CLI — flags, input methods, output naming, image list format, and usage examples.

The viesus command-line tool is the most common interface for batch image enhancement on Windows and Linux. It reads image files (singly or by list), applies the VIESUS enhancement pipeline, and writes output — built to be called from shell scripts, schedulers, or any orchestration tool. This page documents every flag, input method, and output convention. To run it in a container see Docker for CLI; for throughput data see Benchmarks, and for fixes see Troubleshooting.

Syntax

viesus [options] [-l imagelist | -f file1 [file2 ...]]

The -f option must be the last parameter on the command line — everything after it is treated as input files.

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Input methods

Method	Flag	Description
File list	-l <imagelist>	Process images listed in a text file (one path per line)
Direct files	-f <file1> [file2 ...]	Process specified image files directly

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Core options

Flag	Argument	Description
-b <path>	String	Base path for saving enhanced image results
-p <file>	String	Path to parameter/configuration JSON file
-i	—	Save enhanced images with the same filename (overwrites the original)
-s	—	Save enhanced images in the same folder with default suffix _viesus
-n <suffix>	String	Save enhanced images with a custom suffix. Only valid when -b is not used.
-e	—	Enhance only images containing valid EXIF data
-a	—	Force re-enhancement of already processed images (not recommended)
-T <n>	Integer	Number of worker threads. Defaults to physical CPU core count.

Information options

Flag	Description
-I	Display license information. For GUID libraries, the GUID must be specified using -g GUID.
-v	Display VIESUS library version
-h	Show help information

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Output behavior

When processing images, VIESUS writes a results text file alongside the enhanced images. The file contains one line per processed image with its error code, plus processing statistics.

Input source	Results file name
-f direct files	Images.res
-l ImageList.lst	ImageList.res

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Output naming

Flag combination	Example input	Example output	Location
-s	photo.jpg	photo_viesus.jpg	Same folder as input
-n "_custom"	photo.jpg	photo_custom.jpg	Same folder as input
-b "output" -s	photo.jpg	photo_viesus.jpg	output/ folder
-i	photo.jpg	photo.jpg	Same location (overwrites)

-i overwrites the original. Back up source images before using it. There is no undo.

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Image list format

The simplest image list has one image path per line:

C:\Photos\image1.jpg
C:\Photos\image2.png
D:\Pictures\vacation\sunset.jpg

You can also specify a destination path per image using a pipe separator:

C:\Photos\image1.jpg|D:\Output\image1_enhanced.jpg
C:\Photos\image2.png|D:\Output\image2_enhanced.png

Creating an image list

Windows

# All JPG files recursively
dir /b /s *.JPG > Images.lst

# Multiple extensions
dir /b /s *.jpg *.png *.tiff > Images.lst

# Specific folder
dir /b "C:\Photos\*.jpg" > Images.lst

Linux

# All JPG files recursively
find /path/to/images -name "*.jpg" > images.lst

# Multiple extensions
find /path/to/images \( -name "*.jpg" -o -name "*.png" \) > images.lst

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Examples

Process a folder of images with a config

# Create image list (Windows)
dir /b /s *.JPG > Images.lst

# Process using image list
viesus -l Images.lst -s -p "TempFolder\Viesus_Configuration.json" -n "_myConfig" -b "TempFolder"

Process individual files with a custom suffix

viesus -s -n "_enhanced" -p "config.json" -f image1.jpg image2.jpg image3.jpg

Process files and save to a different directory

viesus -b "C:\output" -s -p "settings.json" -f "C:\input\photo.jpg"

Professional batch — EXIF-filtered, custom suffix, 8 threads

viesus -l photos.lst -e -s -n "_pro" -p "professional.json" -b "enhanced"

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Best practices

• Use image lists for large batches — calling -f with thousands of files exceeds command-line length limits on Windows.
• Test on a small subset first — validate your config before kicking off a 100,000-image run.
• Back up before -i — it overwrites originals with no recovery path.
• Monitor disk space when using -b — output files can match or exceed source size, especially after AI Upscaling.
• Use -e to skip non-photographic images — improves throughput when the source contains screenshots or graphics.

Performance tips

• Batch size: process in batches that fit in memory rather than passing one giant list.
• Storage: use SSD storage for both input and output paths to avoid I/O bottlenecks.
• Parallelism: run multiple CLI instances in parallel rather than increasing threads inside one — single-threaded is fastest per image. See Performance Tuning.
• Network paths: avoid processing over SMB / NFS where possible — copy locally, process, copy back.
• EXIF filtering: -e saves time on heterogeneous source folders.

For deeper guidance, see Operations → Performance Tuning and Benchmarks.