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API Reference

Complete API reference for the VIESUS Node.js native module — MyViesusObject constructor, Enhance method, error codes, and result JSON.

Linux Only

The VIESUS Node.js module is available on Linux only.


Import

const viesus = require('viesus');

new viesus.MyViesusObject(guid)

Creates and initializes a VIESUS enhancer instance. Create one object per worker thread and reuse it across multiple Enhance() calls — initialization is expensive.

Parameter
Type
Description

guid

string

Your VIESUS license GUID

const viesusObj = new viesus.MyViesusObject('4e8f35ab-7f72-4b1e-a1fd-2b5e9c58e9d3');

viesusObj.Enhance(fromPath, toPath, iniPath, resPath)

Enhances a single image. Synchronous — must be called from a worker thread, not the main thread.

Parameter
Type
Description

fromPath

string

Absolute path to the input image

toPath

string

Absolute path for the enhanced output image

iniPath

string

Absolute path to the viesusini.json configuration file

resPath

string

Absolute path for the result JSON output file

Returns: number

  • > 0 — success; value is processing time in milliseconds

  • < 0 — error; see error codes


Error codes

Code
Description

-1

Init failed

-2

GUID wrong

-3

Internal error

-4

Loading image not possible

-5

Can't open file

-6

File not found

-7

File is empty

-8

Memory open internal error

-9

Enhancement failed — contact info@viesus.com

-10

Parameter file not found

-11

Parameter file empty

-12

Output format not supported

-13

Error writing result file

-126

Enhancement failed — image was already enhanced

-378

Wrong GUID

< -18

Internal error — contact info@viesus.com


Result JSON

When WriteResultFiles: 1 is set in viesusini.json, a JSON file is written to resPath after each enhancement with per-image processing details:

Field
Type
Description

brightCorrStrength

float

Applied brightness correction strength

colorCorrStrength

float

Applied color correction strength

fdApplied

int

1 if face detection ran

ieApplied

int

1 if image enhancement ran

isArtificial

int

1 if image was classified as artificial/synthetic

isMonochrome

int

1 if image was detected as monochrome

locShpApplied

int

1 if local sharpening was applied

rszApplied

int

1 if resizing was applied

rszSRApplied

int

1 if AI upscaling was used for resize

arApplied

int

1 if artifact removal was applied

bgApplied

int

1 if background handling was applied


Thread pool pattern

The recommended production pattern uses node-worker-threads-pool:

See Getting Started for the complete example.

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