AI Engine Reference

The @ashim/ai package bridges Node.js to a persistent Python sidecar for all ML operations. The dispatcher process stays alive between requests for fast warm-start performance. GPU is auto-detected at startup and used when available.

13 AI tool routes. All models run locally - no internet required after initial model download.

Architecture

Node.js Tool Route
      │
      ▼
 @ashim/ai bridge.ts
      │ (stdin/stdout JSON + stderr progress events)
      ▼
 Python dispatcher (persistent process)
      │
      ├─ remove_bg.py        (rembg / BiRefNet)
      ├─ upscale.py          (RealESRGAN)
      ├─ inpaint.py          (LaMa ONNX)
      ├─ ocr.py              (PaddleOCR / Tesseract)
      ├─ detect_faces.py     (MediaPipe)
      ├─ face_landmarks.py   (MediaPipe landmarks)
      ├─ enhance_faces.py    (GFPGAN / CodeFormer)
      ├─ colorize.py         (DDColor)
      ├─ noise_removal.py    (tiered denoising)
      ├─ red_eye_removal.py  (landmark + color analysis)
      ├─ restore.py          (scratch repair + enhancement + denoising)
      └─ seam_carving        (Go caire binary - not Python)

Timeouts: 300 s default; OCR and BiRefNet background removal get 600 s.

Background Removal

Function: removeBackground
Tool route: remove-background
Model: rembg with BiRefNet (default) or U2-Net variants

Parameter	Type	Default	Description
model	string	birefnet-general	Model variant - see table below
alphaMattingForeground	number (1–255)	240	Foreground threshold for alpha matting
alphaMattingBackground	number (1–255)	10	Background threshold for alpha matting
returnMask	boolean	false	Return the mask instead of the cutout
backgroundColor	string	-	Fill removed area (hex color or "transparent")

Available models:

Model ID	Best for
birefnet-general	General purpose (default)
birefnet-portrait	People / portraits
birefnet-dis	Dichotomous Image Segmentation
birefnet-hrsod	High-resolution salient objects
birefnet-cod	Camouflaged objects
u2net	Fast general purpose
u2net_human_seg	Human segmentation
isnet-general-use	High quality general

Image Upscaling

Function: upscale
Tool route: upscale
Model: RealESRGAN (with Lanczos fallback on CPU-constrained systems)

Parameter	Type	Default	Description
scale	2 | 4	4	Upscale factor
model	string	realesrgan-x4plus	Model variant
faceEnhance	boolean	false	Apply GFPGAN face enhancement pass
denoise	number (0–1)	0.5	Denoising strength
format	string	-	Output format override
quality	number	95	Output quality (for JPEG/WebP)

OCR / Text Extraction

Function: extractText
Tool route: ocr
Models: Tesseract (fast), PaddleOCR PP-OCRv5 (balanced), PaddleOCR-VL 1.5 (best)

Parameter	Type	Default	Description
quality	fast | balanced | best	balanced	Processing tier
language	string	en	Language code (ISO 639-1)
enhance	boolean	false	Pre-process image to improve OCR accuracy

Returns structured results with bounding boxes, confidence scores, and extracted text blocks.

Face / PII Blur

Function: blurFaces
Tool route: blur-faces
Model: MediaPipe face detection

Parameter	Type	Default	Description
blurRadius	number	30	Gaussian blur radius
sensitivity	number (0–1)	0.5	Detection confidence threshold

Face Enhancement

Function: enhanceFaces
Tool route: enhance-faces
Models: GFPGAN, CodeFormer

Parameter	Type	Default	Description
model	gfpgan | codeformer	gfpgan	Enhancement model
strength	number (0–1)	0.7	Enhancement strength
sensitivity	number (0–1)	0.5	Face detection threshold
centerFace	boolean	false	Focus enhancement on center face only

AI Colorization

Function: colorize
Tool route: colorize
Model: DDColor (with OpenCV DNN fallback)

Converts black-and-white or grayscale photos to full color.

Parameter	Type	Default	Description
intensity	number (0–1)	0.85	Color saturation strength
model	string	ddcolor	Model variant

Noise Removal

Function: noiseRemoval
Tool route: noise-removal

Three-tier denoising pipeline (fast: OpenCV bilateral filter; balanced: frequency-domain; best: deep learning model).

Parameter	Type	Default	Description
quality	fast | balanced | best	balanced	Processing tier
strength	number (0–1)	0.5	Denoising strength
preserveDetail	boolean	true	Edge-preserving mode
colorNoise	boolean	false	Target color noise specifically

Red Eye Removal

Function: removeRedEye
Tool route: red-eye-removal

Detects face landmarks, locates eye regions, and corrects red-channel oversaturation.

Parameter	Type	Default	Description
sensitivity	number (0–1)	0.5	Red pixel detection threshold
strength	number (0–1)	0.9	Correction strength

Photo Restoration

Function: restorePhoto
Tool route: restore-photo

Multi-step pipeline for old or damaged photos: scratch/tear detection and repair → face enhancement → denoising → optional colorization.

Parameter	Type	Default	Description
mode	auto | light | heavy	auto	Restoration intensity
scratchRemoval	boolean	true	Detect and repair scratches, tears
faceEnhancement	boolean	true	Apply face enhancement pass
fidelity	number (0–1)	0.7	Face enhancement strength
denoise	boolean	true	Apply denoising pass
denoiseStrength	number (0–100)	40	Denoising strength
colorize	boolean	false	Colorize after restoration

Passport Photo

Function: Uses detectFaceLandmarks + removeBackground
Tool route: passport-photo
Model: MediaPipe face landmarks

Generates government-compliant ID photos. Supports 37 countries across 6 regions (Americas, Europe, Asia, Africa, Oceania, Middle East). Each spec includes physical dimensions, DPI, head-height ratio, eye-line position, and background color requirements.

Parameter	Type	Default	Description
country	string	us	ISO country code (see list in UI)
printLayout	4x6 | A4 | none	none	Output as print sheet or standalone
backgroundColor	string	country default	Background fill color

Object Erasing (Inpainting)

Function: inpaint
Tool route: erase-object
Model: LaMa via ONNX Runtime

Parameter	Type	Required	Description
maskData	string	Yes	Base64-encoded PNG mask (white = erase)
maskThreshold	number (0–255)	No	Threshold for mask binarization

GPU-accelerated when an NVIDIA GPU is available.

Smart Crop

Function: Uses MediaPipe + Sharp attention/entropy
Tool route: smart-crop
Model: MediaPipe face detection

Parameter	Type	Default	Description
mode	subject | face | trim	subject	Crop strategy
width	number	-	Output width
height	number	-	Output height
facePreset	string	-	Preset framing when mode=face

Face presets:

Preset	Head ratio	Best for
close-up	1.8× face	Headshots
head-and-shoulders	2.8× face	Profile photos
upper-body	4.5× face	LinkedIn / formal
half-body	7.0× face	Full upper body

Content-Aware Resize (Seam Carving)

Function: seamCarve
Tool route: content-aware-resize
Engine: Go caire binary (not Python - no GPU benefit)

Intelligently resizes images by removing or adding low-energy seams, preserving important content.

Parameter	Type	Default	Description
width	number	-	Target width
height	number	-	Target height
protectFaces	boolean	true	Protect detected face regions from seam removal
blurRadius	number	0	Pre-blur to reduce noise sensitivity
sobelThreshold	number	10	Edge sensitivity threshold
square	boolean	false	Force square output

Max input edge before auto-downscaling: 1200 px.