SnapOtter/apps/docs/api/ai.md

---
description: AI engine reference with all local ML tools. Background removal, upscaling, OCR, face detection, photo restoration, and more.
---

# AI Engine Reference

The `@snapotter/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. NVIDIA CUDA is auto-detected at startup and used when available; otherwise AI tools run on CPU.

Intel/AMD iGPU acceleration through VA-API, Quick Sync, or OpenCL is not supported for AI inference today. Mapping `/dev/dri` into a container does not accelerate these Python sidecar tools unless a CUDA-capable NVIDIA GPU is available.

19 Python sidecar AI tools across four modalities (image, audio, video, document), plus 2 tools with optional AI capabilities. All models run locally - no internet required after initial model download.

## Architecture

```
Node.js Tool Route
      |
      v
 @snapotter/ai bridge.ts
      | (stdin/stdout JSON + stderr progress events)
      v
 Python dispatcher (persistent process, "ai" profile)
      |
      |-- remove_bg.py        (rembg / BiRefNet)
      |-- upscale.py          (RealESRGAN)
      |-- inpaint.py          (LaMa ONNX)
      |-- outpaint.py         (LaMa canvas expansion)
      |-- ocr.py              (PaddleOCR / Tesseract)
      |-- ocr_pdf.py          (page-by-page document OCR)
      |-- ocr_preprocess.py   (image enhancement for OCR)
      |-- detect_faces.py     (MediaPipe)
      |-- face_landmarks.py   (MediaPipe landmarks)
      |-- enhance_faces.py    (GFPGAN / CodeFormer)
      |-- colorize.py         (DDColor)
      |-- noise_removal.py    (SCUNet / tiered denoising)
      |-- red_eye_removal.py  (landmark + color analysis)
      |-- restore.py          (scratch repair + enhancement + denoising)
      |-- transcribe.py       (faster-whisper speech-to-text)
      +-- install_feature.py  (on-demand bundle installer)
```

A separate "docs" dispatcher profile replaces the AI allowlist with document-processing scripts (`doc_pagecount`, `doc_health`, `doc_flatten`, `doc_redact`, `doc_text`, `doc_to_word`, `doc_metadata`, `doc_html_pdf`) and skips heavy ML imports.

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

## Feature Bundles

Each AI tool requires a model bundle to be installed before use. Bundles are installed on demand via the admin UI or `install_feature.py`.

| Bundle | Size | Tools |
|--------|------|-------|
| `background-removal` | 4-5 GB | remove-background, passport-photo, transparency-fixer, background-replace, blur-background |
| `face-detection` | 200-300 MB | blur-faces, red-eye-removal, smart-crop |
| `object-eraser-colorize` | 1-2 GB | erase-object, colorize, ai-canvas-expand |
| `upscale-enhance` | 4-5 GB | upscale, enhance-faces, noise-removal |
| `photo-restoration` | 800 MB - 1 GB | restore-photo |
| `ocr` | 3-4 GB | ocr, ocr-pdf |
| `transcription` | ~600 MB | transcribe-audio, auto-subtitles |

---

## Background Removal

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

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `model` | string | - | Model variant (optional override) |
| `backgroundType` | string | `"transparent"` | One of: `transparent`, `color`, `gradient`, `blur`, `image` |
| `backgroundColor` | string | - | Hex color for solid background |
| `gradientColor1` | string | - | First gradient color |
| `gradientColor2` | string | - | Second gradient color |
| `gradientAngle` | number | - | Gradient angle in degrees |
| `blurEnabled` | boolean | - | Enable background blur effect |
| `blurIntensity` | number (0-100) | - | Blur intensity |
| `shadowEnabled` | boolean | - | Enable drop shadow on subject |
| `shadowOpacity` | number (0-100) | - | Shadow opacity |
| `outputFormat` | string | - | Output format: `png`, `webp`, or `avif` |
| `edgeRefine` | integer (0-3) | - | Edge refinement level |
| `decontaminate` | boolean | - | Remove color bleed from edges |

## Background Replace

**Tool route:** `background-replace`  
**Model:** rembg / BiRefNet (shared with remove-background)

Removes the background and replaces it with a solid color or gradient.

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `backgroundType` | `"color"` \| `"gradient"` | `"color"` | Background mode |
| `color` | string | `"#ffffff"` | Background hex color (when `backgroundType` is `color`) |
| `gradientColor1` | string | - | First gradient hex color |
| `gradientColor2` | string | - | Second gradient hex color |
| `gradientAngle` | integer (0-360) | `180` | Gradient angle in degrees |
| `feather` | integer (0-20) | `0` | Edge feathering radius |
| `format` | `"png"` \| `"webp"` | `"png"` | Output format |

## Blur Background

**Tool route:** `blur-background`  
**Model:** rembg / BiRefNet (shared with remove-background)

Blurs the background while keeping the subject sharp.

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `intensity` | integer (1-100) | `50` | Blur intensity |
| `feather` | integer (0-20) | `0` | Edge feathering radius |
| `format` | `"png"` \| `"webp"` | `"png"` | Output format |

## Image Upscaling

**Tool route:** `upscale`  
**Model:** RealESRGAN (with Lanczos fallback when unavailable)

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `scale` | number | `2` | Upscale factor |
| `model` | string | `"auto"` | Model variant |
| `faceEnhance` | boolean | `false` | Apply GFPGAN face enhancement pass |
| `denoise` | number | `0` | Denoising strength |
| `format` | string | `"auto"` | Output format override |
| `quality` | number | `95` | Output quality (1-100) |

## OCR / Text Extraction

**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 | `"auto"` | Language: `auto`, `en`, `de`, `fr`, `es`, `zh`, `ja`, `ko` |
| `enhance` | boolean | `true` | Pre-process image to improve OCR accuracy |
| `engine` | string | - | Deprecated. Maps `tesseract` to `fast`, `paddleocr` to `balanced` |

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

## PDF OCR

**Tool route:** `ocr-pdf`  
**Models:** Same tier system as image OCR

Extracts text from scanned PDF documents using AI-powered OCR, page by page.

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `quality` | `"fast"` \| `"balanced"` \| `"best"` | `"balanced"` | Processing tier |
| `language` | string | `"auto"` | Language: `auto`, `en`, `de`, `fr`, `es`, `zh`, `ja`, `ko` |
| `pages` | string | `"all"` | Page selection: `"all"`, `"1-3"`, `"1,3,5"` |

## Face / PII Blur

**Tool route:** `blur-faces`  
**Model:** MediaPipe face detection

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `blurRadius` | number (1-100) | `30` | Gaussian blur radius |
| `sensitivity` | number (0-1) | `0.5` | Detection confidence threshold |

## Face Enhancement

**Tool route:** `enhance-faces`  
**Models:** GFPGAN, CodeFormer

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `model` | `"auto"` \| `"gfpgan"` \| `"codeformer"` | `"auto"` | Enhancement model |
| `strength` | number (0-1) | `0.8` | Enhancement strength |
| `sensitivity` | number (0-1) | `0.5` | Face detection threshold |
| `onlyCenterFace` | boolean | `false` | Enhance only the most central face |

## AI Colorization

**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) | `1.0` | Color saturation strength |
| `model` | `"auto"` \| `"ddcolor"` \| `"opencv"` | `"auto"` | Model variant |

## Noise Removal

**Tool route:** `noise-removal`  
**Model:** SCUNet (tiered denoising pipeline)

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `tier` | `"quick"` \| `"balanced"` \| `"quality"` \| `"maximum"` | `"balanced"` | Processing tier |
| `strength` | number (0-100) | `50` | Denoising strength |
| `detailPreservation` | number (0-100) | `50` | How much detail to preserve; higher keeps more texture |
| `colorNoise` | number (0-100) | `30` | Color noise reduction strength |
| `format` | string | `"original"` | Output format: `original`, `png`, `jpeg`, `webp`, `avif`, `jxl` |
| `quality` | number (1-100) | `90` | Output encoding quality |

## Red Eye Removal

**Tool route:** `red-eye-removal`

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

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `sensitivity` | number (0-100) | `50` | Red pixel detection threshold |
| `strength` | number (0-100) | `70` | Correction strength |
| `format` | string | - | Output format override (optional) |
| `quality` | number (1-100) | `90` | Output quality |

## Photo Restoration

**Tool route:** `restore-photo`

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

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `scratchRemoval` | boolean | `true` | Detect and repair scratches, tears |
| `faceEnhancement` | boolean | `true` | Apply face enhancement pass |
| `fidelity` | number (0-1) | `0.7` | Face enhancement strength (higher = more conservative) |
| `denoise` | boolean | `true` | Apply denoising pass |
| `denoiseStrength` | number (0-100) | `25` | Denoising strength |
| `colorize` | boolean | `false` | Colorize after restoration |
| `colorizeStrength` | number (0-100) | `85` | Colorization intensity |

## Passport Photo

**Tool route:** `passport-photo`  
**Models:** MediaPipe face landmarks + BiRefNet background removal

Two-phase workflow: analyze (detect face + remove background) then generate (crop, resize, tile). Supports 37+ countries across 6 regions.

### Phase 1: Analyze

`POST /api/v1/tools/image/passport-photo/analyze`

Accepts an image file (multipart). Returns face landmark data, a base64 preview, and image dimensions.

### Phase 2: Generate

`POST /api/v1/tools/image/passport-photo/generate`

Accepts a JSON body with the Phase 1 results plus generation settings:

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `jobId` | string | (required) | Job ID from Phase 1 |
| `filename` | string | (required) | Original filename from Phase 1 |
| `countryCode` | string | (required) | ISO country code (e.g., `US`, `GB`, `IN`) |
| `documentType` | string | `"passport"` | Document type |
| `bgColor` | string | `"#FFFFFF"` | Background color hex |
| `printLayout` | string | `"none"` | Print layout: `none`, `4x6`, `a4`, `letter` |
| `maxFileSizeKb` | number | `0` | Max file size in KB (0 = no limit) |
| `dpi` | number (72-1200) | `300` | Output DPI |
| `customWidthMm` | number | - | Custom width in mm (overrides country spec) |
| `customHeightMm` | number | - | Custom height in mm (overrides country spec) |
| `zoom` | number (0.5-3) | `1` | Zoom factor |
| `adjustX` | number | `0` | Horizontal position adjustment |
| `adjustY` | number | `0` | Vertical position adjustment |
| `landmarks` | object | (required) | Landmarks from Phase 1 |
| `imageWidth` | number | (required) | Image width from Phase 1 |
| `imageHeight` | number | (required) | Image height from Phase 1 |

## Object Erasing (Inpainting)

**Tool route:** `erase-object`  
**Model:** LaMa via ONNX Runtime

The mask is sent as a **second file part** (fieldname `mask`), not as base64. White pixels in the mask indicate areas to erase. The `format` and `quality` settings are sent as top-level form fields.

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `file` | file | (required) | Source image (multipart) |
| `mask` | file | (required) | Mask image (multipart, fieldname `mask`, white = erase) |
| `format` | string | `"auto"` | Output format: `auto`, `png`, `jpg`, `jpeg`, `webp`, `tiff`, `gif`, `avif`, `heic`, `heif`, `jxl` |
| `quality` | integer (1-100) | `95` | Output quality |

CUDA-accelerated when an NVIDIA GPU is available.

## AI Canvas Expand

**Tool route:** `ai-canvas-expand`  
**Model:** LaMa-based outpainting

Expands the canvas of an image in any direction and fills new areas with AI-generated content that matches the existing image.

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `extendTop` | integer | `0` | Pixels to extend at the top |
| `extendRight` | integer | `0` | Pixels to extend at the right |
| `extendBottom` | integer | `0` | Pixels to extend at the bottom |
| `extendLeft` | integer | `0` | Pixels to extend at the left |
| `tier` | `"fast"` \| `"balanced"` \| `"high"` | `"balanced"` | Quality tier |
| `format` | string | `"auto"` | Output format: `auto`, `png`, `jpg`, `jpeg`, `webp`, `tiff`, `gif`, `avif`, `heic`, `heif`, `jxl` |
| `quality` | integer (1-100) | `95` | Output quality |

At least one extend direction must be greater than 0.

## Smart Crop

**Tool route:** `smart-crop`  
**Model:** MediaPipe face detection (face mode only)

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `mode` | string | `"subject"` | Crop strategy: `subject`, `face`, `trim` |
| `strategy` | `"attention"` \| `"entropy"` | `"attention"` | Strategy for subject mode |
| `width` | integer | - | Output width |
| `height` | integer | - | Output height |
| `padding` | integer (0-50) | `0` | Padding percentage around subject |
| `facePreset` | string | `"head-shoulders"` | Preset framing when `mode=face` |
| `sensitivity` | number (0-1) | `0.5` | Face detection threshold |
| `threshold` | integer (0-255) | `30` | Background detection threshold (trim mode) |
| `padToSquare` | boolean | `false` | Pad trimmed result to a square |
| `padColor` | string | `"#ffffff"` | Background color for square padding |
| `targetSize` | integer | - | Target size for padded output (pixels) |
| `quality` | integer (1-100) | - | Output quality |

Legacy `mode` values `attention` and `content` are accepted and mapped to `subject` and `trim` respectively.

**Face presets:**

| Preset | Best for |
|--------|---------|
| `closeup` | Headshots |
| `head-shoulders` | Profile photos |
| `upper-body` | LinkedIn / formal |
| `half-body` | Full upper body |

## Transcribe Audio

**Tool route:** `transcribe-audio`  
**Model:** faster-whisper

Converts speech to text. Supports plain text, SRT, and VTT output formats.

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `language` | string | `"auto"` | Language: `auto`, `en`, `de`, `fr`, `es`, `zh`, `ja`, `ko`, `id`, `th`, `vi` |
| `outputFormat` | `"txt"` \| `"srt"` \| `"vtt"` | `"txt"` | Output format |

## Auto Subtitles

**Tool route:** `auto-subtitles`  
**Model:** faster-whisper (extracts audio from video, then transcribes)

Generates subtitle files from a video's audio track.

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `language` | string | `"auto"` | Language: `auto`, `en`, `de`, `fr`, `es`, `zh`, `ja`, `ko`, `id`, `th`, `vi` |
| `format` | `"srt"` \| `"vtt"` | `"srt"` | Output subtitle format |

## PNG Transparency Fixer

**Tool route:** `transparency-fixer`  
**Model:** BiRefNet HR-matting (2048x2048 resolution)

Fixes "fake transparent" PNGs where the background was removed but left behind fringing, halos, or semi-transparent artifacts. Uses BiRefNet's high-resolution matting model to produce a clean alpha channel, then applies configurable defringe processing to remove color contamination along edges.

**OOM fallback chain:** If BiRefNet HR-matting exceeds available memory, the tool automatically falls back to `birefnet-general`, then to `u2net`.

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `defringe` | number (0-100) | `30` | Edge defringe strength to remove color contamination |
| `outputFormat` | `"png"` \| `"webp"` | `"png"` | Output image format |
| `removeWatermark` | boolean | `false` | Apply watermark removal pre-processing (median filter) |

```bash
curl -X POST http://localhost:1349/api/v1/tools/image/transparency-fixer \
  -H "Authorization: Bearer <token>" \
  -F "file=@fake-transparent.png" \
  -F 'settings={"defringe":30,"outputFormat":"png"}'
```

---

## Tools with Optional AI Capabilities

The following tools are not Python sidecar tools but use AI features when certain options are enabled.

### Image Enhancement

**Tool route:** `image-enhancement`  
**Engine:** Analysis-based (Sharp histogram and statistics)

Analyzes the image and applies automatic corrections for exposure, contrast, white balance, saturation, sharpness, and noise. Supports scene-specific modes.

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `mode` | `"auto"` \| `"portrait"` \| `"landscape"` \| `"low-light"` \| `"food"` \| `"document"` | `"auto"` | Scene mode for tuning corrections |
| `intensity` | number (0-100) | `50` | Overall correction strength |
| `corrections.exposure` | boolean | `true` | Apply exposure correction |
| `corrections.contrast` | boolean | `true` | Apply contrast correction |
| `corrections.whiteBalance` | boolean | `true` | Apply white balance correction |
| `corrections.saturation` | boolean | `true` | Apply saturation correction |
| `corrections.sharpness` | boolean | `true` | Apply sharpness correction |
| `corrections.denoise` | boolean | `true` | Apply denoising |
| `deepEnhance` | boolean | `false` | Enable AI noise removal via SCUNet (requires `upscale-enhance` bundle) |

An additional analysis endpoint is available at `POST /api/v1/tools/image/image-enhancement/analyze` which returns the detected corrections without applying them.

### Content-Aware Resize (Seam Carving)

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

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

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `width` | number | - | Target width |
| `height` | number | - | Target height |
| `protectFaces` | boolean | `false` | Protect detected face regions (requires `face-detection` bundle) |
| `blurRadius` | number (0-20) | `4` | Pre-blur for energy calculation |
| `sobelThreshold` | number (1-20) | `2` | Edge sensitivity threshold |
| `square` | boolean | `false` | Force square output |