ImageProc API Reference: Core Modules The ImageProc API is a high-performance, developer-friendly library designed for programmatic image manipulation and analysis. Built to handle scale and speed, ImageProc provides a robust suite of tools for web applications, mobile platforms, and automated data pipelines. This reference document outlines the four core modules that form the foundation of the ImageProc ecosystem: ImageIO, Transform, Filter, and ColorSpace. 1. ImageIO Module
The ImageIO module handles all input and output tasks, serving as the gateway for bringing images into the processing pipeline and exporting them upon completion. It provides comprehensive codec support, including baseline formats like JPEG and PNG, as well as modern, web-optimized formats such as WebP and AVIF. Primary Functions
load_from_file(path: string, options: LoadOptions): ImageLoads an image asset from a local storage path. The LoadOptions object allows developers to specify raw pixel layouts, streaming buffers, or metadata preservation levels.
load_from_url(url: string, headers: Map, options: LoadOptions): ImageAsynchronously fetches an image from an HTTP/HTTPS endpoint. It includes built-in retry logic and timeout handling suitable for cloud infrastructure workflows.
save_to_file(image: Image, path: string, format: ExportFormat, quality: int): booleanWrites the processed image object back to disk. The quality parameter accepts integers from 1 to 100 to balance compression ratios against visual fidelity.
export_to_buffer(image: Image, format: ExportFormat): ArrayBufferSerializes the image data directly into an in-memory byte array, optimizing workflows that require immediate transmission over networks or WebSockets. 2. Transform Module
The Transform module is engineered for spatial manipulation. It alters the geometric structure of an image by repositioning pixels, resizing dimensions, or changing orientations using advanced mathematical interpolation algorithms. Primary Functions
resize(image: Image, width: int, height: int, interpolation: InterpolationType): ImageScales an image to target dimensions. Developers can select Nearest Neighbor for pixel art, Bilinear for speed, or Lanczos resampling for high-fidelity photographic downscaling.
crop(image: Image, x: int, y: int, width: int, height: int): ImageExtracts a rectangular sub-region from the source image. This method throws a bounding box exception if the defined coordinates extend past the canvas boundaries.
rotate(image: Image, degrees: float, expand_canvas: boolean): ImageRotates the image around its central axis. When expand_canvas is set to true, the dimensions of the bounding box automatically grow to prevent clipping the corners of the rotated asset.
flip(image: Image, direction: FlipDirection): ImageMirrors the image along the horizontal, vertical, or both axes simultaneously with near-zero latency by reversing memory arrays. 3. Filter Module
The Filter module applies neighborhood operations to image pixels, enabling complex enhancements, artistic effects, and analytical structural detections. Each operation computes new pixel values based on surrounding pixel matrices. Primary Functions
blur(image: Image, type: BlurType, radius: float): ImageApplies smoothing operations to minimize high-frequency noise. Options include Box Blur for rapid execution or Gaussian Blur for mathematically smooth transitions.
sharpen(image: Image, amount: float, threshold: float): ImageEnhances edge contrast by subtracting an unsharp mask from the original image. The threshold parameter prevents the amplification of low-level background noise.
edge_detect(image: Image, algorithm: EdgeAlgorithm): ImageIdentifies intensity discontinuities within the image. This function supports Sobel, Scharr, and Canny mathematical operators, generating a high-contrast binary map of structural lines.
noise_reduction(image: Image, strength: float): ImageUtilizes non-local means or median filtering to eliminate digital sensor artifacts while preserving fine textural detail across flat regions. 4. ColorSpace Module
The ColorSpace module manages the interpretation and transformation of color data. It allows developers to alter the representation models of pixel channels and adjust fundamental color balancing parameters. Primary Functions
adjust_brightness(image: Image, factor: float): ImageScales the intensity values of all color channels. A factor of 1.0 represents the baseline, values below 1.0 darken the image, and values above 1.0 increase exposure.
adjust_contrast(image: Image, factor: float): ImageModifies the dynamic range of pixel values by shifting highlights and shadows away from or toward the median gray point.
apply_lut(image: Image, lut_table: LookUpTable): ImageMaps source colors to a predefined three-dimensional Lookup Table. This enables instant color grading, cinematic styling, and precise color correction presets. Error Handling and Performance
All core modules are built on thread-safe architecture, allowing parallel asynchronous execution across multi-core systems. If an operation fails due to memory limitations, invalid arguments, or corrupted headers, the API throws structured exceptions containing specific error codes and diagnostics to simplify developer debugging workflows.
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