Image Resize

The image resize tool computes output dimensions from inputs and optional mode flags. Conceptually, it treats an input image as a rectangle defined by width and height, and applies a scaling factor derived from target bounds and aspect rules. It separates dimension calculation from the actual image processing, enabling downstream pipelines to pass the computed width/height to a separate encoder. Beneficiaries include content teams that publish assets to multiple channels, developers building automation scripts, and QA engineers validating asset specs.
The tool supports both strict dimension matching and proportional resizing, with clear validation and deterministic results. Core features include input validation, aspect-ratio preservation, multiple resize modes (fit inside and cover), optional padding, and an approximate file-size estimate. Typical use cases include creating 1920x1080 hero images from larger originals, generating square thumbnails from landscape photos, and producing consistent 256x256 app icons.
The domain logic emphasizes correctness, predictability, and integration readiness, avoiding any destructive actions on source data and exposing explicit outputs for further processing. Unique value resides in explicit dimension formulas and safe defaults that reduce failed asset deliveries in production pipelines. When used with batch automation, the tool can be scripted to resize large sets of images with consistent results, ensuring brand consistency across channels.
Inputs and outputs are strictly numeric and dimensional; the tool does not perform color space conversion or content-aware resizing. It provides final_width_px, final_height_px, and estimated_file_size_kb, along with a status flag to indicate feasibility.