Version 1.3 of Qwen Image Edit for Urbanism introduces mask-controlled editing in ComfyUI, enabling precise, localized image transformations using prompts or reference images. The new Grow Mask utility softens boundaries, preserves unmasked areas, and integrates seamlessly with existing single-image and sequential workflows.
ComfyUI Sequential Image Editing for Urbanism arrives in Qwen v1.2 with custom Python nodes, multi-image batch processing, and a six-slot buffer for reproducible urban edits. This version streamlines automated workflows for researchers, designers, and architects working with street and neighborhood imagery.
Qwen Image Edit for Urbanism v1.1 expands local AI editing in ComfyUI with advanced sampling and dual-image workflows. The new Lightning LoRA system improves realism, texture fidelity, and processing speed, enabling fast, privacy-preserving urban scene transformation—entirely offline.
Learn how to build a fully local AI image-editing workflow for urbanism and architectural visualization using ComfyUI and Qwen-Image-Edit. This step-by-step guide runs entirely offline with GGUF models, providing fast, private, and realistic visual edits.
Calculating Nearest Neighbor Distance (NND) and comparing it with Complete Spatial Randomness (CSR) can be useful in various fields. In this tutorial, we will see together how to calculate a nearest neighbor distance from a given point pattern and compare it to a random distribution (CSR).
