IMAGDressing-v1 is a customizable virtual dressing system designed to generate editable human images with fixed garments and optional conditions. It addresses the limitations of existing virtual try-on (VTON) technologies by focusing on comprehensive garment displays for merchants, allowing flexible control over faces, poses, and scenes. The system incorporates a garment UNet that captures semantic features from CLIP and texture features from VAE, and a hybrid attention module that integrates garment features into a frozen denoising UNet, enabling scene control through text. IMAGDressing-v1 can be combined with extensions like ControlNet and IP-Adapter to enhance image diversity and controllability. A large-scale interactive garment pairing (IGPair) dataset with over 300,000 clothing and dressed image pairs is released to support the system. The system achieves state-of-the-art performance in human image synthesis under various controlled conditions. The code and model are available at https://github.com/muzishen/IMAGDressing.IMAGDressing-v1 is a customizable virtual dressing system designed to generate editable human images with fixed garments and optional conditions. It addresses the limitations of existing virtual try-on (VTON) technologies by focusing on comprehensive garment displays for merchants, allowing flexible control over faces, poses, and scenes. The system incorporates a garment UNet that captures semantic features from CLIP and texture features from VAE, and a hybrid attention module that integrates garment features into a frozen denoising UNet, enabling scene control through text. IMAGDressing-v1 can be combined with extensions like ControlNet and IP-Adapter to enhance image diversity and controllability. A large-scale interactive garment pairing (IGPair) dataset with over 300,000 clothing and dressed image pairs is released to support the system. The system achieves state-of-the-art performance in human image synthesis under various controlled conditions. The code and model are available at https://github.com/muzishen/IMAGDressing.