Workflow Name: Product Packaging Box Cover Image Generator
【Workflow Introduction】
This workflow is somewhat complex. Users first need to upload 5 images. These 5 images include product images and corresponding color ID images specifically created for the product images (since there are 3 products with a total of 5 exposed surfaces, there are 5 color IDs. If the number of exposed surfaces changes, manual adjustments will be needed in the mask section of the workflow). Additionally, 3 cover images need to be carefully selected from numerous pictures. The workflow is divided into two parts: this description focuses on the first part, whose main function is to generate designated images for product packaging boxes. The second part focuses on replacing the background of the product images, which can be achieved using a specialized separate workflow.
Background Replacement Workflow Online URLs:
https://www.runninghub.cn/post/1845758651062743041
https://www.runninghub.ai/post/1845772448322220034
Built-in parameter settings are completed. Welcome to experience it, and have fun!

【Usage Scenarios】
In the field of product packaging design, when companies or designers need to quickly generate diverse product packaging box cover images, this image generator can be highly effective. Whether it is for creating various packaging previews for new product launches or updating series product packaging by adjusting color IDs and cover images to batch-generate different versions of packaging designs, this tool can efficiently accomplish the task. Additionally, for e-commerce merchants creating product display images, if they need to change the product background to match different page styles or promotional themes, the second part of the background replacement workflow can provide a convenient solution. It helps them obtain high-quality, demand-compliant product packaging box covers and related display images in a short time, thereby enhancing product image and sales appeal.

【Key Nodes】Flux1 redux, Flux1 depth

【Model Version】
FLUX
Model Name: Flux1 depth.safetensors

【LoRA Model】
None

【ControlNet Application】
AnyLine Lineart
DA Depth Preprocessor

【K Sampler】
Sampling Method: euler
Scheduler: simple
CFG: 1
Denoising: 1