KREAM-Product-Generator

KREAM-Product-Generator is a finetuned text-to-image generative model with a custom dataset collected from KREAM, one of the best online-resell market in Korea. Have fun creating realistic, high-quality fashion items!

You can see detailed instructions to finetune and inference the model in my github repository: easy-finetuning-stable-diffusion.

This model is more precise version compared to the previous model: hahminlew/sdxl-kream-model-lora.

*Generate various creative products through prompt engineering!

Results

Prompts

• outer, The Nike x Balenciaga Down Jacket Black, a photography of a black down jacket with a logo on the chest.
• top, (W) Moncler x Adidas Slip Hoodie Dress Cream, a photography of a cream dress and a hood on.
• bottom, Supreme Animal Print Baggy Jean Washed Indigo - 23FW, a photography of a dark blue jean with an animal printing on.
• outer, The North Face x Supreme White Label Nuptse Down Jacket Cream, a photography of a white puffer jacket with a red box logo on the front.
• top, The Supreme x Stussy Oversized Cotton Black Hoodie, a photography of a black shirt with a hood on and a logo on the chest.
• bottom, IAB Studio x Stussy Tie-Dye Sweat Wooven Shorts, a photography of a dye short pants with a logo.

Inference

from diffusers import DiffusionPipeline
import torch

pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16)
pipe.to("cuda")
pipe.load_lora_weights("hahminlew/sdxl-kream-model-lora-2.0")

prompt = "outer, The Nike x Balenciaga Down Jacket Black, a photography of a black down jacket with a logo on the chest."

image = pipe(prompt, num_inference_steps=45, guidance_scale=7.5).images[0]
image.save("example.png")

LoRA text2image fine-tuning - hahminlew/sdxl-kream-model-lora-2.0

These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were fine-tuned on the hahminlew/kream-product-blip-captions dataset.

LoRA for the text encoder was enabled: False.

Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.

Citation

If you use KREAM Product Dataset and the model in your research or projects, please cite it as:

@misc{lew2023kream,
      author = {Lew, Hah Min},
      title = {KREAM Product BLIP Captions},
      year={2023},
      howpublished= {\url{https://huggingface.co/datasets/hahminlew/kream-product-blip-captions/}}
}