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from huggingface_hub import InferenceClient
from PIL import Image
import gradio as gr
import os
# Load token from environment
token = os.environ["HF_TOKEN"]
# Create the client
client = InferenceClient(
model="artificialguybr/TshirtDesignRedmond-V2",
provider="fal-ai",
token=token,
)
# Trigger word for model
trigger_word = "T shirt design, TshirtDesignAF, "
def generate_image(dress_type, fabric_type, color_type, design):
base_description = (
f"Hyper-realistic scene of a single {color_type} {dress_type} "
f"made of {fabric_type} with {design} printed on it, hanging neatly on a wooden hanger "
f"against a clean matte concrete wall. The {dress_type} is centered, casting a soft natural shadow, "
f"detailed fabric folds visible, studio lighting setup with soft diffused highlights, "
f"4K resolution, shallow depth of field, ultra-clean minimalist aesthetic, fashion editorial style."
)
full_prompt = f"{base_description} {trigger_word}"
print("Generating image with:", full_prompt)
image = client.text_to_image(
prompt=full_prompt,
negative_prompt="(worst quality, low quality, lowres, bad photo, ...)",
num_inference_steps=30,
guidance_scale=7.5,
)
return image
iface = gr.Interface(
fn=generate_image,
inputs=[
gr.Textbox(label="Dress Type"),
gr.Textbox(label="Fabric Type"),
gr.Textbox(label="Color Type"),
gr.Textbox(label="Design"),
],
outputs="image",
title="TShirt Design XL Image Generator",
description="Powered by Redmond.AI — Generate stunning T-shirt designs from simple attributes.",
)
print("Launching Gradio interface...")
iface.launch() |