File size: 1,393 Bytes
12863e1 2cf6be0 f1759ae 05d3d42 2cf6be0 f1759ae 6b0d828 2cf6be0 12863e1 0fc6bc9 4095388 af84433 f1759ae 987f112 f1759ae 2cf6be0 fa0ee64 fb01197 0fc6bc9 f0f8ecd 262e1d3 f1759ae ad9ba71 f1759ae 2cf6be0 fa0ee64 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 |
import spaces
import gradio as gr
import torch
from diffusers import DiffusionPipeline
import rembg
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
pipe.to("cuda")
# Function to generate an image from text using diffusion
@spaces.GPU
def generate_image(prompt):
prompt += "no background, side view, minimalist shot"
image = pipe(prompt).images[0]
image2 = rembg.remove(image)
return image, image2
_TITLE = "Shoe Generator"
with gr.Blocks(_TITLE) as ShoeGen:
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label="Enter a discription of a shoe")
# neg_prompt = gr.Textbox(label="Enter a negative prompt", value="low quality, watermark, ugly, tiling, poorly drawn hands, poorly drawn feet, poorly drawn face, out of frame, extra limbs, body out of frame, blurry, bad anatomy, blurred, watermark, grainy, signature, cut off, draft, closed eyes, text, logo")
button_gen = gr.Button("Generate Image")
with gr.Column():
image = gr.Image(label="Generated Image", show_download_button=True)
image_nobg = gr.Image(label="Generated Image (No Background)", show_download_button=True)
button_gen.click(generate_image, inputs=[prompt], outputs=[image, image_nobg])
ShoeGen.launch()
|