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import gradio as gr
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import StableDiffusionPipeline
# Load the model and tokenizer
model_id = "stabilityai/stable-diffusion-xl-base-1.0"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
pipe = pipe.to("cpu")
def generate_image(prompt, negative_prompt, size):
if not prompt:
prompt = "a beautiful landscape"
if not negative_prompt:
negative_prompt = ""
width, height = map(int, size.split('x'))
generator = torch.Generator("cpu").manual_seed(42)
# Generate the image
result = pipe(prompt, height=height, width=width, negative_prompt=negative_prompt, generator=generator)
if result is not None and 'images' in result:
return result.images[0]
else:
return None
with gr.Blocks() as demo:
gr.Markdown("## Text to Image SDXL")
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label="Prompt", placeholder="Enter the prompt here...")
negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Enter the negative prompt here...")
size = gr.Dropdown(choices=["512x512", "768x768", "1024x1024"], value="1024x1024", label="Size")
submit = gr.Button("Submit")
with gr.Column():
output = gr.Image(label="Output")
submit.click(generate_image, inputs=[prompt, negative_prompt, size], outputs=output)
demo.launch()
# import gradio as gr
# import torch
# from transformers import CLIPTextModel, CLIPTokenizer
# from diffusers import StableDiffusionPipeline
# # Load the model and tokenizer
# model_id = "stabilityai/stable-diffusion-xl-base-1.0"
# pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
# pipe = pipe.to("cpu")
# def generate_image(prompt, negative_prompt, size):
# width, height = map(int, size.split('x'))
# generator = torch.Generator("cpu").manual_seed(42)
# image = pipe(prompt, height=height, width=width, negative_prompt=negative_prompt, generator=generator).images[0]
# return image
# with gr.Blocks() as demo:
# gr.Markdown("## Text to Image SDXL")
# with gr.Row():
# with gr.Column():
# prompt = gr.Textbox(label="Prompt")
# negative_prompt = gr.Textbox(label="Negative Prompt")
# size = gr.Dropdown(choices=["512x512", "768x768", "1024x1024"], value="1024x1024", label="Size")
# submit = gr.Button("Submit")
# with gr.Column():
# output = gr.Image(label="Output")
# submit.click(generate_image, inputs=[prompt, negative_prompt, size], outputs=output)
# demo.launch()
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