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## Created by ruslanmv.com
## Happy coding!
import gradio as gr
import torch
#import modin.pandas as pd
import numpy as np
from diffusers import DiffusionPipeline
from transformers import pipeline
pipe = pipeline('text-generation', model='daspartho/prompt-extend')
def extend_prompt(prompt):
return pipe(prompt+',', num_return_sequences=1)[0]["generated_text"]
def text_it(inputs):
return extend_prompt(inputs)
def load_pipeline(use_cuda):
device = "cuda" if use_cuda and torch.cuda.is_available() else "cpu"
if device == "cuda":
torch.cuda.max_memory_allocated(device=device)
torch.cuda.empty_cache()
pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
pipe.enable_xformers_memory_efficient_attention()
pipe = pipe.to(device)
torch.cuda.empty_cache()
else:
pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
pipe = pipe.to(device)
return pipe
def genie(prompt="sexy woman", use_details=False,steps=2, seed=398231747038484200, use_cuda=False):
pipe = load_pipeline(use_cuda)
generator = np.random.seed(0) if seed == 0 else torch.manual_seed(seed)
if use_details:
extended_prompt = extend_prompt(prompt)
else:
extended_prompt=prompt
int_image = pipe(prompt=extended_prompt, generator=generator, num_inference_steps=steps, guidance_scale=0.0).images[0]
return int_image, extended_prompt
with gr.Blocks() as myface:
gr.HTML()
with gr.Row():
with gr.Row():
input_text = gr.Textbox(label='Prompt Text.', lines=1)
details_checkbox = gr.Checkbox(label="details", info="Generate Details?")
steps_slider = gr.Slider(1, maximum=5, value=2, step=1, label='Number of Iterations')
seed_slider = gr.Slider(minimum=0, step=1, maximum=999999999999999999, randomize=True)
cuda_checkbox = gr.Checkbox(label="cuda", info="Do you have cuda?")
with gr.Row():
generate_button = gr.Button("Generate")
with gr.Row():
output_image = gr.Image("./imagen.png")
output_text = gr.Textbox(label="Generated Text", lines=2)
generate_button.click(genie, inputs=[input_text,details_checkbox, steps_slider, seed_slider, cuda_checkbox], outputs=[output_image, output_text], concurrency_limit=10)
# Define the example
example = [["sexy woman", True ,2, 398231747038484200, ""],
['''sexy woman, in a black bikini, white bra, highly detailed, d & d, fantasy, highly detailed, digital painting, trending on artstation, concept art, sharp focus, illustration, art by artgerm and greg rutkowski and fuji choko and viktoria gavrilenko''', False ,2, 304332410412655740, ""],
['''sexy woman, D&D, fantasy, portrait, highly detailed, headshot, digital painting, trending on artstation, concept art, sharp focus, illustration, art by artgerm and greg rutkowski and magali villeneuve and wlop, ilya kuvshinov, octane render, 8 ''', False ,2, 747356768820251800, ""],
[''' sexy woman, worksafe, light blonde long hair, fully clothed, brown eyes, sitting on a chair, sitting by a reflective pool, in the style of ilya kuvshinov, very dark, cinematic dramatic atmosphere, artstation, detailed facial ''', False ,2, 398231747038484200, ""],
['''sexy woman, medium shot, candid, red hair, 4 k, high definition, realistic, natural, highly detailed, photo realistic smooth, sharp, unreal engine 5, cinema4d, Blender, render photo-realistic, v-ray ''', False ,2, 398231747038484200, ""],
]
with gr.Interface(
fn=genie,
inputs=[input_text,details_checkbox, steps_slider, seed_slider, cuda_checkbox],
outputs=[output_image, output_text],
title="Stable Diffusion Turbo with GPT",
description="Type your text and lets create an image, check the box details if you want a creative picture",
examples=example,
) as iface:
iface.launch(inline=True, show_api=False, max_threads=200)
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