Logan Zoellner
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from asyncio import constants
import gradio as gr
import requests
import os
import re
import random
from words import *
from base64 import b64decode
from PIL import Image
import io
import numpy as np
def desc_to_image(desc):
print("*****Inside desc_to_image")
desc = " ".join(desc.split('\n'))
desc = desc + ", character art, concept art, artstation"
steps, width, height, images, diversity = '50','256','256','1',15
iface = gr.Interface.load("spaces/multimodalart/latentdiffusion")
print("about to die",iface,dir(iface))
prompt = re.sub(r'[^a-zA-Z0-9 ,.]', '', desc)
print("about to die",prompt)
img=iface(desc, steps, width, height, images, diversity)[0]
return img
def upscale_img(img):
iface = gr.Interface.load("spaces/akhaliq/Real-ESRGAN")
model='base'
uimg=iface(img,models)
return uimg
demo = gr.Blocks()
with demo:
gr.Markdown("<h1><center>NPC Generator</center></h1>")
gr.Markdown(
"<div>Run <a href='https://huggingface.co/spaces/multimodalart/latentdiffusion'>Latent Diffusion</a> first to generate an image</div>"
"<div>Then upscale with <a href='https://huggingface.co/spaces/akhaliq/Real-ESRGAN/blob/main/app.py'>ESRGAN</a></div>"
)
with gr.Row():
b0 = gr.Button("generate")
b1 = gr.Button("upscale")
with gr.Row():
desc = gr.Textbox(label="description",placeholder="an impressionist painting of a white vase")
with gr.Row():
intermediate_image = gr.Image(label="portrait",type="filepath", shape=(256,256))
output_image = gr.Image(label="portrait",type="filepath", shape=(256,256))
b0.click(desc_to_image,inputs=[desc],outputs=[intermediate_image])
b1.click(upscale_img, inputs=[ intermediate_image], outputs=output_image)
#examples=examples
demo.launch(enable_queue=True, debug=True)