app.py

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)