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from asyncio import constants | |
import gradio as gr | |
import requests | |
import os | |
from base64 import b64decode | |
from PIL import Image | |
import io | |
def generate_image(text): | |
#dalle = gr.Interface.load("spaces/kuprel/min-dalle") | |
dalle = gr.Interface.load("spaces/Axolotlily/DalleMini") | |
print("calling interface",text) | |
img=dalle(text) | |
#img=dalle.fns[0].fn(seed,psi) | |
#header, encoded = img.split(",", 1) | |
#data = b64decode(encoded) | |
#image = Image.open(io.BytesIO(data)) | |
return img | |
#gfpgan=gr.Interface.load("spaces/akhaliq/GFPGAN") | |
#img2=dalle(image) | |
#return img2 | |
demo = gr.Blocks() | |
with demo: | |
gr.Markdown("<h1><center>StyleGan-Human + PIFu </center></h1>") | |
gr.Markdown( | |
"create an image with min-dalle then fix faces with grpgan" | |
) | |
with gr.Row(): | |
b0 = gr.Button("generate image") | |
with gr.Row(): | |
text=gr.Text(default="three pigs in a trenchcoat", label='Seed') | |
#outputImage = gr.Image(label="portrait",type="filepath", shape=(256,256)) | |
output_image = gr.outputs.Image(type="filepath", label='Output') | |
b0.click(generate_image,inputs=[text],outputs=[output_image]) | |
demo.launch(enable_queue=True, debug=True) |