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from asyncio import constants
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import gradio as gr
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import requests
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import os
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from base64 import b64decode
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from PIL import Image
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import io
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import numpy as np
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def generate_image(seed,psi):
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iface = gr.Interface.load("spaces/hysts/StyleGAN-Human")
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img=iface.fns[0].fn(seed,psi)
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header, encoded = img.split(",", 1)
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data = b64decode(encoded)
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image = Image.open(io.BytesIO(data))
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image_np = np.array(image)
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return image_np
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def generate_model(img):
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print("about to die")
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iface = gr.Interface.load("spaces/radames/PIFu-Clothed-Human-Digitization")
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print("calling interface")
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model,file=iface(img)
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print("got result",result)
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return model,file
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demo = gr.Blocks()
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with demo:
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gr.Markdown("<h1><center>StyleGan-Human + PIFu </center></h1>")
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gr.Markdown(
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"create a person and then generate a model from that person's image"
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)
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with gr.Row():
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b0 = gr.Button("generate image")
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b1 = gr.Button("generate model")
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with gr.Row():
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seed=gr.Number(default=0, label='Seed')
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psi=gr.Slider(0, 2, step=0.05, default=0.7, label='Truncation psi')
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output_image = gr.outputs.Image(type="filepath", label='Output')
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model = gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0], label="3D Model")
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file= gr.File(label="Download 3D Model")
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b0.click(generate_image,inputs=[seed,psi],outputs=output_image)
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b1.click(generate_model, inputs=output_image, outputs=[model,file])
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demo.launch(enable_queue=True, debug=True) |
