ZENpanorama / app.py
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import spaces
import gradio as gr
from gradio_pannellum import Pannellum
import torch
from huggingface_hub import snapshot_download
from txt2panoimg import Text2360PanoramaImagePipeline
from PIL import Image
# Download the model
model_path = snapshot_download("archerfmy0831/sd-t2i-360panoimage")
# Initialize pipelines
txt2panoimg = Text2360PanoramaImagePipeline(model_path, torch_dtype=torch.float16)
@spaces.GPU(duration=200)
def text_to_pano(prompt, upscale):
input_data = {'prompt': prompt, 'upscale': upscale, 'refinement': False}
output = txt2panoimg(input_data)
return output, output
title = """<h1 align="center">SD-T2I-360PanoImage</h1>
<p align="center">360° Panorama Image Generation</p>
<p><center>
<a href="https://github.com/ArcherFMY/SD-T2I-360PanoImage/" target="_blank">[Github]</a>
<a href="https://huggingface.co/archerfmy0831/sd-t2i-360panoimage" target="_blank">[Models]</a>
</center></p>
"""
with gr.Blocks(theme='bethecloud/storj_theme') as demo:
gr.HTML(title)
with gr.Row():
with gr.Column():
t2p_input = gr.Textbox(label="Enter your prompt", lines=3)
t2p_upscale = gr.Checkbox(label="Upscale (takes about 60 seconds 6144x3072 resolution)")
t2p_generate = gr.Button("Generate Panorama")
with gr.Column(variant="default"):
t2p_output = Pannellum(show_label=False, interactive=True)
with gr.Row():
t2p_image_output = gr.Image(label="Generated Image")
# Add a hidden component to store a random value
update_trigger = gr.State(value=0)
def generate_with_update(prompt, upscale, trigger):
output, image = text_to_pano(prompt, upscale)
return output, image, trigger + 1
t2p_generate.click(
generate_with_update,
inputs=[t2p_input, t2p_upscale, update_trigger],
outputs=[t2p_output, t2p_image_output, update_trigger]
)
demo.launch()