Upload app.py

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()