import time import gradio as gr import os import numpy as np from PIL import Image import math import os from huggingface_hub import HfApi def greet(name): return "Hello " + name + "!" def get_dataset_classes(): return { "airplane": [ "airplane/0.glb", "airplane/1.glb", "airplane/2.glb", "airplane/3.glb", "airplane/4.glb", "airplane/5.glb", "airplane/6.glb", "airplane/7.glb", ], "bench": [ "bench/0.glb", "bench/1.glb", "bench/10.glb", "bench/11.glb", "bench/12.glb", "bench/13.glb", "bench/14.glb", "bench/2.glb", "bench/3.glb", "bench/4.glb", "bench/5.glb", "bench/6.glb", "bench/7.glb", "bench/8.glb", "bench/9.glb", ], "camera": [ "camera/0.glb", "camera/1.glb", "camera/2.glb", "camera/3.glb", "camera/4.glb", "camera/5.glb", "camera/6.glb", "camera/7.glb", ], "dishwasher": [ "dishwasher/0.glb", "dishwasher/1.glb", "dishwasher/10.glb", "dishwasher/11.glb", "dishwasher/2.glb", "dishwasher/3.glb", "dishwasher/4.glb", "dishwasher/5.glb", "dishwasher/6.glb", "dishwasher/7.glb", "dishwasher/8.glb", "dishwasher/9.glb", ], "jar": [ "jar/0.glb", "jar/1.glb", "jar/2.glb", "jar/3.glb", "jar/4.glb", "jar/5.glb", "jar/6.glb", "jar/7.glb", "jar/8.glb", ], "motorcycle": [ "motorcycle/0.glb", "motorcycle/1.glb", "motorcycle/10.glb", "motorcycle/2.glb", "motorcycle/3.glb", "motorcycle/4.glb", "motorcycle/5.glb", "motorcycle/6.glb", "motorcycle/7.glb", "motorcycle/8.glb", "motorcycle/9.glb", ], "printer": [ "printer/0.glb", "printer/1.glb", "printer/10.glb", "printer/11.glb", "printer/2.glb", "printer/3.glb", "printer/4.glb", "printer/5.glb", "printer/6.glb", "printer/7.glb", "printer/8.glb", "printer/9.glb", ], "sofa": [ "sofa/0.glb", "sofa/1.glb", "sofa/10.glb", "sofa/11.glb", "sofa/12.glb", "sofa/2.glb", "sofa/3.glb", "sofa/4.glb", "sofa/5.glb", "sofa/6.glb", "sofa/7.glb", "sofa/8.glb", "sofa/9.glb", ], "washer": [ "washer/0.glb", "washer/1.glb", "washer/10.glb", "washer/11.glb", "washer/2.glb", "washer/3.glb", "washer/4.glb", "washer/5.glb", "washer/6.glb", "washer/7.glb", "washer/8.glb", "washer/9.glb", ], } dataset_dict = get_dataset_classes() dataset_classes = list(dataset_dict.keys()) default_models = dataset_dict[dataset_classes[0]] def load_mesh(mesh_file_name): return mesh_file_name, mesh_file_name def update(model_name): # wget the glb file from the datasets repo print(model_name) return f"{model_name}/0.glb" def update_model_list(choice_class): print(f"inp1 changed {choice_class}") return {"choices":dataset_dict[choice_class]} with gr.Blocks() as demo: with gr.Row(): with gr.Column(): inp = gr.Dropdown(choices=dataset_classes, interactive=True, label="3D Model Class", value=dataset_classes[0]) out1 = gr.Dropdown(choices=default_models, interactive=True, label="3D Model", value=default_models[0]) out2 = gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0], label="3D Model") inp.change(fn=update, inputs=inp, outputs=out2) # with gr.Row(): # btn = gr.Button("Load model") # btn.click(fn=update, inputs=inp, outputs=out2) # demo = gr.Interface( # fn=load_mesh, # inputs=gr.Model3D(), # outputs=[ # gr.Model3D( # clear_color=[0.0, 0.0, 0.0, 0.0], label="3D Model"), # gr.File(label="Download 3D Model") # ], # examples=[ # ], demo.launch()