import gradio as gr from collections import defaultdict import os from huggingface_hub import HfApi, hf_hub_download HUB_TOKEN = os.getenv("HUB_TOKEN") REPO_ID = "ShapeNet/shapenetcore-gltf" def get_dataset_classes(): hf_api = HfApi() info = hf_api.dataset_info(repo_id=REPO_ID, token=HUB_TOKEN) dataset_classes = defaultdict(list) for file in info.siblings: if ".gltf" in file.rfilename: class_name = file.rfilename.split("/")[0] dataset_classes[class_name].append(file.rfilename) print(dataset_classes) return dataset_classes 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(asset_name): split_model_path = asset_name.split("/") asset_path = hf_hub_download( repo_id=REPO_ID, filename=split_model_path[1], subfolder=split_model_path[0], repo_type="dataset", use_auth_token=HUB_TOKEN, ) print(asset_name) return asset_path def update_models(class_name): model_choices = dataset_dict[class_name] return gr.Dropdown.update(choices=model_choices) def update_model_list(class_name): model_choices = dataset_dict[class_name] return gr.Dropdown.update(choices=model_choices, value=model_choices[0]) def update_asset_path(model_name): return REPO_ID + "/" + model_name 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]) out3 = gr.Textbox(value=REPO_ID + "/" + out1.value, label="Asset Path") out2 = gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0], label="3D Model") # Update second dropdown inp.change(fn=update_model_list, inputs=inp, outputs=out1) # Update 3D model view inp.change(fn=update, inputs=out1, outputs=out2) out1.change(fn=update, inputs=out1, outputs=out2) # Update path to asset inp.change(fn=update_asset_path, inputs=out1, outputs=out3) out1.change(fn=update_asset_path, inputs=out1, outputs=out3) demo.launch()