app.py

import time
import gradio as gr
import os

import numpy as np
from PIL import Image
import math
from collections import defaultdict
import os
from huggingface_hub import HfApi, hf_hub_download


HUB_TOKEN = os.getenv("HUB_TOKEN")
REPO_ID = "simenv-explorer/shapenetcore-glb"

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 ".glb" 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):
    # wget the glb file from the datasets repo
    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",
        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)


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_model_list, inputs=inp, outputs=out1)
    inp.change(fn=update, inputs=out1, outputs=out2)
    out1.change(fn=update, inputs=out1, outputs=out2)


demo.launch()