import gradio as gr import plotly.graph_objects as go import torch from tqdm.auto import tqdm from model import Model from settings import CACHE_EXAMPLES, MAX_SEED from utils import randomize_seed_fn def inference(prompt): model = Model() seed: int = 0 guidance_scale: float = 15.0 num_inference_steps: int = 64 model.run_text(prompt, seed, guidance_scale, num_inference_steps) return prompt demo = gr.Interface( fn=inference, inputs="text", outputs="text", examples=[ ["a red motorcycle"], ["a RED pumpkin"], ["a yellow rubber duck"] ], title="Point-E demo: text to 3D", description="""Generated 3D Point Clouds with [Point-E](https://github.com/openai/point-e/tree/main). This demo uses a small, worse quality text-to-3D model to produce 3D point clouds directly from text descriptions. Check out the [notebook](https://github.com/openai/point-e/blob/main/point_e/examples/text2pointcloud.ipynb). """ ) demo.launch(debug=True)