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| from pulsar_clip import PulsarCLIP, CONFIG_SPEC | |
| from datetime import datetime | |
| import gradio as gr | |
| import utils | |
| def generate(*args): | |
| pc = PulsarCLIP(dict([(k, t(v) if not isinstance(t, (tuple, list)) | |
| else (type(t[0])(v) if isinstance(t, tuple) else v)) | |
| for v, (k, v0, t) in zip(args, | |
| (y for _, x in CONFIG_SPEC for y in x))])) | |
| frames = [] | |
| for image in pc.generate(): | |
| frames.append(image) | |
| from tqdm.auto import tqdm | |
| from subprocess import Popen, PIPE | |
| fps = 30 | |
| filename = datetime.strftime(datetime.now(), "%Y-%m-%d-%H-%M-%S") | |
| video_path = f"{filename}.mp4" | |
| if frames: | |
| p = Popen((f"ffmpeg -y -f image2pipe -vcodec png -r {fps} -i - -vcodec libx264 -r {fps} " | |
| f"-pix_fmt yuv420p -crf 17 -preset fast ").split() + [str(video_path)], stdin=PIPE) | |
| for im in tqdm(frames): | |
| im.save(p.stdin, "PNG") | |
| p.stdin.close() | |
| p.wait() | |
| model_path = f"{filename}.obj" | |
| pc.save_obj(model_path) | |
| # model_path = None # TODO | |
| return [video_path, model_path, model_path] | |
| def main(): | |
| with gr.Blocks() as ui: | |
| gr.Markdown("# Pulsar+CLIP") | |
| gr.Markdown("<a target='_blank' href='https://colab.research.google.com/drive/1IvV3HGoNjRoyAKIX-aqSWa-t70PW3nPs'> <img src='https://colab.research.google.com/assets/colab-badge.svg' alt='Open In Colab'/> </a> [](https://arxiv.org/abs/2004.07484)") | |
| gr.Markdown("Generate 3D point clouds from text!") | |
| with gr.Group(): | |
| gr.Markdown("## Settings") | |
| inputs = [] | |
| defaults = [] | |
| with gr.Tabs(): | |
| for name, section in CONFIG_SPEC: | |
| with gr.TabItem(name): | |
| for k, v0, t in section: | |
| if t in (float, int): | |
| element = gr.Number(label=k, value=v0) | |
| elif t == str: | |
| element = gr.Textbox(label=k, value=v0) | |
| elif t == bool: | |
| element = gr.Checkbox(label=k, value=v0) | |
| elif isinstance(t, tuple): | |
| element = gr.Slider(*t, label=k, value=v0) | |
| elif isinstance(t, list): | |
| element = gr.Dropdown(label=k, value=v0, choices=t) | |
| else: | |
| raise TypeError(f"Input format {t} should be one of str, int, bool, tuple, list") | |
| element = 1/0 | |
| inputs.append(element) | |
| defaults.append(v0) | |
| button = gr.Button("Run") | |
| gr.Markdown("## Result") | |
| with gr.Row(): | |
| with gr.Column(): | |
| video_result = gr.Video() | |
| with gr.Column(): | |
| model_demo = gr.Model3D() | |
| model_file = gr.File() | |
| button.click(fn=generate, inputs=inputs, outputs=[video_result, model_demo, model_file]) | |
| gr.Markdown("## Examples") | |
| gr.Examples(fn=generate, inputs=inputs, outputs=[video_result, model_demo, model_file], | |
| examples=[defaults], cache_examples=True, examples_per_page=1) | |
| return ui | |
| ui = main() | |
| ui.configure_queue(concurrency_count=5).launch() | |
| demo = ui | |