import gradio as gr import numpy as np # get_image(), get_video(), get_audio(), get_file(), get_model3d() return file paths to sample media included with Gradio from gradio.media import get_image, get_video, get_audio, get_file, get_model3d txt = "the quick brown fox" num = 10 img = get_image("cheetah1.jpg") vid = get_video("world.mp4") audio = get_audio("cantina.wav") csv = get_file("time.csv") model = get_model3d("Bunny.obj") dataframe = [[1, 2, 3, 4], [4, 5, 6, 7], [8, 9, 1, 2], [3, 4, 5, 6]] with gr.Blocks() as demo: gr.Markdown("# Dataset previews") a = gr.Audio(visible=False) gr.Dataset( components=[a], label="Audio", samples=[ [audio], [audio], [audio], [audio], [audio], [audio], ], ) c = gr.Checkbox(visible=False) gr.Dataset( label="Checkbox", components=[c], samples=[[True], [True], [False], [True], [False], [False]], ) c_2 = gr.CheckboxGroup(visible=False, choices=['a', 'b', 'c']) gr.Dataset( label="CheckboxGroup", components=[c_2], samples=[ [["a"]], [["a", "b"]], [["a", "b", "c"]], [["b"]], [["c"]], [["a", "c"]], ], ) c_3 = gr.ColorPicker(visible=False) gr.Dataset( label="ColorPicker", components=[c_3], samples=[ ["#FFFFFF"], ["#000000"], ["#FFFFFF"], ["#000000"], ["#FFFFFF"], ["#000000"], ], ) d = gr.DataFrame(visible=False) gr.Dataset( components=[d], label="Dataframe", samples=[ [np.zeros((3, 3)).tolist()], [np.ones((2, 2)).tolist()], [np.random.randint(0, 10, (3, 10)).tolist()], [np.random.randint(0, 10, (10, 3)).tolist()], [np.random.randint(0, 10, (10, 10)).tolist()], ], ) d_2 = gr.Dropdown(visible=False, choices=["one", "two", "three"]) gr.Dataset( components=[d_2], label="Dropdown", samples=[["one"], ["two"], ["three"], ["one"], ["two"], ["three"]], ) f = gr.File(visible=False) gr.Dataset( components=[f], label="File", samples=[ [csv], [csv], [csv], [csv], [csv], [csv], ], ) h = gr.HTML(visible=False) gr.Dataset( components=[h], label="HTML", samples=[ ["