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from datasets import load_dataset
#LOINC
datasetLOINC = load_dataset("awacke1/LOINC-CodeSet-Value-Description.csv")
#SNOMED:
datasetSNOMED = load_dataset("awacke1/SNOMED-CT-Code-Value-Semantic-Set.csv")
#eCQM:
dataseteCQM = load_dataset("awacke1/eCQM-Code-Value-Semantic-Set.csv")
print(datasetLOINC)
print(datasetSNOMED)
print(dataseteCQM)
import os
import json
import numpy as np
import gradio as gr
CHOICES = ["foo", "bar", "baz"]
JSONOBJ = """{"items":{"item":[{"id": "0001","type": null,"is_good": false,"ppu": 0.55,"batters":{"batter":[{ "id": "1001", "type": "Regular" },{ "id": "1002", "type": "Chocolate" },{ "id": "1003", "type": "Blueberry" },{ "id": "1004", "type": "Devil's Food" }]},"topping":[{ "id": "5001", "type": "None" },{ "id": "5002", "type": "Glazed" },{ "id": "5005", "type": "Sugar" },{ "id": "5007", "type": "Powdered Sugar" },{ "id": "5006", "type": "Chocolate with Sprinkles" },{ "id": "5003", "type": "Chocolate" },{ "id": "5004", "type": "Maple" }]}]}}"""
#def fn( text1, text2, num, slider1, slider2, single_checkbox, checkboxes, radio, dropdown, im1, im2, im3, im4,
# video, audio1, audio2, file, df1, df2,):
def fn( text1, text2, im4, file, df1, df2,):
return (
(text1 if single_checkbox else text2) + ", selected:" + ", ".join(checkboxes), # Text
{"positive": num / (num + slider1 + slider2),"negative": slider1 / (num + slider1 + slider2),"neutral": slider2 / (num + slider1 + slider2),}, # Label
(audio1[0], np.flipud(audio1[1])) if audio1 is not None else os.path.join(os.path.dirname(__file__), "files/cantina.wav"), # Audio
np.flipud(im1) if im1 is not None else os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"), # Image
video if video is not None else os.path.join(os.path.dirname(__file__), "files/world.mp4"), # Video
[
("The", "art"),
("quick brown", "adj"),
("fox", "nn"),
("jumped", "vrb"),
("testing testing testing", None),
("over", "prp"),
("the", "art"),
("testing", None),
("lazy", "adj"),
("dogs", "nn"),
(".", "punc"),
] + [(f"test {x}", f"test {x}") for x in range(10)], # HighlightedText
[
("The testing testing testing", None),
("over", 0.6),
("the", 0.2),
("testing", None),
("lazy", -0.1),
("dogs", 0.4),
(".", 0),
] + [(f"test", x / 10) for x in range(-10, 10)], # HighlightedText
json.loads(JSONOBJ), # JSON
"<button style='background-color: red'>Click Me: " + radio + "</button>", # HTML
os.path.join(os.path.dirname(__file__), "files/titanic.csv"),
df1, # Dataframe
np.random.randint(0, 10, (4, 4)), # Dataframe
df2, # Timeseries
)
demo = gr.Interface(
fn,
inputs=[
gr.Textbox(value="Lorem ipsum", label="Textbox"),
gr.Textbox(lines=3, placeholder="Type here..", label="Textbox 2"),
#gr.Number(label="Number", value=42),
#gr.Slider(10, 20, value=15, label="Slider: 10 - 20"),
#gr.Slider(maximum=20, step=0.04, label="Slider: step @ 0.04"),
#gr.Checkbox(label="Checkbox"),
#gr.CheckboxGroup(label="CheckboxGroup", choices=CHOICES, value=CHOICES[0:2]),
#gr.Radio(label="Radio", choices=CHOICES, value=CHOICES[2]),
#gr.Dropdown(label="Dropdown", choices=CHOICES),
#gr.Image(label="Image"),
#gr.Image(label="Image w/ Cropper", tool="select"),
#gr.Image(label="Sketchpad", source="canvas"),
gr.Image(label="Webcam", source="webcam"),
#gr.Video(label="Video"),
#gr.Audio(label="Audio"),
#gr.Audio(label="Microphone", source="microphone"),
gr.File(label="File"),
gr.Dataframe(label="Dataframe", headers=["Name", "Age", "Gender"]),
gr.Timeseries(x="time", y=["price", "value"], colors=["pink", "purple"]),
],
outputs=[
gr.Textbox(label="Textbox"),
gr.Label(label="Label"),
#gr.Audio(label="Audio"),
#gr.Image(label="Image"),
#gr.Video(label="Video"),
gr.HighlightedText(label="HighlightedText", color_map={"punc": "pink", "test 0": "blue"}),
gr.HighlightedText(label="HighlightedText", show_legend=True),
gr.JSON(label="JSON"),
#gr.HTML(label="HTML"),
gr.File(label="File"),
gr.Dataframe(label="Dataframe"),
gr.Dataframe(label="Numpy"),
gr.Timeseries(x="time", y=["price", "value"], label="Timeseries"),
],
examples=[
[
"the quick brown fox",
"jumps over the lazy dog",
#10,
#12,
#4,
#True,
#["foo", "baz"],
#"baz",
#"bar",
#os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"),
#os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"),
#os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"),
os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"),
#os.path.join(os.path.dirname(__file__), "files/world.mp4"),
#os.path.join(os.path.dirname(__file__), "files/cantina.wav"),
#os.path.join(os.path.dirname(__file__), "files/cantina.wav"),
os.path.join(os.path.dirname(__file__), "files/titanic.csv"),
[[1, 2, 3], [3, 4, 5]],
os.path.join(os.path.dirname(__file__), "files/time.csv"),
]
]
* 3,
theme="default",
title="Gradio AI UI UX",
cache_examples=False,
description="Try out all the components!",
article="Learn more about [Gradio](http://gradio.app)",
)
if __name__ == "__main__":
demo.launch() |