Spaces:
Paused
Paused
File size: 6,689 Bytes
69777eb 4d8b8e1 297a56e 4d8b8e1 297a56e 4d8b8e1 297a56e 4d8b8e1 cdc8845 69777eb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 |
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,
):
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()
#-or-
#git lfs install
#git clone https://huggingface.co/datasets/awacke1/SNOMED-CT-Code-Value-Semantic-Set.csv
# if you want to clone without large files – just their pointers
# prepend your git clone with the following env var:
#GIT_LFS_SKIP_SMUDGE=1
#---
#-or-
#git lfs install
#git clone https://huggingface.co/datasets/awacke1/eCQM-Code-Value-Semantic-Set.csv
# if you want to clone without large files – just their pointers
# prepend your git clone with the following env var:
#GIT_LFS_SKIP_SMUDGE=1
#---
#-or-
#git lfs install
#git clone https://huggingface.co/datasets/awacke1/LOINC-CodeSet-Value-Description.csv
# if you want to clone without large files – just their pointers
# prepend your git clone with the following env var:
#GIT_LFS_SKIP_SMUDGE=1 |