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# %%
import pandas as pd
import gradio as gr
df = pd.read_csv("./data.csv")
def md_builder(model, dataset, displayed_metrics):
row = df[df["friendly_name"] == model]
str = (
f"## <span style='font-size: 16px;'>🚧 Performance and safety of <code style='font-weight: 400'>{model}</code></span>\n"
f"On dataset `{dataset}`\n"
)
if "Performance" in displayed_metrics:
str += f"\nPerformance: `{row['performance'].values[0]}`"
if "Accuracy" in displayed_metrics:
str += f"\nAccuracy: `{row['accuracy'].values[0]}`"
if "Precision" in displayed_metrics:
str += f"\nPrecision: `{row['precision_weighted'].values[0]}`"
if "Recall" in displayed_metrics:
str += f"\nRecall: `{row['recall_weighted'].values[0]}`"
if "Robustness" in displayed_metrics:
str += f"\nRobustness: `{100-row['robustness'].values[0]}`"
if "Fairness" in displayed_metrics:
str += f"\nFairness: `{0}`"
str += "\n<div style='text-align: right'>⛶ Expand safety card</div>"
return str
iface = gr.Interface(
md_builder,
[
gr.Dropdown(
list(df["friendly_name"]),
label="Model",
value="ViT",
info="Select a model to use for testing.",
),
gr.Dropdown(
["marmal88/skin_cancer"],
value="marmal88/skin_cancer",
label="Dataset",
info="Select the sampling dataset to use for testing.",
),
gr.CheckboxGroup(["Performance", "Accuracy", "Precision", "Recall", "Robustness", "Fairness"], value=["Accuracy", "Robustness"], label="Metrics", info="Select displayed metrics."),
# gr.Radio(["park", "zoo", "road"], label="Location", info="Where did they go?"),
# gr.Dropdown(
# ["ran", "swam", "ate", "slept"], value=["swam", "slept"], multiselect=True, label="Activity", info="Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed auctor, nisl eget ultricies aliquam, nunc nisl aliquet nunc, eget aliquam nisl nunc vel nisl."
# ),
# gr.Checkbox(label="Morning", info="Did they do it in the morning?"),
],
"markdown",
examples=[
["ViT", "marmal88/skin_cancer", ["Accuracy", "Robustness"]],
],
)
iface.launch()
# %%
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