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change plot dimensions and update markdown text
Browse files
scripts/scripts_utils/plotly_interface.py
CHANGED
@@ -265,7 +265,7 @@ def prediction_plot(
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title_text="Road Scene",
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hovermode="closest",
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width=800,
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-
height=
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updatemenus=[
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dict(
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type="buttons",
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@@ -373,9 +373,10 @@ def main(load_from=None, cfg_path=None):
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Make predictions for the green agent with a risk-seeking bias towards the ego vehicle in blue.
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The risk level is a value between 0 and 1, where 0 is not risk-seeking and 1 is the most risk-seeking.
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For more information, see the paper [RAP: Risk-Aware Prediction for Robust Planning](https://arxiv.org/abs/2210.01368) published at CoRL 2022.
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""")
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initial_index = 27
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initial_n_samples = 10
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@@ -389,8 +390,8 @@ def main(load_from=None, cfg_path=None):
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label="Index",
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)
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risk_level = gr.Slider(minimum=0, maximum=1, step=0.01, label="Risk")
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n_samples = gr.Slider(minimum=1, maximum=20, step=1, value=initial_n_samples, label="
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button = gr.Button(label="
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# Removed the interactive plot because it was running on the first change and all changes made during computation were ignored
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# This caused the plot to be out of sync with the sliders
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title_text="Road Scene",
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hovermode="closest",
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width=800,
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height=600,
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updatemenus=[
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dict(
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type="buttons",
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Make predictions for the green agent with a risk-seeking bias towards the ego vehicle in blue.
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The risk level is a value between 0 and 1, where 0 is not risk-seeking and 1 is the most risk-seeking.
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+
Once the sliders are set, click the "Run" button to see the predictions.
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The play button will animate the prediction over time (it is slow especially with many samples).
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For more information, see the paper [RAP: Risk-Aware Prediction for Robust Planning](https://arxiv.org/abs/2210.01368) published at [CoRL 2022](https://corl2022.org/).
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""")
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initial_index = 27
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initial_n_samples = 10
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label="Index",
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)
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risk_level = gr.Slider(minimum=0, maximum=1, step=0.01, label="Risk")
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n_samples = gr.Slider(minimum=1, maximum=20, step=1, value=initial_n_samples, label="Number of prediction samples")
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button = gr.Button(label="Run")
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# Removed the interactive plot because it was running on the first change and all changes made during computation were ignored
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# This caused the plot to be out of sync with the sliders
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