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Update app.py
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app.py
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@@ -26,6 +26,7 @@ df = gr.Dataframe(
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datatype=["str", "str", "str", "str"],
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row_count=1,
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col_count=(4, "fixed"),
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)
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examples = [['example_data/audio/20170701_213954-MYOMYS-LR_0_0.5.wav', 0.3],
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@@ -90,16 +91,18 @@ def generate_results_image(audio_file, anns):
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descr_txt = "Demo of BatDetect2 deep learning-based bat echolocation call detection. " \
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"<br>This model is only trained on bat species from the UK. If the input " \
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"file is longer than 2 seconds, only the first 2 seconds will be processed." \
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"<br>
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gr.Interface(
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fn = make_prediction,
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inputs = [gr.Audio(source="upload", type="filepath", optional=True),
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gr.Dropdown([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])],
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outputs = [df, "
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theme = "huggingface",
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title = "BatDetect2 Demo",
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description = descr_txt,
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examples = examples,
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allow_flagging = 'never',
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).launch()
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datatype=["str", "str", "str", "str"],
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row_count=1,
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col_count=(4, "fixed"),
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label='Predictions'
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)
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examples = [['example_data/audio/20170701_213954-MYOMYS-LR_0_0.5.wav', 0.3],
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descr_txt = "Demo of BatDetect2 deep learning-based bat echolocation call detection. " \
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"<br>This model is only trained on bat species from the UK. If the input " \
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"file is longer than 2 seconds, only the first 2 seconds will be processed." \
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"<br>Check out the paper [here](https://www.biorxiv.org/content/10.1101/2022.12.14.520490v1)."
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gr.Interface(
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fn = make_prediction,
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inputs = [gr.Audio(source="upload", type="filepath", optional=True),
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gr.Dropdown([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])],
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outputs = [df, gr.Image(label="Visualisation")],
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theme = "huggingface",
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title = "BatDetect2 Demo",
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description = descr_txt,
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examples = examples,
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allow_flagging = 'never',
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).launch()
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