vshulev commited on
Commit
8260f31
·
1 Parent(s): c75d1fb

Change layout to 2 columns

Browse files
Files changed (1) hide show
  1. app.py +31 -40
app.py CHANGED
@@ -154,6 +154,7 @@ def predict_genus(method: str, dna_sequence: str, latitude: str, longitude: str)
154
  ax.set_title("Genus Prediction")
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  ax.set_xlabel("Genus")
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  ax.set_ylabel("Probability")
 
157
  ax.set_xticklabels(top_k.index.astype(str), rotation=90)
158
  fig.subplots_adjust(bottom=0.3)
159
  fig.canvas.draw()
@@ -231,27 +232,21 @@ with gr.Blocks() as demo:
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  that we precomputed and stored in a Pinecone index. Thie method
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  DOES NOT examine ecological layer data.
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  """)
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- # gr.Interface(
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- # fn=predict_genus,
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- # inputs=[
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- # gr.Dropdown(choices=["cosine", "fine_tuned_model"], value="fine_tuned_model"),
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- # inp_dna,
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- # inp_lat,
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- # inp_lng,
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- # ],
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- # outputs=["image"],
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- # allow_flagging="never",
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- # )
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-
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- method_dropdown = gr.Dropdown(choices=["cosine", "fine_tuned_model"], value="fine_tuned_model")
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- predict_button = gr.Button("Predict Genus")
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- genus_output = gr.Image()
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-
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- predict_button.click(
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- fn=predict_genus,
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- inputs=[method_dropdown, inp_dna, inp_lat, inp_lng],
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- outputs=genus_output
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- )
255
 
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  with gr.Tab("DNA Embedding Space Visualizer"):
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  gr.Markdown("""
@@ -262,24 +257,20 @@ with gr.Blocks() as demo:
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  learning to cluster similar DNA sequences together.
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  """)
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- # gr.Interface(
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- # fn=cluster_dna,
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- # inputs=[
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- # gr.Slider(minimum=1, maximum=10, step=1, value=5,
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- # label="Number of top genera to visualize")
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- # ],
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- # outputs=["image"],
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- # allow_flagging="never",
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- # )
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-
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- top_k_slider = gr.Slider(minimum=1, maximum=10, step=1, value=5, label="Number of top genera to visualize")
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- visualize_button = gr.Button("Visualize Embedding Space")
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- visualize_output = gr.Image()
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-
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- visualize_button.click(
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- fn=cluster_dna,
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- inputs=top_k_slider,
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- outputs=visualize_output
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- )
284
 
285
  demo.launch()
 
154
  ax.set_title("Genus Prediction")
155
  ax.set_xlabel("Genus")
156
  ax.set_ylabel("Probability")
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+ ax.set_xticks(range(len(top_k)))
158
  ax.set_xticklabels(top_k.index.astype(str), rotation=90)
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  fig.subplots_adjust(bottom=0.3)
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  fig.canvas.draw()
 
232
  that we precomputed and stored in a Pinecone index. Thie method
233
  DOES NOT examine ecological layer data.
234
  """)
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+
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+ with gr.Row():
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+ with gr.Column():
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+ method_dropdown = gr.Dropdown(
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+ choices=["cosine", "fine_tuned_model"], value="fine_tuned_model",
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+ )
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+ predict_button = gr.Button("Predict Genus")
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+ with gr.Column():
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+ genus_output = gr.Image()
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+
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+ predict_button.click(
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+ fn=predict_genus,
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+ inputs=[method_dropdown, inp_dna, inp_lat, inp_lng],
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+ outputs=genus_output
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+ )
 
 
 
 
 
 
250
 
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  with gr.Tab("DNA Embedding Space Visualizer"):
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  gr.Markdown("""
 
257
  learning to cluster similar DNA sequences together.
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  """)
259
 
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+ with gr.Row():
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+ with gr.Column():
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+ top_k_slider = gr.Slider(
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+ minimum=1, maximum=10, step=1, value=5,
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+ label="Number of top genera to visualize",
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+ )
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+ visualize_button = gr.Button("Visualize Embedding Space")
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+ with gr.Column():
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+ visualize_output = gr.Image()
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+
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+ visualize_button.click(
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+ fn=cluster_dna,
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+ inputs=top_k_slider,
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+ outputs=visualize_output
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+ )
 
 
 
 
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  demo.launch()