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Running
Running
updated app.py
Browse files
app.py
CHANGED
@@ -432,7 +432,7 @@ def plot_probabilities(probabilities):
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if len(probabilities) < 1:
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return None
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prob_df = pd.DataFrame({"labels": cell_types, "values": probabilities})
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prob_df.to_csv('Cell_types_predictions.csv', index=False)
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return prob_df
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def run_mapping():
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@@ -456,7 +456,7 @@ def run_registration(data_type, selected_idx):
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return "Registration complete!"
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def download_csv():
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return 'Cell_types_predictions.csv'
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def handle_data_type_change(dt):
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@@ -488,7 +488,7 @@ with gr.Blocks() as demo:
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slice_slider = gr.Slider(minimum=0, maximum=0, value=0, step=1, label="Slices", visible=False)
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with gr.Column(scale=1):
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gr.Markdown("### Step 3: Visualizing Allen Brain Cell Types Atlas")
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gallery = gr.Gallery(label="ABC Atlas", value = gallery_images,)
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gr.Markdown("**Step 4: Run cell type mapping**")
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with gr.Row():
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run_button = gr.Button("Run Mapping")
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@@ -498,7 +498,7 @@ with gr.Blocks() as demo:
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gr.Markdown("### Step 5: Quantitative results of the mapping model.")
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prob_plot = gr.BarPlot(prob_df, x="labels", y="values", title="Cell Type Probabilities", scroll_to_output=True, x_label_angle=-90, height=400)
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gr.Markdown("### Step 6: Download Results.")
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download_button = gr.DownloadButton(label="Download Results", value='Cell_types_predictions.csv')
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nifti_file.change(
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load_nifti_or_png,
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if len(probabilities) < 1:
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return None
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prob_df = pd.DataFrame({"labels": cell_types, "values": probabilities})
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prob_df.to_csv('./Cell_types_predictions.csv', index=False)
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return prob_df
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def run_mapping():
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return "Registration complete!"
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def download_csv():
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return './Cell_types_predictions.csv'
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def handle_data_type_change(dt):
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slice_slider = gr.Slider(minimum=0, maximum=0, value=0, step=1, label="Slices", visible=False)
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with gr.Column(scale=1):
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gr.Markdown("### Step 3: Visualizing Allen Brain Cell Types Atlas")
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gallery = gr.Gallery(label="ABC Atlas", value = gallery_images,columns = 5, height = 450)
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gr.Markdown("**Step 4: Run cell type mapping**")
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with gr.Row():
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run_button = gr.Button("Run Mapping")
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gr.Markdown("### Step 5: Quantitative results of the mapping model.")
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prob_plot = gr.BarPlot(prob_df, x="labels", y="values", title="Cell Type Probabilities", scroll_to_output=True, x_label_angle=-90, height=400)
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gr.Markdown("### Step 6: Download Results.")
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download_button = gr.DownloadButton(label="Download Results", value='./Cell_types_predictions.csv')
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nifti_file.change(
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load_nifti_or_png,
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