Upload app.py

app.py

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+import gradio as gr
+import os
+import pyBigWig
+from func_gradio import predict_func,make_plots
+
+inputs = [
+    gr.Dropdown([str(i) for i in range(1, 23)], label='Chromosome', default='1'),
+    gr.Dropdown(['Micro-C', 'Hi-C (ChIA-PET)']
+                , label='Chromatin contact map', info='One type of contact map is predicted for each time'),
+    gr.Number(label='Region of interest (500kb for Micro-C and 1Mb for Hi-C)', info='From'),
+    gr.Number(info='To', show_label=False),
+    gr.File(label='Processed ATAC-seq file (in .pickle format)'),
+
+]
+
+outputs = [
+    gr.Files(label='Download the results'),
+]
+
+app1 = gr.Interface(
+    fn=predict_func,
+    inputs=inputs,
+    outputs=outputs,
+    title='A computational tool to use ATAC-seq to impute epigenome, transcriptome, and high-resolution chromatin contact maps',
+    description= '<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/drjieliu/EPCOT?duplicate=true">'
+                 '<img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>'
+                '\n<a href="https://github.com/zzh24zzh/EPCOT_gradio" class="built-with svelte-1lyswbr" target="_blank" '
+                'style="font-size: 15px; font-color: black; font-weight:bold" rel="noreferrer">View Documentation </a>',
+    # examples=[["11","Micro-C","10500000","11000000","./examples/atac_GM12878.pickle"],
+    #     ["11","Hi-C (ChIA-PET)","7750000","8750000","./examples/atac_GM12878.pickle"]]
+)
+
+
+with open(os.path.abspath('data/epigenomes.txt'), 'r') as f:
+    epis=f.read().splitlines()
+inputs1 = [
+    gr.File(label="Prediction file (in .npz format))"),
+    gr.Markdown(value='### Visualization options'),
+    gr.Dropdown(epis,label='Epigenome features',multiselect=True,max_choices=10,value=['CTCF','H3K4me3']),
+    gr.Radio(choices=['Signal p-values (archsinh)','Binding probability'], label='Type of epigenomic feature data'
+             , value='Signal p-values (archsinh)'),
+    gr.Slider(maximum=16,label='Range of values displayed on the plots',info="Choose between 0 and 16 (contact maps)",value=4),
+    gr.Slider(minimum=2,maximum=12,info="Choose between 2 and 12 (epigenomic feature signals)",value=4,show_label=False),
+    gr.Slider(minimum=2,maximum=12,info="Choose between 2 and 12 (CAGE-seq)",value=8,show_label=False),
+]
+outputs1 = gr.Plot(label='Plots')
+app2 = gr.Interface(
+    fn=make_plots,
+    inputs=inputs1,
+    outputs=outputs1,
+    live=True
+)
+
+demo = gr.TabbedInterface([app1, app2], ["Run model", "Visualize prediction results"],
+                          theme=gr.themes.Soft())
+
+demo.launch(debug=True)