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import gradio as gr | |
import pandas as pd | |
import os | |
import pickle | |
def prediction(sequences): | |
sequences = sequences.strip() | |
sequences = [seq.strip() for seq in sequences.split('\n')] | |
sequences = pd.DataFrame({'Sequence':sequences}) | |
results = pd.DataFrame(model.predict_proba(sequences)) | |
results.columns = ["no-AFP score", "AFP score"] | |
activities = pd.DataFrame({'Antifungal':results['AFP score'] > .5}) | |
return pd.concat((sequences, activities, results), axis = 1) | |
model = pickle.load(open("AFP_Model.pkl", 'rb')) | |
with gr.Blocks() as demo: | |
demo.title = "AFPtransferPred" | |
inp = gr.Textbox(lines=5, max_lines=6, placeholder="Enter peptides sequences in raw format (one line per sequence)", label="") | |
with gr.Row(): | |
btn1 = gr.Button("Submit") | |
btn2 = gr.Button("Clear", elem_id="btn2") | |
out = gr.DataFrame(headers = ["Sequence", "Antifungal", "no-AFP score", 'AFP-score']) | |
btn1.click(fn=prediction, inputs=inp, outputs=out) | |
btn2.click(fn=lambda:"", outputs=inp) | |
demo.launch(show_api=False) |