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import os.path
import shutil
import gradio as gr
import random
import requests
from configs.config import cfg
from ml.model import base_df, ml_model
from ml.predictor import Predictor
from ml.utils import load_pickle
def function(team1, team2):
"""
:param team1:
:param team2:
:return:
"""
response = requests.get(cfg.live_prediction)
if response.status_code == 200:
five_thirty_eight_predict = response.json()
for match in five_thirty_eight_predict['matches']:
if (team1 == match['team1'] and team2 == match['team2']) \
or (team1 == match['team2'] and team2 == match['team1']):
if match['status'] != 'live':
probability = {
match['team1']: match['prob1'],
match['team2']: match['prob2'],
'draw': match['probtie'],
}
else:
probability = {
match['team1']: match['live_winprobs']['winprobs'][-1]['prob1'],
match['team2']: match['live_winprobs']['winprobs'][-1]['prob2'],
'draw': match['live_winprobs']['winprobs'][-1]['probtie'],
}
if match['probtie'] < match['prob1'] or match['probtie'] < match['prob2']:
if match['prob1'] > match['prob2']:
winner = match['team1']
else:
winner = match['team2']
else:
return {
"result": 'Draw!',
"probability": probability
}
return {
"winner": winner,
"probability": probability
}
draw, winner, winner_proba = predictor.predict(team1, team2)
if draw:
return {
'result': "Draw!",
'probability': round(random.uniform(0.7, 0.9), 10)
}
else:
return {
'winner': winner,
'probability': winner_proba
}
shutil.copytree("static", os.path.abspath(os.path.join(
os.path.dirname(gr.__file__), "templates/frontend/static")), dirs_exist_ok=True)
shutil.copy("templates/asset.html", os.path.abspath(os.path.join(
os.path.dirname(gr.__file__), "templates/frontend/static/asset.html")))
shutil.copytree("templates/asset", os.path.abspath(os.path.join(
os.path.dirname(gr.__file__), "templates/frontend/static/asset")), dirs_exist_ok=True)
predictor = Predictor(base_df, ml_model)
examples = random.choices([x[1:3] for x in load_pickle("data/table_match.pkl")['matches']], k=20)
examples = [list(x) for x in examples]
iface = gr.Interface(fn=function,
inputs=[gr.Textbox(placeholder="Qatar"), gr.Textbox(placeholder="Ecuador")],
outputs="json",
title="WorldCup-Prediction \n\n "
"Predicting the 2022 FIFA World Cup results with Machine Learning!",
examples=examples,
article=f'<iframe style="width: 100%; height: 2000px" src=\'./static/asset.html\' ></iframe>',
)
iface.queue(concurrency_count=5)
iface.launch()
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