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import math
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
def get_result(team1, prob1, score1, team2, prob2, score2, probtie):
if prob1 > prob2 and prob1 > probtie:
winner = {"name": team1, "probability": prob1, "goals": score1}
loser = {"name": team2, "probability": prob2, "goals": score2}
elif prob1 < prob2 and prob2 > probtie:
loser = {"name": team1, "probability": prob1, "goals": score1}
winner = {"name": team2, "probability": prob2, "goals": score2}
else:
loser = {"name": None, "probability": 0.0, "goals": score1}
winner = {"name": None, "probability": 0.0, "goals": score2}
result = {
"winner": winner,
"loser": loser,
"draw": {"probability": probtie},
}
return result
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 not (
(team1 == match["team1"] and team2 == match["team2"])
or (team1 == match["team2"] and team2 == match["team1"])
):
continue
if match["status"] != "live":
result = get_result(
match["team1"],
match["prob1"],
math.ceil(match["adj_score1"])
if "adj_score1" in match
else math.ceil(match["o1"] - match["d2"]),
match["team2"],
match["prob2"],
math.ceil(match["adj_score2"])
if "adj_score2" in match
else math.ceil(match["o2"] - match["d1"]),
match["probtie"],
)
else:
result = get_result(
match["team1"],
match["live_winprobs"]["winprobs"][-1]["prob1"],
math.ceil(match["adj_score1"])
if "adj_score1" in match
else math.ceil(match["o1"] - match["d2"]),
match["team2"],
match["live_winprobs"]["winprobs"][-1]["prob2"],
math.ceil(match["adj_score2"])
if "adj_score2" in match
else math.ceil(match["o2"] - match["d1"]),
match["probtie"],
)
return result
draw, winner, winner_proba = predictor.predict(team1, team2)
if draw:
draw_prob = round(random.uniform(0.7, 0.9), 10)
winner_proba = round(random.uniform(0, 1 - draw_prob), 10)
loser_proba = 1 - draw_prob - winner_proba
return {
"winner": {"name": team1, "probability": winner_proba, "goals": None},
"loser": {"name": team2, "probability": loser_proba, "goals": None},
"draw": {"probability": draw_prob},
}
else:
loser_proba = round(random.uniform(0, 1 - winner_proba), 10)
return {
"winner": {"name": winner, "probability": winner_proba, "goals": None},
"loser": {
"name": team1 if winner == team2 else team2,
"probability": loser_proba,
"goals": None,
},
"draw": {"probability": 1 - winner_proba - loser_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 = (
("Croatia", "Argentina"),
("Morocco", "France"),
("Argentina", "France"),
("Morocco", "Croatia"),
)
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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