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import gradio as gr
import pandas as pd
import random
data = pd.read_pickle("merged_all_table.pkl", compression='bz2')
home_team_id = sorted(data["home_team_long_name"].unique())
away_team_id = sorted(data["away_team_long_name"].unique())
def predict(Home_team, Away_team, Model_name):
if Home_team == "":
raise gr.Error("Home Team is required, Please Select The Home Team!")
if Away_team == "":
raise gr.Error("Away Team is required, Please Select The Away Team!")
if Model_name == "":
raise gr.Error("Model is required, Please Select The Model!")
if Model_name == "Simple Model":
# model = km.load_model('models/simple_model.pkl')
pass
return "Model is in under construction 🛠️🚜"
# markup table for markdown
# # Members:
# | Students Name | Student ID |
# | :--- | :----: |
# | Zeel Karshanbhai Sheladiya | 500209119 |
# | Ravikumar Chandrakantbhai Patel | 500196861 |
# | Dharma Teja Reddy Bandreddi | 500209454 |
# | Sai Charan Reddy Meda | 500201602 |
# | Aditya Babu | 500209122 |
# | Sudip Bhattarai | 500198055 |
# | NOMAN FAZAL MUKADAM | 500209115 |
# | Leela Prasad Kavuri | 500209550 |
# | Vamsi Dasari | 500200775 |
with gr.Blocks() as demo:
gr.Markdown("""
# Subject: Data Science Project Management and Requirement Gathering 02 (Group 4)
[](https://github.com/ravi7522/Football-Prediction)
""")
with gr.Row():
gr.Label("⚽️ Football Prediction ⚽️", container=False)
with gr.Row():
with gr.Column():
dd_home_team = gr.Dropdown(
label="Home Team",
choices=home_team_id,
info="Select Your Home Team:",
multiselect=False,
)
with gr.Column():
dd_away_team = gr.Dropdown(
label="Away Team",
choices=away_team_id,
info="Select Your Away Team:",
multiselect=False,
)
with gr.Row():
with gr.Column():
dd_model = gr.Dropdown(
label="Model ( Feature Under Construction 🚧 )",
choices=["Simple Model"],
info="Select Your Model:",
multiselect=False,
)
with gr.Row():
predict_btn = gr.Button(value="Predict")
with gr.Row():
Answer = gr.Label("👋 Hello, Let us predict the Football Match 💁♂️", container=False)
predict_btn.click(
predict,
inputs=[
dd_home_team,
dd_away_team,
dd_model,
],
outputs=[Answer],
)
demo.launch() |