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| from fastai.tabular.all import * | |
| import gradio as gr | |
| import pathlib | |
| plt = platform.system() | |
| if plt == 'Linux': pathlib.WindowsPath = pathlib.PosixPath | |
| # path = Path() | |
| df = pd.read_csv("rookie_year.csv") | |
| learn = load_learner("export.pkl") | |
| columns = ["Name", "G", "GS", "Cmp", "Att", "Yds", "Cmp%", "TD", "Int", "Y/G", "Sk"] | |
| def predict(data): | |
| row = df[df["Name"] == data] | |
| row = row.loc[:, ~df.columns.str.contains('^Unnamed')] | |
| if not len(row): | |
| print("ERROR: No QB in database with this name") | |
| return | |
| pred_row, clas, probs = learn.predict(row.iloc[0]) | |
| prediction = pred_row.decode()["Tier"].item() | |
| return row[columns], prediction | |
| demo = gr.Interface(fn=predict, | |
| inputs="text", | |
| outputs=[ | |
| gr.Dataframe(row_count=1, col_count=11, headers=columns, label="Rookie Year Stats"), | |
| gr.Textbox(label="Prediction") | |
| ], | |
| title="Rookie QB Career Prediction (Name)", | |
| description="Given Name of QB who has played in the NFL, predict their career tier. Uses data from https:\/\/www.pro-football-reference.com. Tiers based on PFR Approximate Value.", | |
| article="See more details at https://github.com/mhrice/Rookie-QB-Predictions", | |
| examples=["Tom Brady", "Joe Burrow", "Trevor Lawrence"] | |
| ) | |
| demo.launch() |