app.py

import gradio as gr
from evaluate import run_evaluation
import pandas as pd

LEADERBOARD_CSV = "leaderboard.csv"
import os
from datetime import datetime, date
from datasets import load_dataset
dataset = load_dataset(os.getenv('VG_user'))
aaa = dataset['train'].to_dict()
for i in aaa:
    aaa[i] = aaa[i][0]
users =aaa
SUBMIT_RECORD = "submissions.csv"
MAX_SUBMIT_PER_DAY = 5

def check_submission_limit(username):
    if not os.path.exists(SUBMIT_RECORD):
        return True  # 没有人提交过

    df = pd.read_csv(SUBMIT_RECORD)
    today = date.today()

    user_today_subs = df[
        (df["username"] == username) &
        (pd.to_datetime(df["timestamp"]).dt.date == today)
    ]

    return len(user_today_subs) < MAX_SUBMIT_PER_DAY

def record_submission(username):
    now = datetime.now().isoformat()
    if os.path.exists(SUBMIT_RECORD):
        df = pd.read_csv(SUBMIT_RECORD)
    else:
        df = pd.DataFrame(columns=["username", "timestamp"])
    df.loc[len(df)] = {"username": username, "timestamp": now}
    df.to_csv(SUBMIT_RECORD, index=False)
import json
def check_user_valid(username, password):

    return username in users and users.get(username) == password

def update_leaderboard(username, score1, score2, score3):
    # 追加记录到总提交记录
    if os.path.exists("leaderboard.csv"):
        sub_df = pd.read_csv("leaderboard.csv")
    else:
        sub_df = pd.DataFrame(columns=["username", "[email protected]", "[email protected]", "[email protected]"])
    sub_df.loc[len(sub_df)] = [username, score1, score2, score3]
    sub_df.to_csv("leaderboard.csv", index=False)

    # 从所有提交中挑选每用户score1最高的记录
    top_df = sub_df.sort_values("[email protected]", ascending=False).drop_duplicates("username", keep="first")
    top_df = top_df.sort_values("[email protected]", ascending=False)
    top_df.to_csv("leaderboard.csv", index=False)
    return top_df

def show_lb():
    if os.path.exists("leaderboard.csv"):
        sub_df = pd.read_csv("leaderboard.csv")
    else:
        sub_df = pd.DataFrame(columns=["username", "[email protected]", "[email protected]", "[email protected]"])
    return sub_df
def evaluate_and_update(pred_file, username,password):
    
    if not check_submission_limit(username):
        return "⛔ Submission limit exceeded for today.", pd.DataFrame()
    if not check_user_valid(username, password):
        return "❌ Invalid username or password", pd.DataFrame()
    score1, score2, score3 = run_evaluation(pred_file.name)
    record_submission(username)
    leaderboard_df = update_leaderboard(username, score1, score2, score3)

    return f"✅ [email protected]: {score1:.4f}, [email protected]: {score2:.4f}, [email protected]: {score3:.4f}", leaderboard_df



with gr.Blocks() as demo:
    gr.Markdown("# 🧊 MMScan HVG Challenge")
    with gr.Row():
        username = gr.Textbox(label="Username")
        password = gr.Textbox(label="Password", type="password")
    upload = gr.File(label="Upload your prediction (.json)")
    score_text = gr.Textbox(label="Evaluation score")
    leaderboard = gr.Dataframe(headers=["Name", "Score"], interactive=False)

    submit_btn = gr.Button("Submit")
    submit_btn.click(
        fn=evaluate_and_update,
        inputs=[upload, username,password],
        outputs=[score_text, leaderboard]
    )
    show_btn = gr.Button("Show Leaderboard")
    show_btn.click(fn=show_lb,inputs=[],outputs=[leaderboard])

demo.launch()