import json import os from datetime import datetime, timezone import gradio as gr import pandas as pd from auth_utils import get_user_greeting, get_daily_cap_info from hf_utils import ( _load_leaderboard_df, _load_user_submissions, _create_submission_record, _count_submissions_today, _get_cap_for_phase, _today_utc_str, ) from config import DAILY_SUBMISSION_CAP from challenges.object_localization.config import ( PHASES, CHALLENGE_TYPES, LEADERBOARD_METRICS, DEFAULT_SORT_METRIC, LEADERBOARD_FILE, CHALLENGE_PHASE, EVAL_DETAILS_MD, FORMAT_MD, ) from challenges.object_localization.validate import validate_submission def load_leaderboard(): try: df = _load_leaderboard_df(LEADERBOARD_FILE, LEADERBOARD_METRICS) except Exception as e: return pd.DataFrame(), f"❌ Could not load leaderboard: {e}" if not df.empty and "phase_codename" in df.columns: df = df[df["phase_codename"] == CHALLENGE_PHASE] if df.empty: return pd.DataFrame(), "ℹ️ No scored Challenge phase submissions yet. Be the first!" df = df.sort_values(by=DEFAULT_SORT_METRIC, ascending=False, kind="mergesort") df_display = df.copy() df_display.insert(0, "Rank", range(1, len(df_display) + 1)) if "timestamp" in df_display.columns: df_display["Scored At"] = pd.to_datetime( df_display["timestamp"], unit="s", errors="coerce" ).dt.strftime("%d %b %Y, %I:%M %p") df_display.drop(columns=["timestamp"], inplace=True) for col in ["username", "email", "phase_codename", "submission_id"]: if col in df_display.columns: df_display.drop(columns=[col], inplace=True) return df_display, "" def handle_submit(file, team, model_name, phase_label, challenge_type, profile: gr.OAuthProfile | None): if profile is None: return "❌ You must be logged in with your HuggingFace account to submit.", "" username = profile.username email = getattr(profile, "email", "") or "" from config import SUBMISSIONS_TOKEN if not SUBMISSIONS_TOKEN: return "❌ Missing SUBMISSIONS_TOKEN. Add it in Space Settings → Secrets.", "" if file is None: return "❌ Please upload a JSON file.", "" if not team.strip(): return "❌ Please enter a Team / Display Name.", "" if not model_name.strip(): return "❌ Please enter a Model Name.", "" phase_codename = next((p["codename"] for p in PHASES if p["label"] == phase_label), phase_label) cap = _get_cap_for_phase(phase_codename) subs_today = _count_submissions_today(username, phase_codename) if subs_today >= cap: phase_label_str = "challenge" if phase_codename == "test-challenge2024" else "this" return f"⛔ You've reached your daily limit of {cap} submission(s) for the {phase_label_str} phase. Come back tomorrow!", "" try: with open(file, "r", encoding="utf-8") as f: pred_obj = json.load(f) except Exception: return "❌ Could not parse JSON file.", "" ok, msg = validate_submission(pred_obj) if not ok: return f"❌ Invalid submission format: {msg}", "" original_filename = os.path.basename(file) try: submission_id = _create_submission_record( pred=pred_obj, team=team, model_name=model_name, phase_codename=phase_codename, challenge_type=challenge_type, original_filename=original_filename, username=username, email=email, ) except Exception as e: return f"❌ Upload failed: {e}", "" remaining = cap - subs_today - 1 return ( f"✅ Submission queued successfully! Visit **My Submissions** to see the results. " f"You have {remaining}/{cap} submissions remaining today for this phase.", submission_id, ) def load_my_submissions(phase_filter: str, profile: gr.OAuthProfile | None): if profile is None: return pd.DataFrame(), "❌ Please log in to view your submissions.", "" username = profile.username submissions = _load_user_submissions(username) if not submissions: return pd.DataFrame(), "ℹ️ No submissions yet. Head to Submit Predictions to get started!", "" all_submissions = submissions[:] if phase_filter and phase_filter != "All": submissions = [s for s in submissions if s["phase"] == phase_filter] if not submissions: return pd.DataFrame(), f"ℹ️ No submissions found for phase **{phase_filter}**.", "" state_icons = {"queued": "🟡", "running": "🔵", "done": "🟢", "failed": "🔴", "unknown": "⚪"} df = pd.DataFrame(submissions) if "timestamp" in df.columns: df["Submitted At"] = pd.to_datetime( df["timestamp"], unit="s", errors="coerce" ).dt.strftime("%d %b %Y, %I:%M %p") if "state" in df.columns: df["Status"] = df["state"].apply(lambda s: f"{state_icons.get(s, '⚪')} {s.capitalize()}") display_cols = ["Submitted At", "Status", "team", "model", "phase", "challenge_type", "error"] metric_cols = [m for m in LEADERBOARD_METRICS if m in df.columns] display_cols += metric_cols df_display = df[[c for c in display_cols if c in df.columns]].copy() df_display.rename(columns={ "team": "Team", "model": "Model", "phase": "Phase", "challenge_type": "Challenge Type", "error": "Error", }, inplace=True) for m in metric_cols: if m in df_display.columns: df_display[m] = df_display[m].apply(lambda x: f"{x:.4f}" if pd.notna(x) else "") total = len(all_submissions) done = sum(1 for s in all_submissions if s["state"] == "done") today_count = sum( 1 for s in all_submissions if datetime.fromtimestamp(s["timestamp"], tz=timezone.utc).strftime("%Y-%m-%d") == _today_utc_str() ) stats = ( f"**Total:** {total}  |  " f"**Scored:** {done}  |  " f"**Today:** {today_count}/{DAILY_SUBMISSION_CAP}" ) return df_display, "", stats def build_ol_page(demo: gr.Blocks) -> None: with demo.route("Object Localization", "/object-localization") as obj_loc: with gr.Row(): with gr.Column(scale=5): gr.Markdown("# 🎯 Object Localization Challenge") gr.Markdown( "Submit bounding box and instance segmentation predictions " "evaluated automatically against hidden ground-truth annotations." ) with gr.Column(scale=1, min_width=160): gr.LoginButton(size="lg") ol_greeting = gr.Markdown("👋 Log in to submit.") gr.Markdown("---") with gr.Tabs(): # ── Submit ── with gr.TabItem("🚀 Submit Predictions"): with gr.Row(): ol_submit_greeting = gr.Markdown("👋 Log in with HuggingFace to submit.") ol_cap_info = gr.Markdown("") gr.Markdown("---") with gr.Row(): with gr.Column(scale=3): gr.Markdown("#### Upload Submission File") ol_file_input = gr.File(label="Choose a JSON file", file_types=[".json"]) with gr.Accordion("📄 Submission Format", open=False): gr.Markdown(FORMAT_MD) with gr.Column(scale=2): gr.Markdown("#### Submission Info") ol_team_input = gr.Textbox(label="Team / Display Name", placeholder="e.g. My Awesome Team") ol_model_input = gr.Textbox(label="Model Name", placeholder="e.g. ResNet50-FPN") ol_phase_input = gr.Dropdown( label="Phase", choices=[p["label"] for p in PHASES], value=PHASES[0]["label"], ) ol_challenge_input = gr.Radio( label="Challenge Type", choices=CHALLENGE_TYPES, value=CHALLENGE_TYPES[0], ) ol_submit_btn = gr.Button("Submit (Queue for Evaluation)", variant="primary", size="lg") ol_submit_status = gr.Markdown("") ol_sid_box = gr.Code(label="Submission ID", language=None, visible=False) def do_ol_submit(file, team, model_name, phase_label, challenge_type, profile: gr.OAuthProfile | None): msg, sid = handle_submit(file, team, model_name, phase_label, challenge_type, profile) return msg, gr.update(value=sid, visible=bool(sid)) ol_submit_btn.click( do_ol_submit, inputs=[ol_file_input, ol_team_input, ol_model_input, ol_phase_input, ol_challenge_input], outputs=[ol_submit_status, ol_sid_box], ) def update_ol_submit_ui(profile: gr.OAuthProfile | None): return get_user_greeting(profile), get_daily_cap_info(profile, PHASES) obj_loc.load(update_ol_submit_ui, outputs=[ol_submit_greeting, ol_cap_info]) # ── My Submissions ── with gr.TabItem("📋 My Submissions"): ol_my_sub_greeting = gr.Markdown("👋 Log in with HuggingFace to view your submissions.") ol_my_sub_stats = gr.Markdown("") with gr.Row(): ol_phase_filter = gr.Dropdown( label="Filter by Phase", choices=["All"] + [p["codename"] for p in PHASES], value="All", scale=2, ) ol_refresh_my_btn = gr.Button("🔄 Refresh", variant="secondary", scale=1) ol_my_sub_msg = gr.Markdown("") ol_my_sub_table = gr.Dataframe(interactive=False, wrap=True) def refresh_ol_my_subs(phase_filter, profile: gr.OAuthProfile | None): df, msg, stats = load_my_submissions(phase_filter, profile) return df, msg, stats, get_user_greeting(profile) ol_refresh_my_btn.click( refresh_ol_my_subs, inputs=[ol_phase_filter], outputs=[ol_my_sub_table, ol_my_sub_msg, ol_my_sub_stats, ol_my_sub_greeting], ) ol_phase_filter.change( refresh_ol_my_subs, inputs=[ol_phase_filter], outputs=[ol_my_sub_table, ol_my_sub_msg, ol_my_sub_stats, ol_my_sub_greeting], ) obj_loc.load( refresh_ol_my_subs, inputs=[ol_phase_filter], outputs=[ol_my_sub_table, ol_my_sub_msg, ol_my_sub_stats, ol_my_sub_greeting], ) # ── Leaderboard ── with gr.TabItem("🏆 Leaderboard"): gr.Markdown("### Challenge Phase Rankings") gr.Markdown(f"Ranked by **{DEFAULT_SORT_METRIC}** (descending). Challenge phase only.") with gr.Accordion("📐 How is the Score Calculated?", open=False): gr.Markdown(EVAL_DETAILS_MD) ol_lb_msg = gr.Markdown("") ol_lb_table = gr.Dataframe(interactive=False, wrap=True) ol_refresh_lb_btn = gr.Button("🔄 Refresh Leaderboard", variant="secondary", size="sm") def refresh_ol_leaderboard(profile: gr.OAuthProfile | None): df, msg = load_leaderboard() return df, msg, get_user_greeting(profile) ol_refresh_lb_btn.click(refresh_ol_leaderboard, outputs=[ol_lb_table, ol_lb_msg, ol_greeting]) obj_loc.load(refresh_ol_leaderboard, outputs=[ol_lb_table, ol_lb_msg, ol_greeting])