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Update main.py
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main.py
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@@ -664,37 +664,42 @@ with demo.route("Object Localization", "/object-localization") as obj_loc:
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# ββ VQA PAGE ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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with demo.route("Visual Question Answering", "/vqa"):
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# gr.Markdown("# π€ Visual Question Answering")
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# gr.Markdown("### π Coming Soon")
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# gr.Markdown(
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# "This challenge is currently under development. "
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# )
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with demo.route("Visual Question Answering", "/vqa") as vqa_page:
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with gr.Row():
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with gr.Column(scale=5):
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gr.Markdown("# π€ Visual Question Answering Challenge")
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gr.Markdown(
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with gr.Column(scale=1, min_width=160):
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gr.LoginButton(size="lg")
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vqa_greeting = gr.Markdown("π Log in to
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gr.Markdown("---")
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with gr.Tabs():
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with gr.TabItem("π Leaderboard"):
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gr.Markdown("### VQA Challenge Rankings")
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vqa_lb_table = gr.Dataframe(interactive=False, wrap=True)
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refresh_vqa_lb_btn = gr.Button("π Refresh Leaderboard", variant="secondary", size="sm")
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def refresh_vqa_leaderboard(profile: gr.OAuthProfile | None):
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#
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cols = ["Rank", "Team", "Model", "Accuracy", "Scored At"]
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empty_df = pd.DataFrame(columns=cols)
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@@ -702,33 +707,101 @@ with demo.route("Visual Question Answering", "/vqa") as vqa_page:
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df = _load_leaderboard_df()
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# Filter for VQA challenge specifically
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if not df.empty and "challenge_type" in df.columns:
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df = df[df["challenge_type"].str.lower() == "
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except Exception as e:
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return empty_df, f"β
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if df.empty:
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# Task 2: Return empty DF if no submissions
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return empty_df, "βΉοΈ No VQA submissions yet. Be the first!", get_user_greeting(profile)
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# Process the data if it exists
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df_display = df.copy()
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df_display.insert(0, "Rank", range(1, len(df_display) + 1))
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return df_display, "", get_user_greeting(profile)
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)
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# ββ ANSWER GROUNDING PAGE βββββββββββββββββββββββββββββββββββββββββββββ
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with demo.route("Answer Grounding", "/answer-grounding"):
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gr.Markdown("# π Answer Grounding")
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)
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# ββ VQA PAGE ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# with demo.route("Visual Question Answering", "/vqa"):
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# gr.Markdown("# π€ Visual Question Answering")
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# gr.Markdown("### π Coming Soon")
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# gr.Markdown(
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# "This challenge is currently under development. "
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# )
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# ββ VQA PAGE ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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with demo.route("Visual Question Answering", "/vqa") as vqa_page:
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with gr.Row():
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with gr.Column(scale=5):
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gr.Markdown("# π€ Visual Question Answering Challenge")
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gr.Markdown(
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"Answer open-ended questions about images taken by blind users. "
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"Models are evaluated on answer accuracy and relevance."
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)
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with gr.Column(scale=1, min_width=160):
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gr.LoginButton(size="lg")
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vqa_greeting = gr.Markdown("π Log in to submit.")
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gr.Markdown("---")
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with gr.Tabs():
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# 1. Leaderboard Tab
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with gr.TabItem("π Leaderboard"):
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gr.Markdown("### VQA Challenge Rankings")
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gr.Markdown("Ranked by **Accuracy** (descending).")
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vqa_lb_msg = gr.Markdown("")
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vqa_lb_table = gr.Dataframe(interactive=False, wrap=True)
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refresh_vqa_lb_btn = gr.Button("π Refresh Leaderboard", variant="secondary", size="sm")
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def refresh_vqa_leaderboard(profile: gr.OAuthProfile | None):
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# Task 2: Default empty DF structure
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cols = ["Rank", "Team", "Model", "Accuracy", "Scored At"]
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empty_df = pd.DataFrame(columns=cols)
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df = _load_leaderboard_df()
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# Filter for VQA challenge specifically
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if not df.empty and "challenge_type" in df.columns:
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df = df[df["challenge_type"].str.lower() == "visual question answering"]
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except Exception as e:
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return empty_df, f"β Could not load leaderboard: {e}", get_user_greeting(profile)
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if df.empty:
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return empty_df, "βΉοΈ No VQA submissions yet. Be the first!", get_user_greeting(profile)
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df_display = df.copy()
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df_display.insert(0, "Rank", range(1, len(df_display) + 1))
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if "timestamp" in df_display.columns:
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df_display["Scored At"] = pd.to_datetime(
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df_display["timestamp"], unit="s", errors="coerce"
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).dt.strftime("%d %b %Y, %I:%M %p")
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# Filter to VQA specific metrics
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display_cols = ["Rank", "team", "model", "accuracy", "Scored At"]
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df_display = df_display[[c for c in display_cols if c in df_display.columns]]
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df_display.rename(columns={"team": "Team", "model": "Model", "accuracy": "Accuracy"}, inplace=True)
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return df_display, "", get_user_greeting(profile)
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refresh_vqa_lb_btn.click(refresh_vqa_leaderboard, outputs=[vqa_lb_table, vqa_lb_msg, vqa_greeting])
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vqa_page.load(refresh_vqa_leaderboard, outputs=[vqa_lb_table, vqa_lb_msg, vqa_greeting])
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# 2. Submit Tab
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with gr.TabItem("π Submit Predictions"):
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with gr.Row():
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vqa_submit_greeting = gr.Markdown("π Log in with HuggingFace to submit.")
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vqa_cap_info = gr.Markdown("")
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gr.Markdown("---")
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with gr.Row():
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with gr.Column(scale=3):
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gr.Markdown("#### Upload VQA Results")
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vqa_file_input = gr.File(label="Choose a JSON file", file_types=[".json"])
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with gr.Column(scale=2):
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gr.Markdown("#### Submission Info")
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vqa_team_input = gr.Textbox(label="Team / Display Name")
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vqa_model_input = gr.Textbox(label="Model Name")
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vqa_phase_input = gr.Dropdown(
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label="Phase",
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choices=[p["label"] for p in PHASES],
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value=PHASES[0]["label"],
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)
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vqa_submit_btn = gr.Button("Submit (Queue for Evaluation)", variant="primary", size="lg")
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vqa_submit_status = gr.Markdown("")
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vqa_sid_box = gr.Code(label="Submission ID", visible=False)
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def do_vqa_submit(file, team, model, phase, profile: gr.OAuthProfile | None):
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# We pass "Visual Question Answering" as the challenge type
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msg, sid = handle_submit(file, team, model, phase, "Visual Question Answering", profile)
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return msg, gr.update(value=sid, visible=bool(sid))
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vqa_submit_btn.click(
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do_vqa_submit,
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inputs=[vqa_file_input, vqa_team_input, vqa_model_input, vqa_phase_input],
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outputs=[vqa_submit_status, vqa_sid_box],
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)
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def update_vqa_submit_ui(profile: gr.OAuthProfile | None):
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return get_user_greeting(profile), get_daily_cap_info(profile)
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vqa_page.load(update_vqa_submit_ui, outputs=[vqa_submit_greeting, vqa_cap_info])
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# 3. My Submissions Tab
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with gr.TabItem("π My Submissions"):
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vqa_my_sub_greeting = gr.Markdown("π Log in to view your submissions.")
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vqa_my_sub_stats = gr.Markdown("")
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with gr.Row():
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vqa_phase_filter = gr.Dropdown(
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label="Filter by Phase",
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choices=["All"] + [p["codename"] for p in PHASES],
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value="All",
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scale=2
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)
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vqa_refresh_my_btn = gr.Button("π Refresh", variant="secondary", scale=1)
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vqa_my_sub_table = gr.Dataframe(interactive=False, wrap=True)
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def refresh_vqa_my_subs(phase_filter, profile: gr.OAuthProfile | None):
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df, msg, stats = load_my_submissions(phase_filter, profile)
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# Further filter results to only show VQA
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if not df.empty and "Challenge Type" in df.columns:
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df = df[df["Challenge Type"] == "Visual Question Answering"]
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return df, msg, stats, get_user_greeting(profile)
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vqa_refresh_my_btn.click(
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refresh_vqa_my_subs,
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inputs=[vqa_phase_filter],
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outputs=[vqa_my_sub_table, gr.Markdown(), vqa_my_sub_stats, vqa_my_sub_greeting],
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)
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vqa_page.load(
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refresh_vqa_my_subs,
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inputs=[vqa_phase_filter],
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outputs=[vqa_my_sub_table, gr.Markdown(), vqa_my_sub_stats, vqa_my_sub_greeting],
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)
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# ββ ANSWER GROUNDING PAGE βββββββββββββββββββββββββββββββββββββββββββββ
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with demo.route("Answer Grounding", "/answer-grounding"):
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gr.Markdown("# π Answer Grounding")
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