| """World Cup Heros — football shot analysis (Gradio, ZeroGPU Space). |
| |
| One RF-DETR-Seg model detects ball + players + goal; pure geometry/physics derive the |
| events: was it a goal (+ when), who shot it, their pose & shooting foot, and shot speed. |
| Upload a clip or pick one of the 12 held-out test examples. |
| |
| ZeroGPU: only the RF-DETR detection runs inside the @spaces.GPU window; the goal physics, |
| possession, MediaPipe pose, speed and rendering all run on CPU. |
| |
| Left: upload + example clips. |
| Right: the clean analysed video (player masks + P# labels + ball trail + goal), then a |
| Result table (goal / foot, predicted vs actual), a Shot-speed card, and a |
| Pose-Detection card. |
| """ |
| import glob |
| import json |
| import os |
|
|
| import gradio as gr |
| import spaces |
| from huggingface_hub import hf_hub_download |
|
|
| from futheros import pipeline as P |
| from futheros import coach as C |
| from futheros.render import render, pose_card_img |
|
|
| HF_MODEL = "build-small-hackathon/futheros-rfdetr-seg" |
| RENDER_DIR = "/tmp/app_renders"; os.makedirs(RENDER_DIR, exist_ok=True) |
| GT = json.load(open("labels/goal_labels.json")) |
| LEG = json.load(open("labels/leg_labels.json")) |
| EXAMPLES = sorted(glob.glob("examples/*.mp4")) |
| EDGE_EMOJIS = ["🏴", "⚽", "🇫🇷", "⚽", "🇧🇷", "⚽", "🇦🇷", "⚽", "🇪🇸", "⚽", |
| "🇩🇪", "⚽", "🇵🇹", "⚽", "🇳🇱", "⚽", "🇧🇪", "⚽"] |
| EDGE_STRIP = " \n".join(EDGE_EMOJIS * 2) |
| CONFETTI_JS = """ |
| (g) => { |
| if (g === 'goal') { |
| const fire = () => { |
| window.confetti({particleCount:200, spread:100, origin:{y:0.6}}); |
| setTimeout(()=>window.confetti({particleCount:150, spread:120, origin:{y:0.5}}), 200); |
| setTimeout(()=>window.confetti({particleCount:120, angle:60, spread:80, origin:{x:0}}), 350); |
| setTimeout(()=>window.confetti({particleCount:120, angle:120, spread:80, origin:{x:1}}), 350); |
| }; |
| if (!window.confetti) { |
| const s = document.createElement('script'); |
| s.src = 'https://cdn.jsdelivr.net/npm/canvas-confetti@1.9.3/dist/confetti.browser.min.js'; |
| s.onload = fire; document.head.appendChild(s); |
| } else { fire(); } |
| } |
| } |
| """ |
|
|
| CSS = """ |
| .gradio-container{background:linear-gradient(160deg,#f3fdf6 0%,#eef6ff 55%,#fff7ea 100%) !important;} |
| #wc-head{text-align:center !important;max-width:980px;margin:0 auto !important;} |
| #wc-head h1{text-align:center !important;font-size:2.7rem !important;font-weight:900 !important; |
| letter-spacing:-1px;margin:6px 0 4px !important; |
| background:linear-gradient(90deg,#15803d,#0891b2,#d97706); |
| -webkit-background-clip:text;background-clip:text;-webkit-text-fill-color:transparent;} |
| #wc-head p,#wc-head span{text-align:center !important;color:#475569 !important;} |
| button.primary,.primary>button{background:linear-gradient(90deg,#16a34a,#0ea5e9) !important; |
| border:none !important;color:#fff !important;font-weight:700 !important;} |
| .block,.gr-box{border-radius:14px !important;} |
| footer{display:none !important;} |
| """ |
|
|
| _MODEL = None |
|
|
|
|
| def _model(): |
| """Lazy-load the detector (checkpoint pulled from HF, cached).""" |
| global _MODEL |
| if _MODEL is None: |
| ckpt = hf_hub_download(HF_MODEL, "checkpoint_best_ema.pth") |
| _MODEL = P.rfdetr_model(ckpt, "small") |
| return _MODEL |
|
|
|
|
| @spaces.GPU(duration=120) |
| def _detect(video_path): |
| """The only GPU step: RF-DETR-Seg over every frame -> tracks dict.""" |
| return P.detect_rfdetr(video_path, _model()) |
|
|
|
|
| def _truth(name): |
| rel = f"5/{name}.mp4" |
| return {"goal": GT.get(rel), "leg": LEG.get(rel)} |
|
|
|
|
| def _table_html(res, truth): |
| def row(metric, pred, actual, match=None): |
| key = pred if match is None else match |
| ok = (actual is None) or (str(key).upper() == str(actual).upper()) |
| col = "#16a34a" if ok else "#dc2626" |
| act = f"<td style='padding:6px 14px;color:#555'>{actual}</td>" if actual is not None else "<td style='padding:6px 14px;color:#999'>—</td>" |
| return (f"<tr><td style='padding:6px 14px;font-weight:600'>{metric}</td>" |
| f"<td style='padding:6px 14px;color:{col};font-weight:700'>{pred}</td>{act}</tr>") |
| goal_p = res.goal.upper() + (f" @ {res.goal_time:.1f}s" if res.goal == "goal" and res.goal_time else "") |
| rows = (row("⚽ Goal", goal_p, (truth.get("goal") or "").upper() or None, match=res.goal) |
| + row("🦶 Shooting foot", res.foot, truth.get("leg"))) |
| return ("<div style='font-weight:600;color:#666;margin-bottom:6px'>Result</div>" |
| "<table style='border-collapse:collapse;font-size:15px;width:100%'>" |
| "<tr style='border-bottom:2px solid #ddd;color:#999;font-size:11px'>" |
| "<th style='text-align:left;padding:4px 14px'>METRIC</th>" |
| "<th style='text-align:left;padding:4px 14px'>PREDICTED</th>" |
| "<th style='text-align:left;padding:4px 14px'>ACTUAL</th></tr>" |
| f"{rows}</table>") |
|
|
|
|
| def _speed_html(res): |
| spd = f"{res.speed_kmh:.0f}" if res.speed_kmh else "—" |
| return ("<div style='text-align:center;padding:10px'>" |
| "<div style='font-weight:600;color:#666'>💨 Shot speed</div>" |
| f"<div style='font-size:40px;font-weight:800;color:#0ea5e9;line-height:1.1'>{spd}</div>" |
| "<div style='color:#999;font-size:13px'>km/h (ball)</div></div>") |
|
|
|
|
| def _coach_loading_html(): |
| return ("<div style='padding:14px;border:1px dashed #cbd5e1;border-radius:10px;color:#64748b'>" |
| "🧠 <b>AI Coach</b> — reading your technique… " |
| "<i>(Nemotron-VL via Modal)</i></div>") |
|
|
|
|
| def _coach_html(text): |
| body = text.strip().replace("\n", "<br>") |
| return ("<div style='padding:16px;border:1px solid #bbf7d0;background:#f0fdf4;border-radius:10px'>" |
| "<div style='font-weight:700;color:#065f46;margin-bottom:8px'>🧠 AI Coach " |
| "<span style='font-weight:400;color:#94a3b8;font-size:12px'>· Nemotron-Nano-VL (NVIDIA)</span></div>" |
| f"<div style='font-size:14px;color:#334155;line-height:1.55'>{body}</div></div>") |
|
|
|
|
| def _coach_error_html(): |
| return ("<div style='padding:16px;border:1px solid #fed7aa;background:#fff7ed;border-radius:10px;color:#9a3412'>" |
| "⚠️ <b>Couldn't reach the AI coach.</b> Your shot analysis above is complete — " |
| "the coaching add-on is offline right now.</div>") |
|
|
|
|
| def analyse_clip(video_path): |
| if not video_path: |
| yield None, "", "", None, "", "" |
| return |
| name = os.path.splitext(os.path.basename(video_path))[0] |
| truth = _truth(name) |
| out_path = f"{RENDER_DIR}/{name}.mp4"; pose_path = f"{RENDER_DIR}/{name}_pose.png" |
| tr = _detect(video_path) |
| res = P.analyse(tr, video_path) |
| render(video_path, tr, res, out_path) |
| pose = pose_card_img(video_path, tr, res, pose_path) |
| table, speed = _table_html(res, truth), _speed_html(res) |
| |
| yield out_path, table, speed, pose, res.goal, _coach_loading_html() |
| |
| try: |
| text = C.get_coaching(C.build_payload(res), C.key_frames_b64(video_path, res)) |
| coach_html = _coach_html(text) |
| except C.CoachUnavailable: |
| coach_html = _coach_error_html() |
| yield out_path, table, speed, pose, res.goal, coach_html |
|
|
|
|
| with gr.Blocks(title="FUT World Cup Coach", css=CSS) as demo: |
| gr.Markdown( |
| "# ⚽ FUT World Cup Coach 🏆\n\n" |
| "Upload a football shot clip and it detects goal/no-goal (+ timestamp), who shot it, " |
| "their shooting foot, and shot speed using one small RF-DETR model, plus an NVIDIA " |
| "Nemotron vision-AI coach that grades your technique and tells you how to fix it. " |
| "All open, local models: the detector was distilled from SAM3 + NVIDIA LocateAnything " |
| "with zero manual labels. Built for the Build-Small Hackathon (World Cup 2026).", |
| elem_id="wc-head") |
| with gr.Row(): |
| with gr.Column(scale=0, min_width=42): |
| gr.Markdown(EDGE_STRIP) |
| with gr.Column(scale=1): |
| inp = gr.Video(label="Upload a shot clip", sources=["upload"], height=300) |
| btn = gr.Button("▶ Analyse", variant="primary") |
| gr.Markdown("#### Examples (held-out test clips)") |
| gr.Examples(examples=[[p] for p in EXAMPLES], inputs=inp, examples_per_page=12) |
| with gr.Column(scale=2): |
| out = gr.Video(label="Analysis", autoplay=True, height=420) |
| with gr.Row(): |
| table = gr.HTML() |
| speed = gr.HTML() |
| pose = gr.Image(label="Pose Detection", height=240) |
| coach = gr.HTML() |
| with gr.Column(scale=0, min_width=42): |
| gr.Markdown(EDGE_STRIP) |
| goal_flag = gr.Textbox(visible=False) |
| btn.click(analyse_clip, inp, [out, table, speed, pose, goal_flag, coach]).then( |
| None, goal_flag, None, js=CONFETTI_JS) |
| inp.change(analyse_clip, inp, [out, table, speed, pose, goal_flag, coach]).then( |
| None, goal_flag, None, js=CONFETTI_JS) |
|
|
| if __name__ == "__main__": |
| demo.launch(theme=gr.themes.Soft(primary_hue="emerald", secondary_hue="amber")) |
|
|
