JianMiauandClaude Fable 5
0ec645d1e0
根本原因： MindAR 以整張照片的特徵點做比對，同場地、同構圖的照片 （例如活動現場連拍）大部分特徵點落在共同背景（場地線條、 天花板、浮水印），會穩定地互相認錯、播出別張的影片。 調高 warmupTolerance 實測無效：錯誤目標是持續穩定匹配， 嚴格化只是更慢地確認錯的答案。 影響： 背景相似的多組照片無法在同一個特徵檔中正確區分。 修法： 1. 管理頁每組配對新增「框主體」：在照片上拖曳框選最有辨識度 的區域（相對座標存於 pairs.json，照片檔不動），編譯時只用 框內影像產生特徵。框的長寬下限 15%，實測框太小（僅臉部 特寫）會特徵點不足而完全偵測不到。 2. server 新增 PUT /api/pairs/:id/crop 儲存裁切框；更動後 自動標記「有變更尚未編譯」。 3. 掃描頁依 mapping 中的 aspect 與 crop 將影片平面放大平移， 辨識目標雖只是照片的一塊，影片仍精確覆蓋整張照片 （已用假相機截圖驗證幾何）。無裁切的舊資料行為不變。 已知限制：兩張照片若互相拍到彼此的主體（同兩人、同場地的 連拍），框選也無法完全區分——框內容本來就存在於另一張裡。 這種情況仍建議更換其中一張照片。 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
455 lines
18 KiB
HTML
455 lines
18 KiB
HTML
<!doctype html>
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<html lang="zh-Hant">
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<head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>動態相片管理</title>
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<style>
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:root { color-scheme: light dark; }
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* { box-sizing: border-box; }
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body {
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margin: 0; padding: 24px; font-family: system-ui, -apple-system, "Noto Sans TC", sans-serif;
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background: #f2f4f8; color: #1c2333;
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}
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@media (prefers-color-scheme: dark) {
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body { background: #0f1219; color: #e8ecf5; }
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.card { background: #1a1f2b !important; }
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th { color: #9aa4bd !important; }
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input[type="text"] { background: #0f1219; color: #e8ecf5; border-color: #333c50 !important; }
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}
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h1 { font-size: 22px; margin: 0 0 4px; }
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.sub { color: #6b7590; font-size: 14px; margin: 0 0 24px; }
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.card {
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background: #fff; border-radius: 12px; padding: 20px; margin-bottom: 20px;
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box-shadow: 0 1px 3px rgba(0,0,0,.08); max-width: 860px;
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}
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.card h2 { font-size: 16px; margin: 0 0 14px; }
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form { display: flex; flex-wrap: wrap; gap: 12px; align-items: end; }
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label { display: flex; flex-direction: column; gap: 6px; font-size: 13px; color: #6b7590; }
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input[type="text"] { padding: 8px 10px; border: 1px solid #d4dae6; border-radius: 8px; font-size: 14px; width: 180px; }
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input[type="file"] { font-size: 13px; max-width: 230px; }
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button {
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padding: 9px 20px; border: none; border-radius: 8px; font-size: 14px; font-weight: 600;
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cursor: pointer; background: #2b6cf5; color: #fff;
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}
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button:disabled { opacity: .5; cursor: default; }
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button.danger { background: transparent; color: #d33; padding: 4px 8px; font-weight: 400; }
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button.plain { background: transparent; color: #2b6cf5; padding: 4px 8px; font-weight: 400; }
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button.big { padding: 12px 28px; }
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table { width: 100%; border-collapse: collapse; font-size: 14px; }
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th { text-align: left; font-size: 12px; color: #6b7590; font-weight: 500; padding: 6px 8px; }
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td { padding: 8px; border-top: 1px solid rgba(128,128,128,.15); vertical-align: middle; }
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td img { width: 72px; height: 54px; object-fit: cover; border-radius: 6px; display: block; }
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.badge { display: inline-block; padding: 3px 10px; border-radius: 999px; font-size: 12px; font-weight: 600; }
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.badge.warn { background: #fff3d6; color: #8a6100; }
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.badge.ok { background: #d9f2e2; color: #12703c; }
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@media (prefers-color-scheme: dark) {
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.badge.warn { background: #443a14; color: #ffd45e; }
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.badge.ok { background: #10331f; color: #5fd68f; }
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}
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#msg { font-size: 14px; margin-top: 10px; min-height: 1.4em; }
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#msg.err { color: #d33; }
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.muted { color: #6b7590; font-size: 13px; }
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progress { width: 240px; }
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#cropModal {
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position: fixed; inset: 0; z-index: 100; display: flex;
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align-items: center; justify-content: center; padding: 20px;
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background: rgba(0, 0, 0, .55);
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}
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#cropModal[hidden] { display: none; }
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#cropPanel {
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background: #fff; border-radius: 12px; padding: 20px;
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max-width: 560px; max-height: 92vh; overflow: auto;
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}
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@media (prefers-color-scheme: dark) { #cropPanel { background: #1a1f2b; } }
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#cropPanel h2 { font-size: 16px; margin: 0 0 8px; }
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#cropStage {
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position: relative; display: inline-block; margin-top: 10px;
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touch-action: none; user-select: none; overflow: hidden; border-radius: 8px;
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}
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#cropImg { display: block; max-width: 100%; max-height: 58vh; }
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#cropRect {
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position: absolute; border: 2px solid #2b6cf5; pointer-events: none;
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box-shadow: 0 0 0 9999px rgba(0, 0, 0, .5);
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}
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#cropMsg { min-height: 1.4em; margin-top: 8px; }
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#cropMsg.err { color: #d33; }
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.cropBtns { display: flex; gap: 10px; justify-content: flex-end; margin-top: 12px; }
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</style>
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</head>
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<body>
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<h1>動態相片管理</h1>
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<p class="sub">照片＝key、影片＝value。新增或刪除配對後，記得按「重新編譯」產生辨識特徵檔。掃描頁：<a id="viewerLink" href="#">載入中…</a></p>
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<div class="card">
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<h2>新增配對</h2>
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<form id="addForm">
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<label>照片（jpg / png，上傳時自動壓縮）<input type="file" name="photo" accept=".jpg,.jpeg,.png" required></label>
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<label>影片（mp4 建議 H.264）<input type="file" name="video" accept=".mp4,.m4v,.mov,.webm" required></label>
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<button type="submit" id="addBtn">上傳</button>
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</form>
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<div id="msg"></div>
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</div>
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<div class="card">
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<h2>辨識特徵檔 <span id="compileBadge"></span></h2>
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<p class="muted">編譯在你目前的瀏覽器執行（建議用桌機，每張照片約 10～30 秒），完成後自動上傳到伺服器。</p>
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<button id="compileBtn" class="big">重新編譯全部照片</button>
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<span id="compileStatus" class="muted" style="margin-left:12px"></span>
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<div><progress id="compileProgress" max="100" value="0" hidden></progress></div>
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</div>
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<div class="card">
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<h2>已登錄配對（<span id="count">0</span>）</h2>
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<table>
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<thead><tr><th>照片</th><th>名稱</th><th>影片</th><th>建立時間</th><th></th></tr></thead>
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<tbody id="rows"></tbody>
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</table>
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</div>
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<div id="cropModal" hidden>
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<div id="cropPanel">
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<h2>框選辨識主體</h2>
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<p class="muted" style="margin:0">
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在照片上拖曳，框出最有辨識度的區域（例如人物）。背景相似的多張照片各自框選主體後，
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掃描就不會互相認錯；影片播放時仍會覆蓋整張照片。
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框的長寬至少要佔照片 15%，框太小特徵點不足反而難辨識。改完記得重新編譯。
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</p>
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<div id="cropStage"><img id="cropImg" draggable="false"><div id="cropRect" hidden></div></div>
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<div id="cropMsg" class="muted"></div>
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<div class="cropBtns">
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<button type="button" id="cropClear" class="danger">清除（用整張照片）</button>
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<button type="button" id="cropCancel" style="background:#6b7590">取消</button>
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<button type="button" id="cropSave">儲存</button>
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</div>
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</div>
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</div>
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<script>
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let state = null;
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async function refresh() {
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state = await (await fetch('/api/state')).json();
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document.getElementById('count').textContent = state.pairs.length;
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const viewerUrl = `https://${location.hostname}:${state.ports.viewer}/`;
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const viewerLink = document.getElementById('viewerLink');
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viewerLink.href = viewerUrl;
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viewerLink.textContent = viewerUrl;
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const badge = document.getElementById('compileBadge');
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if (state.needsCompile) {
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badge.className = 'badge warn';
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badge.textContent = '有變更尚未編譯';
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} else if (state.targets && state.targets.targets.length) {
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badge.className = 'badge ok';
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badge.textContent = '已是最新（' + new Date(state.targets.compiledAt).toLocaleString() + '）';
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} else {
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badge.className = 'badge warn';
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badge.textContent = '尚未編譯';
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}
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const tbody = document.getElementById('rows');
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tbody.textContent = '';
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for (const p of state.pairs) {
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const tr = document.createElement('tr');
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const tdImg = document.createElement('td');
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const img = document.createElement('img');
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img.src = '/data/photos/' + encodeURIComponent(p.photo);
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tdImg.appendChild(img);
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const tdName = document.createElement('td');
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tdName.textContent = p.name;
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const tdVideo = document.createElement('td');
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const a = document.createElement('a');
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a.href = '/data/videos/' + encodeURIComponent(p.video);
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a.target = '_blank';
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a.textContent = p.video;
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tdVideo.appendChild(a);
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const tdTime = document.createElement('td');
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tdTime.className = 'muted';
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tdTime.textContent = new Date(p.createdAt).toLocaleString();
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const tdDel = document.createElement('td');
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const cropBtn = document.createElement('button');
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cropBtn.className = 'plain';
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cropBtn.textContent = p.crop ? '主體✓' : '框主體';
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cropBtn.title = '框選辨識主體（背景相似的照片才不會互相認錯）';
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cropBtn.onclick = () => openCropModal(p);
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tdDel.appendChild(cropBtn);
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const del = document.createElement('button');
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del.className = 'danger';
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del.textContent = '刪除';
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del.onclick = async () => {
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if (!confirm('確定刪除「' + p.name + '」？照片與影片檔案將一併移除。')) return;
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await fetch('/api/pairs/' + p.id, { method: 'DELETE' });
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refresh();
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};
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tdDel.appendChild(del);
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tr.append(tdImg, tdName, tdVideo, tdTime, tdDel);
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tbody.appendChild(tr);
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}
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}
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// 照片統一縮到這個長邊尺寸：對 MindAR 特徵品質足夠，
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// 且掃描端（尤其 iOS Safari）的 WebGL 記憶體撐得住
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const MAX_EDGE = 1280;
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// ---- 框選辨識主體（裁切框只影響編譯輸入，照片檔不動）----
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const cropModal = document.getElementById('cropModal');
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const cropStage = document.getElementById('cropStage');
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const cropImg = document.getElementById('cropImg');
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const cropRect = document.getElementById('cropRect');
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const cropMsg = document.getElementById('cropMsg');
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const CROP_MIN = 0.15; // 框的長寬至少要佔照片的比例
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let cropPair = null;
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let cropRel = null; // {x,y,w,h} 相對座標，null = 整張照片
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function openCropModal(pair) {
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cropPair = pair;
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cropRel = pair.crop ? { ...pair.crop } : null;
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cropMsg.className = 'muted';
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cropMsg.textContent = '';
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cropImg.src = '/data/photos/' + encodeURIComponent(pair.photo) + '?t=' + pair.createdAt;
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cropModal.hidden = false;
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if (cropImg.complete) renderCropRect();
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else cropImg.onload = renderCropRect;
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}
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function renderCropRect() {
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if (!cropRel) {
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cropRect.hidden = true;
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return;
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}
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cropRect.hidden = false;
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cropRect.style.left = cropRel.x * cropImg.clientWidth + 'px';
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cropRect.style.top = cropRel.y * cropImg.clientHeight + 'px';
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cropRect.style.width = cropRel.w * cropImg.clientWidth + 'px';
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cropRect.style.height = cropRel.h * cropImg.clientHeight + 'px';
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}
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// 拖曳畫框（pointer events 同時支援滑鼠與觸控）
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let dragStart = null;
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function pointToRel(e) {
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const r = cropImg.getBoundingClientRect();
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return {
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x: Math.min(1, Math.max(0, (e.clientX - r.left) / r.width)),
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y: Math.min(1, Math.max(0, (e.clientY - r.top) / r.height)),
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};
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}
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cropStage.addEventListener('pointerdown', (e) => {
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e.preventDefault();
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cropStage.setPointerCapture(e.pointerId);
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dragStart = pointToRel(e);
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});
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cropStage.addEventListener('pointermove', (e) => {
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if (!dragStart) return;
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const p = pointToRel(e);
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cropRel = {
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x: Math.min(dragStart.x, p.x),
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y: Math.min(dragStart.y, p.y),
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w: Math.abs(p.x - dragStart.x),
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h: Math.abs(p.y - dragStart.y),
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};
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renderCropRect();
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});
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cropStage.addEventListener('pointerup', () => { dragStart = null; });
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window.addEventListener('resize', () => {
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if (!cropModal.hidden) renderCropRect();
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});
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document.getElementById('cropClear').onclick = () => {
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cropRel = null;
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renderCropRect();
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cropMsg.className = 'muted';
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cropMsg.textContent = '已清除，按「儲存」後會改用整張照片。';
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};
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document.getElementById('cropCancel').onclick = () => { cropModal.hidden = true; };
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document.getElementById('cropSave').onclick = async () => {
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if (cropRel && (cropRel.w < CROP_MIN || cropRel.h < CROP_MIN)) {
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cropMsg.className = 'err';
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cropMsg.textContent = `框太小了：長寬都要至少佔照片 ${CROP_MIN * 100}%，不然特徵點不足難以辨識。`;
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return;
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}
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try {
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const res = await fetch('/api/pairs/' + cropPair.id + '/crop', {
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method: 'PUT',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({ crop: cropRel }),
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});
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const json = await res.json();
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if (!res.ok) throw new Error(json.error || res.statusText);
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cropModal.hidden = true;
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refresh();
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} catch (err) {
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cropMsg.className = 'err';
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cropMsg.textContent = '儲存失敗：' + err.message;
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}
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};
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function loadImageFromFile(file) {
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return new Promise((resolve, reject) => {
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const url = URL.createObjectURL(file);
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const img = new Image();
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img.onload = () => { URL.revokeObjectURL(url); resolve(img); };
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img.onerror = () => { URL.revokeObjectURL(url); reject(new Error('照片檔案無法讀取')); };
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img.src = url;
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});
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}
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// 上傳前先在瀏覽器縮圖壓縮（長邊 MAX_EDGE、JPEG 90%），
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// 伺服器不需裝任何影像處理套件。canvas 重新編碼時
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// 瀏覽器會把 EXIF 方向烘進像素，直式照片不會轉向
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async function optimizePhoto(file) {
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const img = await loadImageFromFile(file);
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const scale = Math.min(1, MAX_EDGE / Math.max(img.naturalWidth, img.naturalHeight));
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if (scale === 1) return file;
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const c = document.createElement('canvas');
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c.width = Math.round(img.naturalWidth * scale);
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c.height = Math.round(img.naturalHeight * scale);
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c.getContext('2d').drawImage(img, 0, 0, c.width, c.height);
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const blob = await new Promise((r) => c.toBlob(r, 'image/jpeg', 0.9));
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if (!blob) throw new Error('照片壓縮失敗');
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return new File([blob], file.name.replace(/\.\w+$/, '') + '.jpg', { type: 'image/jpeg' });
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}
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document.getElementById('addForm').addEventListener('submit', async (e) => {
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e.preventDefault();
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const btn = document.getElementById('addBtn');
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const msg = document.getElementById('msg');
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btn.disabled = true;
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msg.className = '';
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try {
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const rawPhoto = e.target.photo.files[0];
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msg.textContent = '照片壓縮中…';
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const photo = await optimizePhoto(rawPhoto);
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const mb = (n) => (n / 1024 / 1024).toFixed(1) + 'MB';
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msg.textContent = photo === rawPhoto
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? '上傳中…'
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: `上傳中…（照片 ${mb(rawPhoto.size)} → ${mb(photo.size)}）`;
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const fd = new FormData();
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fd.append('photo', photo, photo.name);
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fd.append('video', e.target.video.files[0]);
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const res = await fetch('/api/pairs', { method: 'POST', body: fd });
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const json = await res.json();
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if (!res.ok) throw new Error(json.error || res.statusText);
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msg.textContent = '已新增，請記得重新編譯。';
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e.target.reset();
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refresh();
|
||
} catch (err) {
|
||
msg.className = 'err';
|
||
msg.textContent = '上傳失敗：' + err.message;
|
||
} finally {
|
||
btn.disabled = false;
|
||
}
|
||
});
|
||
|
||
function loadImage(url) {
|
||
return new Promise((resolve, reject) => {
|
||
const img = new Image();
|
||
img.onload = () => resolve(img);
|
||
img.onerror = () => reject(new Error('讀取照片失敗：' + url));
|
||
img.src = url;
|
||
});
|
||
}
|
||
|
||
let compilerLoaded = false;
|
||
function loadCompilerScript() {
|
||
if (compilerLoaded) return Promise.resolve();
|
||
return new Promise((resolve, reject) => {
|
||
const s = document.createElement('script');
|
||
s.type = 'module'; // mind-ar 編譯器是 ES module，會自行掛上 window.MINDAR
|
||
s.src = '/vendor/mindar-image.prod.js';
|
||
s.onload = () => { compilerLoaded = true; resolve(); };
|
||
s.onerror = () => reject(new Error('無法載入 MindAR 編譯器'));
|
||
document.head.appendChild(s);
|
||
});
|
||
}
|
||
|
||
document.getElementById('compileBtn').addEventListener('click', async () => {
|
||
const btn = document.getElementById('compileBtn');
|
||
const status = document.getElementById('compileStatus');
|
||
const bar = document.getElementById('compileProgress');
|
||
if (!state || !state.pairs.length) {
|
||
status.textContent = '沒有任何配對可編譯。';
|
||
return;
|
||
}
|
||
btn.disabled = true;
|
||
bar.hidden = false;
|
||
bar.value = 0;
|
||
try {
|
||
status.textContent = '載入編譯器…';
|
||
await loadCompilerScript();
|
||
|
||
status.textContent = '載入照片…';
|
||
const pairs = state.pairs;
|
||
const images = await Promise.all(
|
||
pairs.map((p) => loadImage('/data/photos/' + encodeURIComponent(p.photo)))
|
||
);
|
||
|
||
// 有框選主體的配對只用框內區域編譯（背景相似的照片才不會互相認錯）。
|
||
// 大圖先縮到長邊 MAX_EDGE 再編譯（雙保險：新上傳的照片已在上傳時縮圖，
|
||
// 這裡再保護縮圖修正前上傳的舊照片）。
|
||
// 曾發生 4 張 2244x4131 原圖直接編譯後，iPhone 掃任何照片都沒反應
|
||
// （桌面 Chrome 正常，iOS WebGL 資源上限較低，辨識引擎無聲掛掉）
|
||
const compileInputs = images.map((img, i) => {
|
||
const crop = pairs[i].crop;
|
||
const sx = crop ? crop.x * img.naturalWidth : 0;
|
||
const sy = crop ? crop.y * img.naturalHeight : 0;
|
||
const sw = crop ? crop.w * img.naturalWidth : img.naturalWidth;
|
||
const sh = crop ? crop.h * img.naturalHeight : img.naturalHeight;
|
||
const scale = Math.min(1, MAX_EDGE / Math.max(sw, sh));
|
||
if (scale === 1 && !crop) return img;
|
||
const c = document.createElement('canvas');
|
||
c.width = Math.round(sw * scale);
|
||
c.height = Math.round(sh * scale);
|
||
c.getContext('2d').drawImage(img, sx, sy, sw, sh, 0, 0, c.width, c.height);
|
||
return c;
|
||
});
|
||
|
||
status.textContent = '編譯特徵中（勿關閉頁面）…';
|
||
const compiler = new window.MINDAR.IMAGE.Compiler();
|
||
await compiler.compileImageTargets(compileInputs, (progress) => {
|
||
bar.value = progress;
|
||
status.textContent = '編譯特徵中 ' + progress.toFixed(0) + '%（勿關閉頁面）…';
|
||
});
|
||
const buffer = await compiler.exportData();
|
||
|
||
status.textContent = '上傳特徵檔…';
|
||
// aspect 一律是整張照片的長寬比；有裁切時另外附上裁切框，
|
||
// 掃描頁靠這兩個值把影片平面校正回「覆蓋整張照片」
|
||
const mapping = {
|
||
targets: pairs.map((p, i) => ({
|
||
pairId: p.id,
|
||
aspect: images[i].naturalHeight / images[i].naturalWidth,
|
||
crop: p.crop || undefined,
|
||
})),
|
||
};
|
||
const fd = new FormData();
|
||
fd.append('mapping', JSON.stringify(mapping));
|
||
fd.append('mind', new Blob([buffer]), 'targets.mind');
|
||
const res = await fetch('/api/targets', { method: 'POST', body: fd });
|
||
const json = await res.json();
|
||
if (!res.ok) throw new Error(json.error || res.statusText);
|
||
|
||
status.textContent = '編譯完成！';
|
||
refresh();
|
||
} catch (err) {
|
||
status.textContent = '編譯失敗：' + err.message;
|
||
} finally {
|
||
btn.disabled = false;
|
||
bar.hidden = true;
|
||
}
|
||
});
|
||
|
||
refresh();
|
||
</script>
|
||
</body>
|
||
</html>
|