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<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8" />
<title>SAM 3 Auto Selection</title>
<script src="https://cdn.jsdelivr.net/npm/onnxruntime-web/dist/ort.min.js"></script>
<link rel="stylesheet" href="css/web.css" />
</head>
<body>
<div class="app-root">
<header>
<div class="logo">
<img src="icon/icon.png" alt="Logo" class="logo-icon" />
<span>SAM 3 <span class="accent">Auto Selection</span></span>
</div>
<div class="toolbar">
<div class="inputs-row">
<div>
<div class="field-label">后端模型地址</div>
<div class="server-input-wrapper">
<input
id="serverInput"
type="text"
value="http://localhost:8000"
spellcheck="false"
/>
<span id="serverStatus" class="status-dot offline"></span>
</div>
</div>
<div>
<div class="field-label">Sam3 模型地址</div>
<input
id="modelPathInput"
type="text"
value="D:/HF_DATA/sam3"
spellcheck="false"
placeholder="SAM 模型路径，例如 D:/HF_DATA/sam3"
/>
</div>
</div>
</div>
<div>
<button id="uploadButton">上传图片</button>
<button id="retryPrecomputeButton" disabled>重试预处理</button>
<input id="fileInput" type="file" accept="image/*" />
</div>
</header>
<main>
<div class="canvas-container" id="canvasContainer">
<div class="placeholder" id="placeholder">
<div class="hand">🖱️</div>
<div class="placeholder-text">UPLOAD TO START</div>
</div>
<div class="canvas-wrapper hidden" id="canvasWrapper">
<img id="baseImage" alt="Base" />
<img id="overlayImage" alt="" />
<img id="fixedOverlay" alt="" />
</div>
</div>
<aside class="side-panel">
<div class="panel-title">Mode</div>
<div class="mode-group">
<button class="mode-button active" id="modeHover" data-mode="hover">悬停选取</button>
<button class="mode-button" id="modeClick" data-mode="click">点击分割</button>
<button class="mode-button" id="modeText" data-mode="text">文字分割</button>
</div>
<div id="textControls" class="hidden">
<div class="field-label" style="margin-top: 8px">文本提示（英文逗号分隔）</div>
<textarea id="promptInput" placeholder="例如: car, wheel"></textarea>
<button id="runTextButton">运行文字分割</button>
</div>
<div>
<div class="field-label" style="margin-top: 8px">状态</div>
<div id="status">等待上传图片...</div>
</div>
</aside>
</main>
<div id="loadingOverlay" class="loading-overlay">
<div class="loading-content">
<img src="icon/icon.png" alt="Loading" class="loading-icon" />
<div class="loading-text">正在上传并处理图片...</div>
</div>
</div>
</div>
<script>
const serverInput = document.getElementById("serverInput");
const serverStatus = document.getElementById("serverStatus");
const modelPathInput = document.getElementById("modelPathInput");
const uploadButton = document.getElementById("uploadButton");
const retryPrecomputeButton = document.getElementById("retryPrecomputeButton");
const fileInput = document.getElementById("fileInput");
const baseImage = document.getElementById("baseImage");
const overlayImage = document.getElementById("overlayImage");
const fixedOverlay = document.getElementById("fixedOverlay");
const placeholder = document.getElementById("placeholder");
const canvasWrapper = document.getElementById("canvasWrapper");
const statusEl = document.getElementById("status");
const modeButtons = document.querySelectorAll(".mode-button");
const promptInput = document.getElementById("promptInput");
const runTextButton = document.getElementById("runTextButton");
const textControls = document.getElementById("textControls");
const loadingOverlay = document.getElementById("loadingOverlay");
const loadingText = loadingOverlay.querySelector(".loading-text");
let imageId = null;
let lastRequestId = 0;
let currentMode = "hover";
let lastHoverX = null;
let lastHoverY = null;
let hoverInFlight = false;
const HOVER_MIN_DISTANCE = 10;
// ONNX 悬停相关状态
let decoderSession = null;
let emb0 = null, emb1 = null, emb2 = null;
let shape0 = null, shape1 = null, shape2 = null;
let onnxReady = false;
let origH = null;
let origW = null;
let decoderTargetSize = 1024;
let hoverUseOnnx = false;
let lastImageDataUrl = null;
function apiBase() {
return serverInput.value.replace(/\/+$/, "");
}
function setServerOnline(online) {
serverStatus.classList.toggle("online", online);
serverStatus.classList.toggle("offline", !online);
}
function setLoading(isLoading, text) {
if (isLoading) {
loadingText.textContent = text || "正在上传并处理图片...";
loadingOverlay.classList.add("visible");
} else {
loadingOverlay.classList.remove("visible");
}
}
function clearOverlay() {
overlayImage.src = "";
overlayImage.style.display = "none";
fixedOverlay.src = "";
fixedOverlay.style.display = "none";
}
function flatten(arr) {
return arr.flat(Infinity);
}
async function ensureDecoderSession() {
if (decoderSession) return;
const url = `${apiBase()}/sam3_decoder.onnx`;
statusEl.textContent = "正在下载 ONNX 模型...";
decoderSession = await ort.InferenceSession.create(url);
statusEl.textContent = "ONNX 模型加载完成。";
}
async function decodePointONNX(normPoints, normLabels) {
if (!decoderSession || !onnxReady || !emb0) return null;
const pts = new Float32Array(flatten(normPoints));
const labelsFlat = flatten(normLabels).map((v) => BigInt(v));
const lbl = new BigInt64Array(labelsFlat);
const feeds = {};
for (const inp of decoderSession.inputNames) {
if (inp === "image_embedding_s0") {
feeds[inp] = new ort.Tensor("float32", emb0, shape0);
} else if (inp === "image_embedding_s1") {
feeds[inp] = new ort.Tensor("float32", emb1, shape1);
} else if (inp === "image_embedding_s2") {
feeds[inp] = new ort.Tensor("float32", emb2, shape2);
} else if (inp === "input_points") {
feeds[inp] = new ort.Tensor("float32", pts, [normPoints.length, normPoints[0].length, normPoints[0][0].length, 2]);
} else if (inp === "input_labels") {
feeds[inp] = new ort.Tensor("int64", lbl, [normLabels.length, normLabels[0].length, normLabels[0][0].length]);
}
}
const outputs = await decoderSession.run(feeds);
return outputs;
}
uploadButton.addEventListener("click", () => fileInput.click());
async function processImageDataUrl(dataUrl) {
lastImageDataUrl = dataUrl;
baseImage.src = dataUrl;
clearOverlay();
placeholder.classList.add("hidden");
canvasWrapper.classList.remove("hidden");
statusEl.textContent = "正在上传图片并预处理悬停特征...";
setLoading(true, "正在上传并预处理图片，请稍候...");
retryPrecomputeButton.disabled = true;
try {
const res = await fetch(`${apiBase()}/set_image`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
image_data: dataUrl,
model_path: modelPathInput.value.trim() || null,
}),
});
if (!res.ok) throw new Error(await res.text());
const json = await res.json();
imageId = json.image_id;
setServerOnline(true);
emb0 = emb1 = emb2 = null;
shape0 = shape1 = shape2 = null;
onnxReady = false;
hoverUseOnnx = false;
origH = null;
origW = null;
decoderTargetSize = 1024;
statusEl.textContent = "图片已上传，正在预处理悬停特征...";
await ensureDecoderSession();
const embRes = await fetch(`${apiBase()}/get_embeddings`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ image_id: imageId }),
});
if (!embRes.ok) throw new Error(await embRes.text());
const embJson = await embRes.json();
const [e0, e1, e2] = embJson.embeddings;
if (Array.isArray(embJson.original_sizes) && embJson.original_sizes.length > 0) {
const sz = embJson.original_sizes[0];
if (Array.isArray(sz) && sz.length >= 2) {
origH = sz[0];
origW = sz[1];
}
} else if (baseImage.naturalWidth && baseImage.naturalHeight) {
origH = baseImage.naturalHeight;
origW = baseImage.naturalWidth;
}
if (typeof embJson.target_size === "number" && embJson.target_size > 0) {
decoderTargetSize = embJson.target_size;
}
shape0 = [e0.length, e0[0].length, e0[0][0].length, e0[0][0][0].length];
shape1 = [e1.length, e1[0].length, e1[0][0].length, e1[0][0][0].length];
shape2 = [e2.length, e2[0].length, e2[0][0].length, e2[0][0][0].length];
emb0 = new Float32Array(flatten(e0));
emb1 = new Float32Array(flatten(e1));
emb2 = new Float32Array(flatten(e2));
onnxReady = true;
hoverUseOnnx = true;
statusEl.textContent = "图片上传并预处理完成，可以开始悬停选取。";
} catch (err) {
console.error(err);
setServerOnline(false);
statusEl.textContent = "上传或预处理失败，请检查后端地址、模型路径和 sam3_decoder.onnx。";
retryPrecomputeButton.disabled = !lastImageDataUrl;
} finally {
setLoading(false);
}
}
fileInput.addEventListener("change", async (event) => {
const file = event.target.files[0];
if (!file) return;
const reader = new FileReader();
reader.onload = async (e) => await processImageDataUrl(e.target.result);
reader.readAsDataURL(file);
});
retryPrecomputeButton.addEventListener("click", async () => {
if (!lastImageDataUrl) return;
await processImageDataUrl(lastImageDataUrl);
});
function getRelativeCoords(event) {
const rect = baseImage.getBoundingClientRect();
const naturalW = baseImage.naturalWidth;
const naturalH = baseImage.naturalHeight;
if (!naturalW || !naturalH) return { x: 0, y: 0 };
const scale = Math.min(rect.width / naturalW, rect.height / naturalH);
const displayW = naturalW * scale;
const displayH = naturalH * scale;
const offsetX = (rect.width - displayW) / 2;
const offsetY = (rect.height - displayH) / 2;
let x = event.clientX - rect.left - offsetX;
let y = event.clientY - rect.top - offsetY;
x = Math.max(0, Math.min(displayW, x));
y = Math.max(0, Math.min(displayH, y));
const origX = x / scale;
const origY = y / scale;
return { x: Math.round(origX), y: Math.round(origY) };
}
baseImage.addEventListener("mousemove", (event) => {
if (currentMode !== "hover") return;
if (!imageId) return;
if (!baseImage.naturalWidth || !baseImage.naturalHeight) return;
if (!onnxReady || !hoverUseOnnx) return;
const coords = getRelativeCoords(event);
if (lastHoverX !== null && lastHoverY !== null) {
const dx = coords.x - lastHoverX;
const dy = coords.y - lastHoverY;
const dist = Math.hypot(dx, dy);
if (dist < HOVER_MIN_DISTANCE) return;
}
lastHoverX = coords.x;
lastHoverY = coords.y;
handleHoverOnnx(coords.x, coords.y);
});
baseImage.addEventListener("click", (event) => {
if (!imageId) return;
const coords = getRelativeCoords(event);
if (currentMode === "click") {
requestSegmentPoint(coords.x, coords.y);
return;
}
if (currentMode === "hover") {
if (!overlayImage.src) return;
const fullW = baseImage.naturalWidth || overlayImage.naturalWidth;
const fullH = baseImage.naturalHeight || overlayImage.naturalHeight;
if (!fullW || !fullH) return;
const fixedCanvas = document.createElement("canvas");
fixedCanvas.width = fullW;
fixedCanvas.height = fullH;
const ctx = fixedCanvas.getContext("2d");
ctx.drawImage(overlayImage, 0, 0, fullW, fullH);
const imgData = ctx.getImageData(0, 0, fullW, fullH);
const data = imgData.data;
const size = fullW * fullH;
// 客户端固定逻辑：这里直接复制 Canvas 像素即可，因为现在 Hover 的视觉效果已经是最终效果
ctx.putImageData(imgData, 0, 0);
fixedOverlay.src = fixedCanvas.toDataURL("image/png");
fixedOverlay.style.display = "block";
overlayImage.src = "";
overlayImage.style.display = "none";
statusEl.textContent = `已固定选区，坐标 (${coords.x}, ${coords.y})`;
}
});
// -------------------------------------------------------------
// 前端图像处理算法库
// -------------------------------------------------------------
function keepLargestComponent(mask, w, h) {
const labels = new Int32Array(w * h).fill(0);
let currentLabel = 1;
const componentSizes = new Map();
// BFS 找连通域
for (let i = 0; i < w * h; i++) {
if (mask[i] && labels[i] === 0) {
let count = 0;
const queue = [i];
labels[i] = currentLabel;
let head = 0;
while(head < queue.length) {
const idx = queue[head++];
count++;
const x = idx % w;
const y = Math.floor(idx / w);
const neighbors = [];
if (y > 0) neighbors.push(idx - w);
if (y < h - 1) neighbors.push(idx + w);
if (x > 0) neighbors.push(idx - 1);
if (x < w - 1) neighbors.push(idx + 1);
for (const n_idx of neighbors) {
if (mask[n_idx] && labels[n_idx] === 0) {
labels[n_idx] = currentLabel;
queue.push(n_idx);
}
}
}
componentSizes.set(currentLabel, count);
currentLabel++;
}
}
let maxLabel = -1;
let maxSize = 0;
for (const [lbl, size] of componentSizes) {
if (size > maxSize) { maxSize = size; maxLabel = lbl; }
}
const result = new Uint8Array(w * h);
if (maxLabel !== -1) {
for (let i = 0; i < w * h; i++) {
if (labels[i] === maxLabel) result[i] = 1;
}
}
return result;
}
// FloodFill 填洞：从四边的背景灌水，灌不到的背景就是被前景包围的内部空洞，填为前景。
// 只填【完全封闭】的洞，不影响外轮廓的凹凸结构。
function fillHoles(mask, w, h) {
const floodMap = new Int32Array(w * h);
const queue = [];
for (let x = 0; x < w; x++) {
if (mask[0 * w + x] === 0) { floodMap[0 * w + x] = 2; queue.push(0 * w + x); }
if (mask[(h - 1) * w + x] === 0) { floodMap[(h - 1) * w + x] = 2; queue.push((h - 1) * w + x); }
}
for (let y = 1; y < h - 1; y++) {
if (mask[y * w + 0] === 0) { floodMap[y * w + 0] = 2; queue.push(y * w + 0); }
if (mask[y * w + (w - 1)] === 0) { floodMap[y * w + (w - 1)] = 2; queue.push(y * w + (w - 1)); }
}
let head = 0;
while(head < queue.length) {
const idx = queue[head++];
const x = idx % w;
const y = Math.floor(idx / w);
const neighbors = [];
if (y > 0) neighbors.push(idx - w);
if (y < h - 1) neighbors.push(idx + w);
if (x > 0) neighbors.push(idx - 1);
if (x < w - 1) neighbors.push(idx + 1);
for (const n_idx of neighbors) {
if (mask[n_idx] === 0 && floodMap[n_idx] === 0) {
floodMap[n_idx] = 2;
queue.push(n_idx);
}
}
}
const result = new Uint8Array(w * h);
for (let i = 0; i < w * h; i++) {
if (mask[i] === 1 || floodMap[i] === 0) {
result[i] = 1;
}
}
return result;
}
// 形态学膨胀（方形核，可分离：先水平后垂直；滑动计数 O(n)，不受半径影响）
function dilateMask(mask, w, h, r) {
if (r <= 0) return mask;
const tmp = new Uint8Array(w * h);
for (let y = 0; y < h; y++) {
const row = y * w;
let count = 0;
for (let x = 0; x <= r && x < w; x++) count += mask[row + x];
for (let x = 0; x < w; x++) {
tmp[row + x] = count > 0 ? 1 : 0;
const out = x - r, add = x + r + 1;
if (out >= 0) count -= mask[row + out];
if (add < w) count += mask[row + add];
}
}
const res = new Uint8Array(w * h);
for (let x = 0; x < w; x++) {
let count = 0;
for (let y = 0; y <= r && y < h; y++) count += tmp[y * w + x];
for (let y = 0; y < h; y++) {
res[y * w + x] = count > 0 ? 1 : 0;
const out = y - r, add = y + r + 1;
if (out >= 0) count -= tmp[out * w + x];
if (add < h) count += tmp[add * w + x];
}
}
return res;
}
// 形态学闭运算 = 先膨胀后腐蚀；腐蚀用 De Morgan：erode(M) = ¬dilate(¬M)。
// 作用：填平小缺口/凹槽、桥接细微断裂（如整车选区里漏掉的一小块轮胎），整体大小基本不变。
function closeMask(mask, w, h, r) {
if (r <= 0) return mask;
const dil = dilateMask(mask, w, h, r);
const inv = new Uint8Array(w * h);
for (let i = 0; i < w * h; i++) inv[i] = dil[i] ? 0 : 1;
const invDil = dilateMask(inv, w, h, r);
const res = new Uint8Array(w * h);
for (let i = 0; i < w * h; i++) res[i] = invDil[i] ? 0 : 1;
return res;
}
function bilinearUpscale(srcData, srcW, srcH, dstW, dstH) {
const dstData = new Float32Array(dstW * dstH);
const xRatio = srcW / dstW;
const yRatio = srcH / dstH;
for (let y = 0; y < dstH; y++) {
for (let x = 0; x < dstW; x++) {
const srcX = x * xRatio;
const srcY = y * yRatio;
const x0 = Math.floor(srcX);
const y0 = Math.floor(srcY);
const x1 = Math.min(x0 + 1, srcW - 1);
const y1 = Math.min(y0 + 1, srcH - 1);
const dx = srcX - x0;
const dy = srcY - y0;
const idx00 = y0 * srcW + x0;
const idx10 = y0 * srcW + x1;
const idx01 = y1 * srcW + x0;
const idx11 = y1 * srcW + x1;
const val00 = srcData[idx00];
const val10 = srcData[idx10];
const val01 = srcData[idx01];
const val11 = srcData[idx11];
const valTop = val00 * (1 - dx) + val10 * dx;
const valBot = val01 * (1 - dx) + val11 * dx;
const val = valTop * (1 - dy) + valBot * dy;
dstData[y * dstW + x] = val;
}
}
return dstData;
}
async function handleHoverOnnx(x, y) {
if (!imageId) return;
if (hoverInFlight) return;
if (!onnxReady || !emb0 || !emb1 || !emb2) return;
if (!origH || !origW || !decoderTargetSize) return;
hoverInFlight = true;
try {
const sx = decoderTargetSize / origW;
const sy = decoderTargetSize / origH;
const nx = x * sx;
const ny = y * sy;
const normPoints = [[[[nx, ny]]]];
const normLabels = [[[1]]];
const out = await decodePointONNX(normPoints, normLabels);
if (!out || !out["pred_masks"]) {
hoverInFlight = false;
return;
}
const predMasks = out["pred_masks"]; // [1, 1, numMasks, H, W]（低分辨率 logits）
const iouScores = out["iou_scores"]; // [1, 1, numMasks]
const numMasks = predMasks.dims[2];
const srcH = predMasks.dims[3]; // 解码器输出分辨率（动态读取，当前模型约 288）
const srcW = predMasks.dims[4];
// 多候选 mask 中按 IoU 选最优：通常是“整体物体”那个 → 选区完整，
// 且在物体内各点之间一致 → 悬停时自然稳定（参考工具的手感来源）。
let bestIdx = 0;
if (iouScores && iouScores.data && iouScores.data.length >= numMasks) {
let bestScore = -Infinity;
for (let m = 0; m < numMasks; m++) {
if (iouScores.data[m] > bestScore) {
bestScore = iouScores.data[m];
bestIdx = m;
}
}
}
const planeSize = srcH * srcW;
// 取出最优 mask 这一层的 logits（subarray 是视图，零拷贝）
const srcData = predMasks.data.subarray(bestIdx * planeSize, (bestIdx + 1) * planeSize);
// --- 处理流水线 (v11: 完整对齐后端 post_process_masks，在显示分辨率上做) ---
// 顺序与后端 segment_point 完全一致：
// 先把 256 的【原始 logits】双线性上采样到显示分辨率，再阈值 → 平滑边界；
// 然后在高分辨率上做「最大连通域」去噪 + 「FloodFill 填洞」 → 实心干净的 mask。
// 关键：不再用 -10 硬砍连通域外的 logit（那会让边界按 256 网格阶梯化、产生锯齿）。
// 1. 计算显示分辨率
const maxDim = 1024;
const imgAspect = (baseImage.naturalWidth || srcW) / (baseImage.naturalHeight || srcH);
let dstW, dstH;
if (imgAspect > 1) {
dstW = maxDim;
dstH = Math.round(maxDim / imgAspect);
} else {
dstH = maxDim;
dstW = Math.round(maxDim * imgAspect);
}
// 2. 上采样【原始 logits】（不做任何硬填），阈值得到平滑边界
const highResLogits = bilinearUpscale(srcData, srcW, srcH, dstW, dstH);
let highResMask = new Uint8Array(dstW * dstH);
for (let i = 0; i < dstW * dstH; i++) {
highResMask[i] = highResLogits[i] > 0.0 ? 1 : 0;
}
// 3. 闭运算：补回整体选区里漏掉的小块、桥接细微断裂（如整车里漏选的一小段轮胎）。
// 放在「最大连通域」之前，好让近乎断开的小块先被桥接回主体、不被当噪点丢掉。
// 半径越大越能「封住」深凹口的口子（封住后第 4 步 fillHoles 就能把整条深槽填满），
// 代价是尖角会更圆。dilateMask 是 O(n)，调大半径不增加计算量。
// —— 这是补全选区凹口的【唯一旋钮】：还漏就调大（如 /100），凹口被过度填平就调小。
// 注意：闭运算是扩张型运算，只填凹陷、不磨凸出尖角，所以放心加大。
const closeR = Math.max(3, Math.round(dstW / 140));
highResMask = closeMask(highResMask, dstW, dstH, closeR);
// 4. 高分辨率去噪 + 填洞（对应后端 connectedComponents + floodFill）
highResMask = keepLargestComponent(highResMask, dstW, dstH);
highResMask = fillHoles(highResMask, dstW, dstH);
// 5. 准备渲染缓冲
const imgData = new ImageData(dstW, dstH);
const pixels = imgData.data;
// 6. 渲染
for (let y = 0; y < dstH; y++) {
for (let x = 0; x < dstW; x++) {
const idx = y * dstW + x;
if (highResMask[idx] === 1) {
const pIdx = idx * 4;
// 简单的 4 邻域边缘检测
let isBorder = false;
if (x === 0 || x === dstW - 1 || y === 0 || y === dstH - 1) {
isBorder = true;
} else {
if (highResMask[idx - 1] === 0 ||
highResMask[idx + 1] === 0 ||
highResMask[idx - dstW] === 0 ||
highResMask[idx + dstW] === 0) {
isBorder = true;
}
}
if (isBorder) {
pixels[pIdx] = 255;
pixels[pIdx + 1] = 255;
pixels[pIdx + 2] = 255;
pixels[pIdx + 3] = 255;
} else {
pixels[pIdx] = 30;
pixels[pIdx + 1] = 144;
pixels[pIdx + 2] = 255;
pixels[pIdx + 3] = 166;
}
}
}
}
const maskCanvas = document.createElement("canvas");
maskCanvas.width = dstW;
maskCanvas.height = dstH;
const mctx = maskCanvas.getContext("2d");
mctx.putImageData(imgData, 0, 0);
const fullW = baseImage.naturalWidth || dstW;
const fullH = baseImage.naturalHeight || dstH;
const fullCanvas = document.createElement("canvas");
fullCanvas.width = fullW;
fullCanvas.height = fullH;
const fctx = fullCanvas.getContext("2d");
fctx.imageSmoothingEnabled = true;
fctx.imageSmoothingQuality = "high";
fctx.drawImage(maskCanvas, 0, 0, fullW, fullH);
overlayImage.src = fullCanvas.toDataURL("image/png");
overlayImage.style.display = "block";
} catch (err) {
console.error(err);
} finally {
hoverInFlight = false;
}
}
async function requestSegmentPoint(x, y) {
const currentRequestId = ++lastRequestId;
statusEl.textContent = `点击坐标: (${x}, ${y})，请求中...`;
try {
const res = await fetch(`${apiBase()}/segment_point`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ image_id: imageId, x, y }),
});
if (!res.ok) {
statusEl.textContent = "当前点未检测到目标。";
clearOverlay();
return;
}
const json = await res.json();
if (currentRequestId !== lastRequestId) return;
overlayImage.src = json.image;
overlayImage.style.display = "block";
statusEl.textContent = `已更新选区，坐标 (${x}, ${y})`;
} catch (err) {
console.error(err);
setServerOnline(false);
statusEl.textContent = "请求失败，请检查后端。";
}
}
modeButtons.forEach((btn) => {
btn.addEventListener("click", () => {
modeButtons.forEach((b) => b.classList.remove("active"));
btn.classList.add("active");
currentMode = btn.dataset.mode;
lastRequestId++;
hoverInFlight = false;
textControls.classList.toggle("hidden", currentMode !== "text");
clearOverlay();
if (currentMode === "text") {
statusEl.textContent = "输入文本提示后点击“运行文字分割”。";
}
});
});
runTextButton.addEventListener("click", async () => {
if (!imageId) { statusEl.textContent = "请先上传图片。"; return; }
const text = promptInput.value.trim();
if (!text) { statusEl.textContent = "文本提示不能为空。"; return; }
statusEl.textContent = "文字分割中...";
try {
const res = await fetch(`${apiBase()}/segment_text`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ image_id: imageId, text }),
});
if (!res.ok) { statusEl.textContent = "文字分割失败，请检查后端日志。"; return; }
const json = await res.json();
overlayImage.src = json.image;
overlayImage.style.display = "block";
statusEl.textContent = "文字分割完成。";
} catch (err) {
console.error(err);
setServerOnline(false);
statusEl.textContent = "请求失败，请检查后端。";
}
});
</script>
</body>
</html>