重写屏幕找图算法，保证准确性

plugin/lib/quickcomposer/simulate/imageFinder.js

@@ -1,68 +1,10 @@
 const { nativeImage } = require("electron");
 const { captureScreen } = require("./screenCapture");
 
-// 将颜色值映射到8个区间
-function mapColorValue(val) {
-  if (val > 223) return 7; // [224 ~ 255]
-  if (val > 191) return 6; // [192 ~ 223]
-  if (val > 159) return 5; // [160 ~ 191]
-  if (val > 127) return 4; // [128 ~ 159]
-  if (val > 95) return 3; // [96 ~ 127]
-  if (val > 63) return 2; // [64 ~ 95]
-  if (val > 31) return 1; // [32 ~ 63]
-  return 0; // [0 ~ 31]
-}
-
-// 计算图像特征向量
-function calculateFeatureVector(
-  buffer,
-  width,
-  height,
-  startX = 0,
-  startY = 0,
-  w = width,
-  h = height
-) {
-  // 8^4 = 4096 维向量，表示RGBA各8个区间的组合
-  const vector = new Array(8 * 8 * 8 * 8).fill(0);
-
-  for (let y = startY; y < startY + h; y++) {
-    for (let x = startX; x < startX + w; x++) {
-      const idx = (y * width + x) * 4;
-      // 计算四个通道的量化值
-      const r = mapColorValue(buffer[idx]);
-      const g = mapColorValue(buffer[idx + 1]);
-      const b = mapColorValue(buffer[idx + 2]);
-      const a = mapColorValue(buffer[idx + 3]);
-
-      // 计算在向量中的位置
-      const vectorIdx = r * 512 + g * 64 + b * 8 + a;
-      vector[vectorIdx]++;
-    }
-  }
-
-  return vector;
-}
-
-// 计算余弦相似度
-function calculateCosineSimilarity(v1, v2) {
-  let dotProduct = 0;
-  let norm1 = 0;
-  let norm2 = 0;
-
-  for (let i = 0; i < v1.length; i++) {
-    dotProduct += v1[i] * v2[i];
-    norm1 += v1[i] * v1[i];
-    norm2 += v2[i] * v2[i];
-  }
-
-  return dotProduct / (Math.sqrt(norm1) * Math.sqrt(norm2));
-}
-
 // 获取显示器缩放比例
 function getDisplayScale() {
+  // MacOS 上要考虑缩放比例
   if (process.platform === "darwin") {
-    // 在 macOS 上，通过比较实际分辨率和报告的分辨率来计算缩放比例
     const primaryDisplay = utools.getPrimaryDisplay();
     const { scaleFactor } = primaryDisplay;
     return scaleFactor;
@@ -71,153 +13,94 @@ function getDisplayScale() {
 }
 
 // 在屏幕上查找图片
-async function findImage(targetImageData, options = {}) {
-  try {
-    // 获取屏幕截图
-    const screenDataUrl = await captureScreen();
-    if (!screenDataUrl) return null;
+async function findImage(subDataURL, options = {}) {
+  const mainDataURL = await captureScreen();
+  if (!mainDataURL) return null;
+  // 解析主图和子图
+  const mainImg = nativeImage.createFromDataURL(mainDataURL);
+  const subImg = nativeImage.createFromDataURL(subDataURL);
 
-    // 获取显示器缩放比例
-    const scale = getDisplayScale();
+  // 获取图像基本信息
+  const mainSize = mainImg.getSize();
+  const subSize = subImg.getSize();
 
-    // 读取屏幕截图
-    const screenImage = nativeImage.createFromDataURL(screenDataUrl);
-    const screenBuffer = screenImage.toBitmap();
-    const { width: actualWidth, height: actualHeight } = screenImage.getSize();
+  // 获取像素数据（返回Buffer，RGBA格式）
+  const mainPixels = mainImg.getBitmap();
+  const subPixels = subImg.getBitmap();
 
-    // 计算缩放后的实际尺寸
-    const screenWidth = Math.round(actualWidth / scale);
-    const screenHeight = Math.round(actualHeight / scale);
+  // 边界检查
+  if (subSize.width > mainSize.width || subSize.height > mainSize.height) {
+    throw new Error("要查找图片尺寸大于屏幕");
+  }
 
-    // 从 base64 字符串创建目标图片
-    const targetImage = nativeImage.createFromDataURL(targetImageData);
-    const targetBuffer = targetImage.toBitmap();
-    const { width: targetWidth, height: targetHeight } = targetImage.getSize();
+  // 预提取子图首像素值（优化点）
+  const firstSubPixel = [
+    subPixels[0], // R
+    subPixels[1], // G
+    subPixels[2], // B
+    subPixels[3], // A
+  ];
 
-    // 计算目标图片的特征向量
-    const targetVector = calculateFeatureVector(
-      targetBuffer,
-      targetWidth,
-      targetHeight
-    );
+  // 主图遍历边界
+  const maxX = mainSize.width - subSize.width;
+  const maxY = mainSize.height - subSize.height;
 
-    // 设置匹配阈值
-    const threshold = options.threshold || 0.9;
+  // 遍历主图每个可能的位置
+  for (let y = 0; y <= maxY; y++) {
+    for (let x = 0; x <= maxX; x++) {
+      // 快速检查首像素（性能优化关键）
+      const mainOffset = (y * mainSize.width + x) * 4;
+      if (
+        mainPixels[mainOffset] !== firstSubPixel[0] ||
+        mainPixels[mainOffset + 1] !== firstSubPixel[1] ||
+        mainPixels[mainOffset + 2] !== firstSubPixel[2] ||
+        mainPixels[mainOffset + 3] !== firstSubPixel[3]
+      ) {
+        continue;
+      }
 
-    let bestMatch = null;
-    let bestSimilarity = 0;
+      // 完整像素比对
+      let match = true;
+      for (let subY = 0; subY < subSize.height; subY++) {
+        for (let subX = 0; subX < subSize.width; subX++) {
+          // 计算像素位置
+          const mainPixelPos = ((y + subY) * mainSize.width + (x + subX)) * 4;
+          const subPixelPos = (subY * subSize.width + subX) * 4;
 
-    // 使用滑动窗口搜索
-    const stepSize = Math.round(8 * scale); // 根据缩放比例调整步长
-    for (let y = 0; y <= actualHeight - targetHeight; y += stepSize) {
-      for (let x = 0; x <= actualWidth - targetWidth; x += stepSize) {
-        // 计算当前区域的特征向量
-        const regionVector = calculateFeatureVector(
-          screenBuffer,
-          actualWidth,
-          actualHeight,
-          x,
-          y,
-          targetWidth,
-          targetHeight
-        );
-
-        // 计算相似度
-        const similarity = calculateCosineSimilarity(
-          targetVector,
-          regionVector
-        );
-
-        // 更新最佳匹配
-        if (similarity > bestSimilarity) {
-          bestSimilarity = similarity;
-          bestMatch = { x: Math.round(x / scale), y: Math.round(y / scale) };
-
-          // 如果相似度已经很高，进行精确搜索
-          if (similarity >= threshold) {
-            // 在周围进行精确搜索，注意搜索范围也要考虑缩放
-            const searchRange = Math.round(4 * scale);
-            for (let dy = -searchRange; dy <= searchRange; dy++) {
-              for (let dx = -searchRange; dx <= searchRange; dx++) {
-                const newX = x + dx;
-                const newY = y + dy;
-
-                if (
-                  newX < 0 ||
-                  newY < 0 ||
-                  newX > actualWidth - targetWidth ||
-                  newY > actualHeight - targetHeight
-                ) {
-                  continue;
-                }
-
-                const preciseVector = calculateFeatureVector(
-                  screenBuffer,
-                  actualWidth,
-                  actualHeight,
-                  newX,
-                  newY,
-                  targetWidth,
-                  targetHeight
-                );
-
-                const preciseSimilarity = calculateCosineSimilarity(
-                  targetVector,
-                  preciseVector
-                );
-                if (preciseSimilarity > bestSimilarity) {
-                  bestSimilarity = preciseSimilarity;
-                  bestMatch = {
-                    x: Math.round(newX / scale),
-                    y: Math.round(newY / scale),
-                  };
-                }
-              }
-            }
+          // 精确匹配每个通道
+          if (
+            mainPixels[mainPixelPos] !== subPixels[subPixelPos] ||
+            mainPixels[mainPixelPos + 1] !== subPixels[subPixelPos + 1] ||
+            mainPixels[mainPixelPos + 2] !== subPixels[subPixelPos + 2] ||
+            mainPixels[mainPixelPos + 3] !== subPixels[subPixelPos + 3]
+          ) {
+            match = false;
+            break;
           }
         }
+        if (!match) break;
+      }
 
-        // 如果找到足够好的匹配，提前返回
-        if (bestSimilarity >= threshold) {
-          const position = {
-            x: bestMatch.x,
-            y: bestMatch.y,
-            width: Math.round(targetWidth / scale),
-            height: Math.round(targetHeight / scale),
-            confidence: bestSimilarity,
-          };
-
-          clickImage(position, options.mouseAction);
-
-          return position;
-        }
+      if (match) {
+        const displayScale = getDisplayScale();
+        const position = {
+          x: Math.round(x / displayScale),
+          y: Math.round(y / displayScale),
+          width: Math.round(subSize.width / displayScale),
+          height: Math.round(subSize.height / displayScale),
+        };
+        clickImage(position, options.mouseAction);
+        return position;
       }
     }
-
-    // 如果没有找到足够好的匹配，但有最佳匹配且相似度不太低，也返回
-    if (bestMatch && bestSimilarity > threshold * 0.8) {
-      const position = {
-        x: bestMatch.x,
-        y: bestMatch.y,
-        width: Math.round(targetWidth / scale),
-        height: Math.round(targetHeight / scale),
-        confidence: bestSimilarity,
-      };
-      clickImage(position, options.mouseAction);
-      return position;
-    }
-
-    return null;
-  } catch (error) {
-    console.error("查找图片失败:", error);
-    return null;
   }
+
+  return null;
 }
 
 const clickImage = (position, mouseAction) => {
-  // 计算中心点
-  const centerX = position.x + position.width / 2;
-  const centerY = position.y + position.height / 2;
+  const centerX = Math.round(position.x + position.width / 2);
+  const centerY = Math.round(position.y + position.height / 2);
 
   // 根据配置执行鼠标动作
   switch (mouseAction) {

src/components/composer/simulate/ImageSearchEditor.vue

@@ -36,7 +36,7 @@
 
       <!-- 配置区域 -->
       <div class="col-12 col-sm-4">
-        <div class="row q-col-gutter-sm">
+        <div class="row">
           <!-- 从剪贴板读取按钮 -->
           <div class="col-12">
             <q-btn
@@ -53,8 +53,13 @@
           <!-- 匹配阈值设置 -->
           <div class="col-12">
             <NumberInput
-              v-model="argvs.threshold"
+              v-if="false"
+              :model-value="argvs.threshold"
+              @update:model-value="updateArgvs('threshold', $event)"
               label="匹配阈值"
+              :min="0"
+              :max="1"
+              :step="0.1"
               class="border-primary"
               :command="{
                 icon: 'tune',
@@ -64,20 +69,15 @@
 
           <!-- 鼠标动作选择 -->
           <div class="col-12">
-            <q-select
-              v-model="argvs.mouseAction"
+            <ButtonGroup
+              :is-collapse="false"
+              :model-value="argvs.mouseAction"
+              @update:model-value="updateArgvs('mouseAction', $event)"
               :options="mouseActionOptions"
               label="找到后"
               class="border-primary"
-              dense
-              filled
-              emit-value
-              map-options
             >
-              <template v-slot:prepend>
-                <q-icon name="mouse" />
-              </template>
-            </q-select>
+            </ButtonGroup>
           </div>
         </div>
       </div>
@@ -97,11 +97,13 @@
 <script>
 import { defineComponent } from "vue";
 import NumberInput from "components/composer/common/NumberInput.vue";
+import ButtonGroup from "components/composer/common/ButtonGroup.vue";
 
 export default defineComponent({
   name: "ImageSearchEditor",
   components: {
     NumberInput,
+    ButtonGroup,
   },
 
   props: {
@@ -123,7 +125,7 @@ export default defineComponent({
       ],
       defaultArgvs: {
         imagePreview: "",
-        threshold: 0.9,
+        threshold: 1,
         mouseAction: "none",
       },
     };
@@ -266,8 +268,8 @@ export default defineComponent({
   border: 2px dashed var(--q-primary);
   border-radius: 8px;
   display: flex;
-  max-height: 128px;
-  min-height: 128px;
+  max-height: 138px;
+  min-height: 138px;
   justify-content: center;
   align-items: center;
   position: relative;