5.0.231

modules/kdayun-app/src/main/resources/application-api.yml

@@ -0,0 +1,6 @@
+api:
+#启动api编写功能,由于api开发是会存在注入的风险.只建议在开发环境内开启,生成环境上建议关闭关闭此功能.
+  enabled: false 
+#是否启动api加密 数据库和网络传输都会都会以加密方式
+  encrypt:
+    enable: true

modules/kdayun-app/src/main/resources/static/appdata/filesres/ico/CEFAF76CFDC74C649664DB699CFED51A.svg

@@ -0,0 +1 @@
+<?xml version="1.0" standalone="no"?><!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd"><svg t="1694571560836" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="2169" width="16" height="16" xmlns:xlink="http://www.w3.org/1999/xlink"><path d="M180.736 248.832L0 776.448h93.696l43.52-132.608h181.76l43.008 132.608h93.696l-179.2-527.616z m-16.128 311.552l63.488-204.8 62.976 204.8zM804.096 289.792c-32-25.6-82.944-39.936-151.552-39.936h-122.368v526.592h86.016V588.8h51.2c121.088 0 185.088-58.88 185.088-169.984 1.024-58.624-15.616-102.144-48.384-129.024z m-38.656 130.56c0 34.048-10.752 79.104-102.4 79.104h-46.848v-161.28h51.2c66.816 0.256 98.048 26.368 98.048 82.176zM937.984 249.856H1024v526.592h-86.016z" p-id="2170" fill="#bfbfbf"></path></svg>

modules/kdayun-app/src/main/resources/static/libs/formdesign/libs/opencv/models/sr.prototxt

@@ -0,0 +1,403 @@
+layer {
+  name: "data"
+  type: "Input"
+  top: "data"
+  input_param {
+    shape {
+      dim: 1
+      dim: 1
+      dim: 224
+      dim: 224
+    }
+  }
+}
+layer {
+  name: "conv0"
+  type: "Convolution"
+  bottom: "data"
+  top: "conv0"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "conv0/lrelu"
+  type: "ReLU"
+  bottom: "conv0"
+  top: "conv0"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/reduce"
+  type: "Convolution"
+  bottom: "conv0"
+  top: "db1/reduce"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db1/reduce/lrelu"
+  type: "ReLU"
+  bottom: "db1/reduce"
+  top: "db1/reduce"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/3x3"
+  type: "Convolution"
+  bottom: "db1/reduce"
+  top: "db1/3x3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 8
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db1/3x3/lrelu"
+  type: "ReLU"
+  bottom: "db1/3x3"
+  top: "db1/3x3"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/1x1"
+  type: "Convolution"
+  bottom: "db1/3x3"
+  top: "db1/1x1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db1/1x1/lrelu"
+  type: "ReLU"
+  bottom: "db1/1x1"
+  top: "db1/1x1"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db1/concat"
+  type: "Concat"
+  bottom: "conv0"
+  bottom: "db1/1x1"
+  top: "db1/concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "db2/reduce"
+  type: "Convolution"
+  bottom: "db1/concat"
+  top: "db2/reduce"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db2/reduce/lrelu"
+  type: "ReLU"
+  bottom: "db2/reduce"
+  top: "db2/reduce"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db2/3x3"
+  type: "Convolution"
+  bottom: "db2/reduce"
+  top: "db2/3x3"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 8
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 8
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db2/3x3/lrelu"
+  type: "ReLU"
+  bottom: "db2/3x3"
+  top: "db2/3x3"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db2/1x1"
+  type: "Convolution"
+  bottom: "db2/3x3"
+  top: "db2/1x1"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "db2/1x1/lrelu"
+  type: "ReLU"
+  bottom: "db2/1x1"
+  top: "db2/1x1"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "db2/concat"
+  type: "Concat"
+  bottom: "db1/concat"
+  bottom: "db2/1x1"
+  top: "db2/concat"
+  concat_param {
+    axis: 1
+  }
+}
+layer {
+  name: "upsample/reduce"
+  type: "Convolution"
+  bottom: "db2/concat"
+  top: "upsample/reduce"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "upsample/reduce/lrelu"
+  type: "ReLU"
+  bottom: "upsample/reduce"
+  top: "upsample/reduce"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "upsample/deconv"
+  type: "Deconvolution"
+  bottom: "upsample/reduce"
+  top: "upsample/deconv"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 32
+    bias_term: true
+    pad: 1
+    kernel_size: 3
+    group: 32
+    stride: 2
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "upsample/lrelu"
+  type: "ReLU"
+  bottom: "upsample/deconv"
+  top: "upsample/deconv"
+  relu_param {
+    negative_slope: 0.05000000074505806
+  }
+}
+layer {
+  name: "upsample/rec"
+  type: "Convolution"
+  bottom: "upsample/deconv"
+  top: "upsample/rec"
+  param {
+    lr_mult: 1.0
+    decay_mult: 1.0
+  }
+  param {
+    lr_mult: 1.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 1
+    bias_term: true
+    pad: 0
+    kernel_size: 1
+    group: 1
+    stride: 1
+    weight_filler {
+      type: "msra"
+    }
+  }
+}
+layer {
+  name: "nearest"
+  type: "Deconvolution"
+  bottom: "data"
+  top: "nearest"
+  param {
+    lr_mult: 0.0
+    decay_mult: 0.0
+  }
+  convolution_param {
+    num_output: 1
+    bias_term: false
+    pad: 0
+    kernel_size: 2
+    group: 1
+    stride: 2
+    weight_filler {
+      type: "constant"
+      value: 1.0
+    }
+  }
+}
+layer {
+  name: "Crop1"
+  type: "Crop"
+  bottom: "nearest"
+  bottom: "upsample/rec"
+  top: "Crop1"
+}
+layer {
+  name: "fc"
+  type: "Eltwise"
+  bottom: "Crop1"
+  bottom: "upsample/rec"
+  top: "fc"
+  eltwise_param {
+    operation: SUM
+  }
+}

modules/kdayun-app/src/main/resources/static/libs/formdesign/libs/opencv/utils.js

@@ -0,0 +1,125 @@
+function Utils(errorOutputId) {
+  this.errorOutput = document.getElementById(errorOutputId);
+
+  this.loadScript = function (url) {
+    return new Promise((resolve, reject) => {
+      let script = document.createElement("script");
+      script.setAttribute("async", "");
+      script.setAttribute("type", "text/javascript");
+      script.setAttribute("id", "opencvjs");
+      script.addEventListener("load", async () => {
+        if (cv.getBuildInformation) {
+          console.log(cv.getBuildInformation());
+          resolve();
+        } else {
+          // WASM
+          if (cv instanceof Promise) {
+            cv = await cv;
+            console.log(cv.getBuildInformation());
+            resolve();
+          } else {
+            cv["onRuntimeInitialized"] = () => {
+              console.log(cv.getBuildInformation());
+              resolve();
+            };
+          }
+        }
+      });
+      script.addEventListener("error", () => {
+        reject();
+      });
+      script.src = url;
+      let node = document.getElementsByTagName("script")[0];
+      node.parentNode.insertBefore(script, node);
+    });
+  };
+
+  /**
+   * 请求二维码训练模型文件
+   */
+  this.fetchModelsData = async function (name) {
+    // const response = await fetch(`https://static.xxxx.com/common/opencv/models/${name}`, {
+    const response = await fetch(`./models/${name}`, {
+      method: "GET",
+    });
+    const data = await response.arrayBuffer();
+
+    return new Uint8Array(data);
+  };
+
+
+  /**
+   * 加载图片到canvas
+   * 发票的二维码基本都在左上角
+   * 为提高效率，只截取出图片二维码的左上角区域放入canvas
+   * @param {*} url
+   * @param {*} cavansId
+   */
+  this.loadImageToCanvas = function (url, cavansId) {
+    let canvas = document.getElementById(cavansId);
+    let ctx = canvas.getContext("2d");
+    let img = new Image();
+    img.crossOrigin = "anonymous";
+    img.onload = function () {
+      const { width, height } = img;
+      const isVertical = width < height;
+      // const crossNum = isVertical ? 3 : 4;
+      // const verticalNum = isVertical ? 4 : 3;
+
+      // canvas.width = width / crossNum;
+      // canvas.height = height / verticalNum;
+      // ctx.drawImage(img, isVertical ? width * (2 / 3) : 0, 0, width, height, 0, 0, width, height);
+
+
+      canvas.width = width
+      canvas.height = height;
+      ctx.drawImage(img, 0, 0, width, height, 0, 0, width, height);
+    };
+    img.src = url;
+  };
+  /**
+   * canvas转图片
+   */
+  this.imagedataToImage = function (imagedata) {
+    const canvas = document.createElement("canvas");
+    const ctx = canvas.getContext("2d");
+    canvas.width = imagedata.width;
+    canvas.height = imagedata.height;
+    ctx.putImageData(imagedata, 0, 0);
+
+    return new Promise((resolve) => {
+      const img = new Image();
+      img.src = canvas.toDataURL();
+      img.onload = () => {
+        resolve(img);
+      };
+    });
+  };
+
+  /**
+   * 拆分图片坐标
+   * @param {*} width 图片宽
+   * @param {*} height 图片高
+   *
+   * @returns 坐标数组 [x,y,width,height][]
+   */
+  this.segmentationImageCoordinates = function (width, height) {
+    const isVertical = width < height;
+    const crossNum = isVertical ? 3 : 5;
+    const verticalNum = isVertical ? 5 : 3;
+    const blockWidth = width / crossNum;
+    const blockHeight = height / verticalNum;
+    const coordinates = [];
+
+    for (let y = 0; y < verticalNum; y++) {
+      for (let x = 0; x < crossNum; x++) {
+        const cx = x * blockWidth;
+        const cy = y * blockHeight;
+
+        coordinates.push([cx, cy, blockWidth, blockHeight]);
+      }
+    }
+
+    return coordinates;
+  };
+}