从node.js中的扫描图像评估checkbox
我想评估checkbox被选中或不是从扫描的图像。 我find了像node-dv和node-fv这样的节点模块。 但是，当安装这个我得到了以下错误在Mac上。
../deps/opencv/modules/core/src/arithm1.cpp:444:51: error: constant expression evaluates to 4294967295 which cannot be narrowed to type 'int' [-Wc++11-narrowing] static int CV_DECL_ALIGNED(16) v64f_absmask[] = { 0xffffffff, 0x7fffffff, 0xffffffff, 0x7fffffff }; ^~~~~~~~~~ ../deps/opencv/modules/core/src/arithm1.cpp:444:51: note: insert an explicit cast to silence this issue static int CV_DECL_ALIGNED(16) v64f_absmask[] = { 0xffffffff, 0x7fffffff, 0xffffffff, 0x7fffffff }; ^~~~~~~~~~ static_cast<int>( ) ../deps/opencv/modules/core/src/arithm1.cpp:444:75: error: constant expression evaluates to 4294967295 which cannot be narrowed to type 'int' [-Wc++11-narrowing] static int CV_DECL_ALIGNED(16) v64f_absmask[] = { 0xffffffff, 0x7fffffff, 0xffffffff, 0x7fffffff }; ^~~~~~~~~~ ../deps/opencv/modules/core/src/arithm1.cpp:444:75: note: insert an explicit cast to silence this issue static int CV_DECL_ALIGNED(16) v64f_absmask[] = { 0xffffffff, 0x7fffffff, 0xffffffff, 0x7fffffff }; ^~~~~~~~~~ static_cast<int>( ) 2 errors generated. make: *** [Release/obj.target/libopencv/deps/opencv/modules/core/src/arithm1.o] Error 1 gyp ERR! build error gyp ERR! stack Error: `make` failed with exit code: 2 gyp ERR! stack at ChildProcess.onExit (/Users/entapzian/.nvm/versions/node/v4.3.1/lib/node_modules/npm/node_modules/node-gyp/lib/build.js:270:23) gyp ERR! stack at emitTwo (events.js:87:13) gyp ERR! stack at ChildProcess.emit (events.js:172:7) gyp ERR! stack at Process.ChildProcess._handle.onexit (internal/child_process.js:200:12) 上面的依赖是我的问题的最佳解决scheme？ 如果不是，请build议我一个好的解决scheme。
对不起，迟到的答复，我昨天和今天真的很忙。 这是一个示例，它捕获图像的预定义区域，并确定checkbox是否填充或为空。 这只是一个起点，可能会大大改善，但如果扫描的图像质量不错，它应该工作。
第一步是获取图像的像素。 接下来，通过根据模式抓取图像中的区域，获取包含checkbox的区域。 最后，通过比较图像中该区域的平均亮度与未选中的框的基线亮度，来评估checkbox是否被选中。
我build议使用get-pixels Node.js包来获取图像像素。
以下是您可以根据需要进行调整的示例：
var get_pixels = require('get-pixels'); var image_uri = 'path_to_image'; get_pixels(image_uri, process_image); var pattern_width = 800, // Width of your pattern image pattern_height = 1100; // Height of your pattern image // The pattern image doesn't need to be loaded, you just need to use its dimensions to reference the checkbox regions below // This is only for scaling purposes in the event that the scanned image is of a higher or lower resolution than what you used as a pattern. var checkboxes = [ {x1: 10, y1: 10, x2: 30, y2: 30}, // Top left and bottom right corners of the region containing the checkbox {x1: 10, y1: 60, x2: 30, y2: 80} ]; // You'll need to get these by running this on an unchecked form and logging out the adjusted_average of the regions var baseline_average = ??, // The average brightness of an unchecked region darkness_tolerance = ??; // The offset below which the box is still considered unchecked function process_image(err, pixels) { if (!err) { var regions = get_regions(pixels); var checkbox_states = evaluate_regions(regions); // Whatever you want to do with the determined states }else{ console.log(err); return; } } function get_regions(pixels) { var regions = [], // Array to hold the pixel data from selected regions img_width = pixels.shape[0], // Get the width of the image being processed img_height = pixels.shape[1], // Get the height scale_x = img_width / pattern_width, // Get the width scale difference between pattern and image (for different resolution scans) scale_y = img_height / pattern_height; // Get the height scale difference for (var i = 0; i < checkboxes.length; i++) { var start_x = Math.round(checkboxes[i].x1 * scale_x), start_y = Math.round(checkboxes[i].y1 * scale_y), end_x = Math.round(checkboxes[i].x2 * scale_x), end_y = Math.round(checkboxes[i].y2 * scale_y), region = []; for (var y = start_y; y <= end_y; y++) { for (var x = start_x; y <= end_x; x++) { region.push( pixels.get(x, y, 0), // Red channel pixels.get(x, y, 1), // Green channel pixels.get(x, y, 2), // Blue channel pixels.get(x, y, 3) // Alpha channel ); } } regions.push(region); } return regions; } function evaluate_regions(regions) { var states = []; for (var i = 0; i < regions.length; i++) { var brightest_value = 0, darkest_value = 255, total = 0; for (var j = 0; j < regions[i].length; j+=4) { var brightness = (regions[i][j] + regions[i][j + 1] + regions[i][j + 2]) / 3; // Pixel brightness if (brightness > brightest_value) brightest_value = brightness; if (brightness < darkest_value) darkest_value = brightness; total += brightness; } var adjusted_average = (total / (regions[i].length / 4)) - darkest_value; // Adjust contrast var checked = baseline_average - adjusted_average > darkness_tolerance ? true : false; states.push(checked); } return states; }