, path) x = zeros(size(labelsInfo, 1), imageSize) for (index, idImage) in enumerate(labelsInfo.ID...Gray.(): 将RGB图像转化为灰度图像 reshape(): 在这里做的是平铺工作 设置图像大小以及项目路径： imageSize = 400 path = "..."...读取训练图像数据： xTrain = read_data("train", labelsInfoTrain, imageSize, path) ?...读取测试图像数据： xTest = read_data("test", labelsInfoTest, imageSize, path) ?...(temp) x[index, :] = reshape(temp, 1, imageSize) end return x end imageSize = 400 path
imageSize=getImageViewSize(imageView); //获取图片大小，ImageSize是封装着ImageView大小的类 //计算采样率 options.inSampleSize...=caculateInSampleSize(options,imageSize.width,imageSize.height); options.inJustDecodeBounds=false; Bitmap...imageSize=getImageViewSize(imageView); int inSampleSize=caculateInSampleSize(options, imageSize.width...getImageViewSize(ImageView imageView) { ImageSize imageSize = new ImageSize(); DisplayMetrics metrics...= width; imageSize.height = height; return imageSize; } //ImageView大小的封装类 private static class ImageSize
= GetImageSize(image, width, height); return GetThumbnailImage(image, imageSize.Width, imageSize.Height...; int desiredWidth = imageSize.Width; imageSize.Height = desiredHeight; if...(widthRatio > 0) imageSize.Width = Convert.ToInt32(imageSize.Height * widthRatio);...if (imageSize.Width > desiredWidth) { imageSize.Width = desiredWidth;...imageSize.Height = Convert.ToInt32(imageSize.Width * heightRatio); } return imageSize
= {}; if(imageWidth){ imageSize.imageWidth = imageWidth; imageSize.imageHeight =...} }); } return imageSize; } /*** * 按照显示图片的高等比例缩放得到显示图片的宽 * @params...= {}; if(imageHeight){ imageSize.imageWidth = (imageHeight *originalWidth) / originalHeight...} }); } return imageSize; } } export default Util; 复制代码 工具库使用 <image bindload...,imageHeight:imageSize.imageHeight}) } }) 复制代码 绘制背景图 用上面的方法动态设置图片宽高，解决失真问题 import Util from '../..
targetData[i + 3] = 255; } } UIImage *result = [self imageFromBRGABytes: targetData imageSize... free(targetData); return result; } - (UIImage *)imageFromBRGABytes:(unsigned char *)imageBytes imageSize...:(CGSize)imageSize { CGImageRef imageRef = [self imageRefFromBGRABytes:imageBytes imageSize:imageSize...:(CGSize)imageSize { CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB(); CGContextRef...context = CGBitmapContextCreate(imageBytes, imageSize.width
, CV_32S); sub_map2 = sub_map2.zeros(imageSize, CV_16U); sub_map3 = sub_map3.zeros(imageSize, CV_16U)...; sub_map4 = sub_map4.zeros(imageSize, CV_16U); sub_map5 = sub_map5.zeros(imageSize, CV_16U); float x_value..., "uint2", imageSize.width, imageSize.height, (Hlong)(temp)); memcpy(temp, sub_map3.data, size * 2);...HalconCpp::GenImage1(&sub_map_data3, "uint2", imageSize.width, imageSize.height, (Hlong)(temp)); memcpy...(temp, sub_map4.data, size * 2); HalconCpp::GenImage1(&sub_map_data4, "uint2", imageSize.width, imageSize.height
300, right: 16 }) .rotate({ x: 0, y: 0, z: 1, angle: this.angle }) .scale({ x: this.imageSize..., y: this.imageSize }) 在Image组件中设置了很多属性，如height、width等，这些都是使用静态值设置的，而旋转角度（this.angle）和图像缩放比例（this.imageSize...() } 本案例完整的代码如下： @Entry @Component struct Index { @State private speed: number = 5 @State private imageSize..., y: this.imageSize }) // 创建Text组件(用于描述Slider组件) this.DescribeText('速度：', this.speed) Slider({...) // 用于控制缩放比例 Slider({ value: this.imageSize, min: 0.5, max: 4.5,
/** * 压缩的宽和高 */ private class ImageSize{ int width ; int height; }...计算压缩的宽和高的方法 /** * 根据imageView获取适当的压缩的宽和高 * @param imageView */ private ImageSize...getImageViewSize(ImageView imageView) { ImageSize imageSize = new ImageSize(); final...// parameter if (height <= 0) height = displayMetrics.heightPixels; imageSize.width...= width; imageSize.height = height; return imageSize; } /** * 为了兼容低版本，没有采用@
小图片不放大 static func imageZoomByWidth(_ sourceImage:UIImage,maxWidth:CGFloat) -> UIImage{ let imageSize...= sourceImage.size; let width = imageSize.width; let height = imageSize.height;...static func imageZoomByHeight(_ sourceImage:UIImage,maxHeight:CGFloat) -> UIImage{ let imageSize...= sourceImage.size; let width = imageSize.width; let height = imageSize.height;...= sourceImage.size; let width = imageSize.width; let height = imageSize.height;
imageSize = ImageSizeUtil.getImageViewSize(imageView); // 2、压缩图片 bm = decodeSampledBitmapFromPath(path..., imageSize.width, imageSize.height); return bm; } /** * 从任务队列取出一个方法 * * @return */ private Runnable...return inSampleSize; } /** * 根据ImageView获适当的压缩的宽和高 * * @param imageView * @return */ public static ImageSize...getImageViewSize(ImageView imageView) { ImageSize imageSize = new ImageSize(); DisplayMetrics displayMetrics...= width; imageSize.height = height; return imageSize; } public static class ImageSize { public int width
(ImgWidth, ImgHeight); cv::Mat NewCameraMatrix = getOptimalNewCameraMatrix(K, D, imageSize, alpha, imageSize..., 0); // 非鱼眼相机 initUndistortRectifyMap(K, D, cv::Mat(), NewCameraMatrix, imageSize, CV_16SC2, map1,...const int ImgWidth = 1920; const int ImgHeight = 1080; cv::Mat map1, map2; cv::Size imageSize...= 0; cv::Mat NewCameraMatrix; cv::fisheye::estimateNewCameraMatrixForUndistortRectify(K, D, imageSize...cv::Mat UndistortImage; cv::fisheye::undistortImage(RawImage, UndistortImage, K, D, K, imageSize
, type_size, center_crop_size = 128): self.imageSize = imageSize self.type_size = type_size...********************** myReader = MyReader(imageSize=imageSize, type_size=type_size, center_crop_size..., imageSize)).flatten() return img # 使用训练好的参数进行预测 def to_prediction(inferer, image_paths, imageSize..., imageSize)).flatten() return img # 使用训练好的参数进行预测 def to_prediction(inferer, image_paths, imageSize...=imageSize) print('预测结果为:%d,可信度为:%f' % (result, probability))
// 设置图片名 reader.setFileName("D:\\123.jpg"); // 读取图片大小 //sleep(30000); QSize imageSize...= reader.size(); // 缩放图片尺寸以适应屏幕大小 //imageSize.scale(100,100,); //设定宽度高度比例 //imageSize.scale...(100,Qt::KeepAspectRatio); // 设置图片大小 imageSize.setHeight(500); imageSize.setWidth(500); reader.setScaledSize...(imageSize); img= reader.read(); // 读取图片 QLabel *m_label= new QLabel; //m_label->resize(image_width
class SegDataset(Dataset): def __init__(self,filetxt,imagesize,cropsize,transform=None):...lines = open(filetxt,'r').readlines() self.samples = [] self.imagesize = imagesize...,self.imagesize),interpolation=cv2.INTER_NEAREST) label = cv2.resize(label,(self.imagesize,self.imagesize...),interpolation=cv2.INTER_NEAREST) offsetx = np.random.randint(self.imagesize-self.cropsize)...(filetxt,imagesize,cropsize) print(mydataset.
初始化变量以保存图像大小 imageSize = zeros(numImages,2); % Iterate over remaining image pairs 迭代剩余的图像对 for n = 2...imageSize(n,:) = size(grayImage); % Detect and extract SURF features for I(n)....(i,2)], [1 imageSize(i,1)]); end 接下来，计算每次变换的平均 X 限制，并找到位于中心的图像。...outputLimits for i = 1:numel(tforms) [xlim(i,:), ylim(i,:)] = outputLimits(tforms(i), [1 imageSize...(i,2)], [1 imageSize(i,1)]); end maxImageSize = max(imageSize); % Find the minimum and maximum output
unsigned int read, ri, p, n; unsigned int imgWidth = w; unsigned int imgHeight = h; unsigned int imageSize...= imgWidth*imgHeight; unsigned char * rgb = (unsigned char *)malloc(sizeof(unsigned char) * imageSize...* 3); unsigned char * r = rgb; unsigned char * g = rgb + imageSize; unsigned char * b = rgb + imageSize...* 2; unsigned char * rgb2 = (unsigned char *)malloc(sizeof(unsigned char) * imageSize * 3); unsigned...char * r2 = rgb2; unsigned char * g2 = rgb2 + imageSize; unsigned char * b2 = rgb2 + imageSize * 2
): self.imageSize = imageSize def train_mapper(self,sample): ''' map image.../model/model.tar" # 数据的大小 datadim = 3 * imageSize * imageSize paddleUtil = PaddleUtil().../model/model.tar" # 数据的大小 datadim = 3 * imageSize * imageSize # 添加数据 image_path = [].../model/model.tar" # 数据的大小 datadim = 3 * imageSize * imageSize paddleUtil = PaddleUtil().../model/model.tar" # 数据的大小 datadim = 3 * imageSize * imageSize # ************************
{\[Theta], 2 \[Pi] i/m, 2 \[Pi] (m + i - 2)/m, 2 \[Pi]/m}], PlotRange -> 3, ImageSize...540, Background -> None], {i,1, m}]; ImageCompose[Graphics[Background -> cols[[5]], ImageSize...Background -> RGBColor["#172940"], PlotStyle -> Directive[Thickness[.004], RGBColor["#acf0f2"]], ImageSize...Background -> RGBColor["#172940"], PlotStyle -> Directive[Thickness[.004], RGBColor["#acf0f2"]], ImageSize...verts, k + 1][[i]]}]}, {i, 1, n - 1, 2}, {t, 1/12, 11/12, 1/12}]}, PlotRange -> 3, ImageSize
const fs = require('fs-extra'); const path = require('path'); const imageSize = require('image-size')...plot.dirName = dirName; plot.fileName = subfileName; const imageInfo = imageSize...= item.split(" ")[0]; imageX = imageSize.split(".")[0]; imageY = imageSize.split...let self = this; var html, imgNameWithPattern, imgName, imageSize...= item.split(" ")[0]; imageX = imageSize.split(".")[0]; imageY = imageSize.split
private String projectName = "test"; private String common = "common"; private String imageSize...; } public void setImageSize(String imageSize) { this.imageSize = imageSize; } }...public String uploadImgToCos(MultipartFile file, String businessName) throws Exception { int imageSize...= Integer.parseInt(cosConfig.getImageSize()); int maxSize = imageSize << 20; if (file.getSize...() > maxSize) { throw new Exception("上传图片大小不能超过"+imageSize+"M！")
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