1、cv2.imread()接口读图像,读进来直接是BGR 格式数据格式在 0~255,通道格式为(W,H,C) 2、caffe.io.load_image()读进来是RGB格式和 0~1(float) 因此,cv2.imread()读取的数据,需要进过转换后,才和caffe.io.load_image()相同,例如: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 image=caffe.io...
img_rotated =crop_image(img_rotated, x0, y0, w_crop, h_crop)returnimg_rotated'''随机旋转 angle_vari是旋转角度的范围[-angle_vari, angle_vari) p_crop是要进行去黑边裁剪的比例'''defrandom_rotate(img, angle_vari, p_crop): angle = np.random.uniform(-angle_vari, angle_vari) crop =...
(正值为顺时针旋转,负值为逆时针旋转) imageRotate1(src, angle) { if src.empty() { return -1 } width := src.cols height := src.rows center := [width / 2.0, height / 2.0] scale := 1.0 trans_mat := cv2.getRotationMatrix2D(center, -angle, scale) dst := cv2.warpAffine(src, ...
>> python run_augmentation.py imagenet_samples more_samples 1000 --rotate_angle_vari 180 --p_rotate_crop 0.5 其中imagenet_samples为一些从imagenet图片url中随机下载的一些图片,--rotate_angle_vari设为180方便测试全方向的旋转,--p_rotate_crop设置为0.5,让旋转裁剪对一半图片生效。扰动增加后的1000张图...
() > p_crop else True return rotate_image(img, angle, crop) ''' 定义hsv变换函数: hue_delta是色调变化比例 sat_delta是饱和度变化比例 val_delta是明度变化比例 ''' def hsv_transform(img, hue_delta, sat_mult, val_mult): img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV).astype(np.float...
旋转函数:angle是逆时针旋转的角度crop是个布尔值,表明是否要裁剪去除黑边'''defrotate_image(img, angle, crop): h, w = img.shape[:2]#旋转角度的周期是360°angle %= 360#用OpenCV内置函数计算仿射矩阵M_rotate = cv2.getRotationMatrix2D((w/2, h/2), angle, 1)#得到旋转后的图像img_rotated =...
Image Sensor1/2.7" Progressive Scan CMOS Max. Resolution1920 × 1080 Min. IlluminationColor: 0.005 Lux @ (F1.6, AGC ON),B/W: 0 Lux with IR Shutter Time1/3 s to 1/100,000 s Day & NightIR cut filter Angle AdjustmentPan: 0° to 355°,tilt: 0° to 75°,rotate: 0° to ...
models: DS-2CV2126G0-IDW(2.8mm) DS-2CV2126G0-IDW(4mm) DS-2CV2126G0-IDW Discontinued Specification Resources Accessories Specification Camera Lens Illuminator Video Audio Network Wi-Fi Image Interface Event Deep Learning Function General Approval Camera Image Sensor1/2.8″ Progressive Scan CMOS Min...
angle:旋转角度,单位为角度,逆时针为正数,顺时针为负数 scale: 缩放因子 返回值:M, 旋转变换矩阵,2行3列 # 1.36 图像旋转 (以任意点 (x0,y0) 为中心旋转) img = cv2.imread("../images/imgGaia.tif") # 读取彩色图像(BGR) height, width = img.shape[:2] # 图片的高度和宽度 theta1, theta2 ...
If the logos differed in scale or the viewing angle was different, the method would fail. For example, let’s try this example image, but this time I have rotated the Coca-Cola bottle slightly and scaled the bottle down: $ python single_template_matching.py \ --image images/coke_bottle...