基于数字处理答案

基于OpenCV的数字图像处理参考答案项目一知识回顾ABBAABCCCC技能练习参考代码：importcv2importnumpyasnpimportrandom#读取图像image=cv2.imread('image//girl.jpg')print(image.shape)image_mask=image.copy()#将image复制一份给变量image_maskimage_mask[80:105,110:185]=(255,255,255)cv2.imshow("image",image)cv2.imshow("image_mask",image_mask)cv2.waitKey()cv2.destroyAllWindows()项目二知识回顾BABAACBACB技能练习参考代码：importcv2importnumpyasnp#读取图像image=cv2.imread('image//house.jpg')ifimageisNone:print("Error:Imagecouldnotberead.")exit()#图像旋转,以图像中心为旋转中心,旋转45度(h,w)=image.shape[:2]center=(w//2,h//2)M=cv2.getRotationMatrix2D(center,45,1.0)#第三个参数是缩放比例rotated=cv2.warpAffine(image,M,(w,h))#旋转后的图像大小可能与原图不同，这里简单设为相同#图像平滑处理（均值滤波）,使用5x5滤波核smoothed=cv2.GaussianBlur(rotated,(5,5),0,0)#显示结果cv2.imshow('OriginalImage',image)cv2.imshow('RotatedImage',rotated)cv2.imshow('SmoothedImage',smoothed)#等待按键后关闭窗口cv2.waitKey(0)cv2.destroyAllWindows()项目三知识回顾BDBCABBCAC技能练习参考代码：importcv2importnumpyasnp#读取图像image=cv2.imread('image//house.jpg')ifimageisNone:print("Error:Imagecouldnotberead.")exit()#图像旋转,以图像中心为旋转中心,旋转45度(h,w)=image.shape[:2]center=(w//2,h//2)M=cv2.getRotationMatrix2D(center,45,1.0)#第三个参数是缩放比例rotated=cv2.warpAffine(image,M,(w,h))#旋转后的图像大小可能与原图不同，这里简单设为相同#图像平滑处理（均值滤波）,使用5x5滤波核smoothed=cv2.GaussianBlur(rotated,(5,5),0,0)#显示结果cv2.imshow('OriginalImage',image)cv2.imshow('RotatedImage',rotated)cv2.imshow('SmoothedImage',smoothed)#等待按键后关闭窗口cv2.waitKey(0)cv2.destroyAllWindows()项目四知识回顾ABACCAAADA技能练习参考代码：importcv2importnumpyasnpdefpreprocess_image(image):#定义图像预处理函数#转换为灰度图像gray=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)#高斯模糊，去除噪声blurred=cv2.GaussianBlur(gray,(5,5),0)#形态学开运算，去除小的噪声kernel=np.ones((5,5),np.uint8)opening=cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel)returnopening#加载图像image=cv2.imread('image//car4.png')#检查图像是否正确加载ifimageisNone:print("Error:Imagenotfound.")exit()processed_image=preprocess_image(image)#调用函数对图像进行预处理edges=cv2.Canny(processed_image,100,200)#获取车辆的轮廓cv2.imwrite(“image//edges.jpg”,edges)#显示原始图像和检测到的车辆cv2.imshow('OriginalImage',image)cv2.imshow('VehiclesDetected',edges)#等待按键，然后关闭所有窗口cv2.waitKey(0)cv2.destroyAllWindows()项目五知识回顾BABAADABCC技能练习参考代码：importcv2importnumpyasnpimportmatplotlib.pyplotaspltimage=cv2.imread('image//star.jpg')gray_image=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)#转换为灰度图#阈值处理_,binary_image=cv2.threshold(gray_image,127,255,cv2.THRESH_BINARY_INV)#假设使用反二值化，根据实际情况调整#检测轮廓contours,hierarchy=cv2.findContours(binary_image,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)#绘制轮廓和凸包contour_color=(0,255,0)#绿色轮廓hull_color=(0,0,255)#红色凸包forcontourincontours:hull=cv2.convexHull(contour)#计算凸包cv2.drawContours(image,[contour],-1,contour_color,2)#绘制轮廓cv2.drawContours(image,[hull],-1,hull_color,2)#绘制凸包plt.figure(figsize=(10,8))plt.title('ContoursandConvexHulls')plt.imshow(cv2.cvtColor(image,cv2.COLOR_BGR2RGB))#注意Matplotlib使用RGB顺序plt.axis('off')plt.show()项目六知识回顾ABACBBCCAC技能练习参考代码：importcv2defReversePlayVideo(src):#创建VideoCapture对象cap=cv2.VideoCapture(src)ifnotcap.isOpened():print("Error:视频或摄像头打开失败.....")return#获取视频流属性frame_width=cap.get(cv2.CAP_PROP_FRAME_WIDTH)frame_height=cap.get(cv2.CAP_PROP_FRAME_HEIGHT)fps=cap.get(cv2.CAP_PROP_FPS)brightness=cap.get(cv2.CAP_PROP_BRIGHTNESS)print(f"Framesize:{frame_width}x{frame_height}")print(f"FPS:{fps}")print(f"Brightness:{brightness}")#获取最后一帧的索引total_frames=cap.get(cv2.CAP_PROP_FRAME_COUNT)frame_index=total_frames-1whilecap.isOpened()andframe_index>=0:#设置当前帧位置cap.set(cv2.CAP_PROP_POS_FRAMES,frame_index)ret,frame=cap.read()ifnotret:print("视频捕获错误或结束.....")breakcv2.imshow("ReversePlayVideo",frame)