[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fUz7iUZV37vBr2a9aRaJfNtH7hhOI9F6PfzjEr3LLfWk":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":19,"related":20,"source":30,"type":31},[],"2025-01-03 16:07:43",176052447,[8,9,10,11],"以树形结构输出轮廓信息","只检测外轮廓","对检测到的轮廓不建立等级关系","输出两层轮廓信息",{"count":13,"courseId":14,"courseImg":15,"courseName":16,"workId":17,"workName":18},122,"49fdbcb522d1c23cad56f543ae5a3941","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F25b30343053994e8940089572d36015b.jpg","计算机视觉应用开发","exam_147134842","计算机视觉应用开发模拟试卷","在图像轮廓查找函数 cv2.findContours () 中,轮廓检索模式 cv2.RETR_EXTERNAL 的作用是( )",[21,32,41,50,53,62,71,80,89,98],{"answer":22,"createTime":5,"id":23,"options":24,"question":29,"source":30,"type":31},[],176052444,[25,26,27,28],"cv2.ADAPTIVE_THRESH_BINARY","cv2.ADAPTIVE_THRESH_MEAN_C","cv2.ADAPTIVE_THRESH_BINARY_INV","cv2.ADAPTIVE_THRESH_GAUSSIAN_C","自适应阈值分割中,邻域内加权平均的方法是( )","v1",0,{"answer":33,"createTime":5,"id":34,"options":35,"question":40,"source":30,"type":31},[],176052445,[36,37,38,39],"'John' 6","123456 3","'John' 3","123456 6","运行以下代码的结果是什么: my_dic = {'John':123456, 'Lisa':98765, 'Bob':56666} print( my_dic['John']) print(len(my_dic))",{"answer":42,"createTime":5,"id":43,"options":44,"question":49,"source":30,"type":31},[],176052446,[45,46,47,48],"[1, 2, 3, 4, 5] [1, 2, 3, 4] [1, 2, 3, 4] True False","[1, 2, 3, 4, 5] [1, 2, 3, 4, 5] [1, 2, 3, 4] True False","[1, 2, 3, 4, 5] [1, 2, 3, 4, 5] [1, 2, 3, 4] False False","[1, 2, 3, 4, 5] [1, 2, 3, 4, 5] [1, 2, 3, 4, 5] True True","阅读下面的代码,判断选择执行结果( ) a = [1, 2, 3, 4] c = a.copy() b = a a.append(5) print(a) print(b) print(c) print(a is b) print(a is c)",{"answer":51,"createTime":5,"id":6,"options":52,"question":19,"source":30,"type":31},[],[8,9,10,11],{"answer":54,"createTime":5,"id":55,"options":56,"question":61,"source":30,"type":31},[],176052448,[57,58,59,60],"不变","更加严格","更加宽松","根据图像内容自适应变化","在 Brute - Force 特征匹配中,cv2.BFMatcher () 函数的 crossCheck 参数设置为 True 时,匹配条件会如何变化",{"answer":63,"createTime":5,"id":64,"options":65,"question":70,"source":30,"type":31},[],176052449,[66,67,68,69],"将连续的点连在一起的线,具有相同的颜色或灰度","图像中的亮点","图像中的噪声点","图像中的边缘像素点","图像的轮廓可以被认为是( )",{"answer":72,"createTime":5,"id":73,"options":74,"question":79,"source":30,"type":31},[],176052450,[75,76,77,78],"绿色","随机颜色","红色","蓝色","使用 cv2.drawKeypoint 函数绘制图像中的关键点时,默认的关键点颜色是什么",{"answer":81,"createTime":5,"id":82,"options":83,"question":88,"source":30,"type":31},[],176052451,[84,85,86,87],"平移不变性和旋转不变性","亮度不变性和旋转不变性","尺度不变性和旋转不变性","尺度不变性和亮度不变性","图像特征检测中,SIFT 特征提取算法具有哪些优点",{"answer":90,"createTime":5,"id":91,"options":92,"question":97,"source":30,"type":31},[],176052452,[93,94,95,96],"高斯滤波","双边滤波","中值滤波","均值滤波","以下哪种滤波方法在去噪的同时能较好地保护图像边缘信息?( )",{"answer":99,"createTime":5,"id":100,"options":101,"question":106,"source":30,"type":31},[],176052453,[102,103,104,105],"图像采集-图像标注-图像清洗-模型构建-模型训练-模型评估-调用预测","图像采集-图像清洗-图像标注-模型构建-模型训练-模型评估-调用预测","图像采集-图像清洗-图像标注-模型构建-模型训练-调用预测-模型评估","图像采集-图像清洗-图像标注-模型训练-模型构建-模型评估-调用预测","关于计算机视觉技术的开发流程,以下排序正确的是"]