我是tensorflow的新手，我想知道如何在检测对象时同时获取其“类别”和分数？
这是一个样本图像的分数数组，你可以看到有4个“框”的置信度超过50%:
scoresOut[104]: array([[ 0.86274904, 0.68427145, 0.53348649, 0.51449829, 0.4737072 , 0.20210901, 0.18676876, 0.15660423, 0.15557742, 0.15542269, 0.15463693, 0.14486608, 0.13966955, 0.1298867 , 0.12409254, 0.12288965, 0.10780571, 0.10559474, 0.10537479, 0.10148374, 0.10037792, 0.09754734, 0.09640686, 0.09590817, 0.09435588, 0.09198856, 0.0918662 , 0.09173656, 0.0879355 , 0.08762371, 0.08711197, 0.08627746, 0.08621041, 0.08481266, 0.08390592, 0.08365501, 0.08259587, 0.08251529, 0.08152138, 0.08019584, 0.07996205, 0.07962734, 0.07907323, 0.07718709, 0.07715672, 0.07693762, 0.07692765, 0.07642546, 0.07611038, 0.07582222, 0.0754476 , 0.07542069, 0.07490928, 0.07476845, 0.0747645 , 0.07418264, 0.07383376, 0.07275221, 0.07237192, 0.0722541 , 0.07183521, 0.07175662, 0.07174246, 0.07155806, 0.071283 , 0.0710848 , 0.07026858, 0.06924678, 0.06890308, 0.06833564, 0.06827622, 0.06769758, 0.06753176, 0.06721075, 0.0663776 , 0.06553975, 0.06466822, 0.06375053, 0.06349288, 0.0633459 , 0.06320453, 0.06309631, 0.06307632, 0.06258182, 0.06233004, 0.06231011, 0.06228941, 0.06161467, 0.06125913, 0.06117567, 0.06101252, 0.06089024, 0.0608751 , 0.06063354, 0.06047466, 0.06046106, 0.0603817 , 0.06035899, 0.06034132, 0.06016544]], dtype=float32)我想知道如何获取这些分数所代表的对象类别，我在任何变量中似乎都找不到。这里是返回的列表:
print(locals().keys())dict_keys(['__name__', '__builtin__', '__builtins__', '_ih', '_oh', '_dh', 'In', 'Out', 'get_ipython', 'exit', 'quit', '_i', '_ii', '_iii', '_i52', 'np', 'os', 'urllib', 'sys', 'tarfile', 'tf', 'zipfile', 'defaultdict', 'StringIO', 'plt', 'Image', 'total_count', 'label_map_util', 'vis_util', 'MODEL_NAME', 'MODEL_FILE', 'DOWNLOAD_BASE', 'PATH_TO_CKPT', 'PATH_TO_LABELS', 'NUM_CLASSES', 'opener', 'tar_file', 'file', 'file_name', 'detection_graph', 'od_graph_def', 'fid', 'serialized_graph', 'label_map', 'categories', 'category_index', 'load_image_into_numpy_array', 'PATH_TO_TEST_IMAGES_DIR', 'TEST_IMAGE_PATHS', 'IMAGE_SIZE', 'sess', 'image_tensor', 'detection_boxes', 'detection_scores', 'detection_classes', 'num_detections', 'image_path', 'image', 'image_np', 'image_np_expanded', 'boxes', 'scores', 'classes', 'num',这是使用了github上object_detection教程中的主要教程脚本，可以在这里找到: https://github.com/tensorflow/models/tree/master/research/object_detection
任何帮助都将不胜感激。谢谢，
回答：
我猜你指的是这个笔记本。
我查看了代码，分数数组表示每个检测框的置信度。每个框的类别在classes变量中（detection_classes:0张量）。
这行代码将输入通过网络运行:
(boxes, scores, classes, num) = sess.run( [detection_boxes, detection_scores, detection_classes, num_detections], feed_dict={image_tensor: image_np_expanded})为了打印类别和分数，你可以:
for class, score in zip(classes, scores): print(class, ':', score)笔记本中使用的类别描述在这里（mscoco标签）:https://github.com/tensorflow/models/blob/master/research/object_detection/data/mscoco_label_map.pbtxt
