MIT Cars 数据集标签问题求助
第一张图是打开数据集标签的时候的数据，一共有1万多条，每条对应一张车的图片的数据（车的图片就不贴出来了）第二张图是我打开的代码
第三张图片是另外的一个配送的文件，里面有车的类型（都是截取部分的数据）
再下面呢是我下载的官网https://ai.stanford.edu/~jkrause/cars/car_dataset.html
再下面是官官方的说明文档：
This file gives documentation for the cars 196 dataset.
(http://ai.stanford.edu/~jkrause/cars/car_dataset.html)
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Metadata/Annotations
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Descriptions of the files are as follows:
-cars_meta.mat:
Contains a cell array of class names, one for each class.
-cars_train_annos.mat:
Contains the variable 'annotations', which is a struct array of length
num_images and where each element has the fields:
bbox_x1: Min x-value of the bounding box, in pixels
bbox_x2: Max x-value of the bounding box, in pixels
bbox_y1: Min y-value of the bounding box, in pixels
bbox_y2: Max y-value of the bounding box, in pixels
class: Integral id of the class the image belongs to.
fname: Filename of the image within the folder of images.
-cars_test_annos.mat:
Same format as 'cars_train_annos.mat', except the class is not provided.
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Submission file format
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Files for submission should be .txt files with the class prediction for
image M on line M. Note that image M corresponds to the Mth annotation in
the provided annotation file. An example of a file in this format is
train_perfect_preds.txt
Included in the devkit are a script for evaluating training accuracy,
eval_train.m. Usage is:
(in MATLAB)
>> = eval_train('train_perfect_preds.txt')
If your training predictions work with this function then your testing
predictions should be good to go for the evaluation server, assuming
that they're in the same format as your training predictions.
我需要求助的问题是：每张车的图片都有对应的数据标签，但是在标签里面没有找到车的类型（可能我不会看，这才是关键），理论上应该都有的（因为这个数据集是公开的神经网络训练的图片），看了老半天，就六个数据怎么都和车的类型对不上，有用过这个数据集的朋友帮帮忙或者能看懂的朋友发表一下见解，谢谢了。
{:10_249:}看看
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