update

README.md

@@ -76,6 +76,16 @@ in which each node of the hierarchy is depicted by hundreds and thousands of ima
 The project has been instrumental in advancing computer vision and deep learning research.   
 The data is available for free to researchers for non-commercial use.  
 ```
+### 4、Stanford_Cars 数据集
+* [数据集下载地址(百度网盘 Password: txtu )](https://pan.baidu.com/s/1DR9ANGqFS6z90yzU6nlIoA)
+* Stanford_Cars官网地址：http://ai.stanford.edu/~jkrause/cars/car_dataset.html
+```
+ 3D Object Representations for Fine-Grained Categorization
+ Jonathan Krause, Michael Stark, Jia Deng, Li Fei-Fei
+ 4th IEEE Workshop on 3D Representation and Recognition, at ICCV 2013 (3dRR-13). Sydney, Australia. Dec. 8, 2013.
+       
+ Note that the dataset, as released, has 196 categories, one less than in the paper, as it has been cleaned up slightly since publication. Numbers should be more or less comparable, though.
+```
 
 ### 构建自己的数据集  
 * 构建一个总的数据集目录，在目录内建立每一个具体类别的子目录，每一个子目录有且只有单独的一个类别。并且文件夹的命名为“数字-名称”，比如上图的“one静态手势”的文件夹命名为“000-one”。  
@@ -94,6 +104,9 @@ The data is available for free to researchers for non-commercial use.
 * 具体分类看json信息即"imagenet_msg.json"，运行 [read_imagenet_msg.py](https://codechina.csdn.net/EricLee/classification/-/blob/master/imagenet/read_imagenet_msg.py) 读取。
 * "chinese_name"为类别中文名字，"doc_name"为数据集对应的每一类文件夹名字，前面的数字为模型的类别号从 "0"~"999"，共 1000 类 。
 
+### 4、Stanford_Cars 预训练模型
+* [预训练模型下载地址(百度网盘 Password: 7bf7 )](https://pan.baidu.com/s/1JY_ia48e92am6JJ_p-kgQg)
+
 ## 项目使用方法  
 ### 模型训练  
    注意: train.py 中的 3个参数与具体分类任务数据集，息息相关，如下所示：