Update README.md

README.md

@@ -48,7 +48,7 @@ The mAP results are subject to random variations, which we estimate are ~0.5% mA
 ### Requirements: software
 
 0. `Caffe` build for Faster R-CNN (included in this repository, see `external/caffe`)
-    - If you are using Windows, you may download a compiled mex file by running `fetch_data/fetch_caffe_library.m`
+    - If you are using Windows, you may download a compiled mex file by running `fetch_data/fetch_caffe_mex_windows_vs2013_cuda65.m`
     - If you are using Linux or you want to compile for Windows, please follow the [instructions](https://github.com/ShaoqingRen/caffe/tree/faster-R-CNN) on our Caffe branch.
 0.	MATLAB
 
@@ -66,13 +66,13 @@ GPU: Titan, Titan Black, Titan X, K20, K40, K80.
 
 
 ### Preparation for Testing:
-0.	Run `fetch_data/fetch_caffe_library.m` to download a compiled Caffe mex (for Windows only).
+0.	Run `fetch_data/fetch_caffe_mex_windows_vs2013_cuda65.m` to download a compiled Caffe mex (for Windows only).
 0.	Run `faster_rcnn_build.m`
 0.	Run `startup.m`
 
 
 ### Testing Demo:
-0.	Run `fetch_data/fetch_model_trained.m` to download our trained models.
+0.	Run `fetch_data/fetch_faster_rcnn_final_model.m` to download our trained models.
 0.	Run `experiments/script_faster_rcnn_demo.m` to test a single demo image.
     - The first run might be slower due to memory load.
     - The running time on K40 of this code is about 220ms/image, 10% more than we reported in the paper. This is because of unknown issues when we switch from our older version of Caffe to the newer one.
@@ -108,8 +108,10 @@ GPU: Titan, Titan Black, Titan X, K20, K40, K80.
 If the automatic "fetch_data" fails, you may manually download resouces from:
 
 0. Pre-complied caffe mex:
-    - Windows-based mex complied with VS2013 and Cuda6.5: [OneDrive](https://onedrive.live.com/download?resid=4006CBB8476FF777!17255&authkey=!AHOIeRzQKCYXD3U&ithint=file%2czip), [DropBox](https://www.dropbox.com/s/m6sg347tiaqpcwy/caffe_mex.zip?dl=0), [BaiduYun](http://pan.baidu.com/s/1nZYOI)
+    - Windows-based mex complied with VS2013 and Cuda6.5: [OneDrive](https://onedrive.live.com/download?resid=4006CBB8476FF777!17255&authkey=!AHOIeRzQKCYXD3U&ithint=file%2czip), [DropBox](https://www.dropbox.com/s/m6sg347tiaqpcwy/caffe_mex.zip?dl=0), [BaiduYun](http://pan.baidu.com/s/1i3m0i0H)
 0. ImageNet-pretrained networks:
-    - Zeiler & Fergus (ZF) net [OneDrive](https://onedrive.live.com/download?resid=4006CBB8476FF777!17256&authkey=!AF7wGc1kbUTfI7o&ithint=file%2czip), [DropBox](https://www.dropbox.com/s/sw58b2froihzwyf/model_ZF.zip?dl=0), [BaiduYun](http://pan.baidu.com/s/1sj3K21B)
-    - VGG-16 net [OneDrive](https://onedrive.live.com/download?resid=4006CBB8476FF777!17257&authkey=!AO38BiePXqYrz5M&ithint=file%2czip), [DropBox](https://www.dropbox.com/s/z5rrji25uskha73/model_VGG16.zip?dl=0), [BaiduYun](http://pan.baidu.com/s/1pJ9opyr)
-0. Final RPN+FastRCNN models: [OneDrive](https://onedrive.live.com/download?resid=4006CBB8476FF777!17292&authkey=!AFCIads9CKr5-4s&ithint=file%2czip), [DropBox](https://www.dropbox.com/s/jswrnkaln47clg2/faster_rcnn_final_model.zip?dl=0), [BaiduYun](http://pan.baidu.com/s/1eQwF64y)
+    - Zeiler & Fergus (ZF) net [OneDrive](https://onedrive.live.com/download?resid=4006CBB8476FF777!17255&authkey=!AHOIeRzQKCYXD3U&ithint=file%2czip), [DropBox](https://www.dropbox.com/s/sw58b2froihzwyf/model_ZF.zip?dl=0), [BaiduYun](http://pan.baidu.com/s/1sj3K21B)
+    - VGG-16 net [OneDrive](https://onedrive.live.com/download?resid=4006CBB8476FF777!17319&authkey=!APSc546R6TbCCl4&ithint=file%2czip), [DropBox](https://www.dropbox.com/s/z5rrji25uskha73/model_VGG16.zip?dl=0), [BaiduYun](http://pan.baidu.com/s/1dDoAna5)
+0. Final RPN+FastRCNN models: [OneDrive](https://onedrive.live.com/download?resid=4006CBB8476FF777!17292&authkey=!AFCIads9CKr5-4s&ithint=file%2czip), [DropBox](https://www.dropbox.com/s/jswrnkaln47clg2/faster_rcnn_final_model.zip?dl=0), [BaiduYun](http://pan.baidu.com/s/1hq2brlq)
+
+