Update README.md

README.md

@@ -108,17 +108,17 @@ A data point comprises an image and its face and license plate annotations.
 #### Initial Data Collection and Normalization
 
 The objective of PP4AV is to build a benchmark dataset that can be used to evaluate face and license plate detection models for autonomous driving. For normal camera data, we sampled images from the existing videos in which cameras were mounted in moving vehicles, running around the European cities. We focus on sampling data in urban areas rather than highways in order to provide sufficient samples of license plates and pedestrians. The images in PP4AV were sampled from **6** European cities at various times of day, including nighttime. The source data from 6 cities in European was described as follow:
-  - `Paris`: This subset contains **1450** images of the car driving down a Parisian street during the day. The video frame rate is 30 frames per second. Due to the video is longer than one hour, we cut a shorter video for sampling and annotation. The original video can be found at the following URL:
+  - `Paris`: This subset contains **1450** images of the car driving down a Parisian street during the day. The video frame rate is 30 frames per second. The video is longer than one hour. We cut a shorter video for sampling and annotation. The original video can be found at the following URL:
     URL: [paris_youtube_video](https://www.youtube.com/watch?v=nqWtGWymV6c)  
   - `Netherland day time`: This subset consists of **388** images of Hague, Amsterdam city in day time. The image of this subset are sampled from the bellow original video:  
     URL: [netherland_youtube_video](https://www.youtube.com/watch?v=Xuo4uCZxNrE)  
-    The frame rate of the video is 30 frames per second. We cut a shorter video for sampling and annotation because the video was longer than one hour.
+    The frame rate of the video is 30 frames per second. We cut a shorter video for sampling and annotation. The original video was longer than a half hour.
   - `Netherland night time`: This subset consists of **824** images of Hague, Amsterdam city in night time sampled by the following original video:   
     URL: [netherland_youtube_video](https://www.youtube.com/watch?v=eAy9eHsynhM)  
-    The frame rate of the video is 30 frames per second. We cut a shorter video for sampling and annotation because the video was longer than one hour.
+    The frame rate of the video is 30 frames per second. We cut a shorter video for sampling and annotation. The original video was longer than a half hour.
   - `Switzerland`: This subset consists of **372** images of Switzerland sampled by the following video:   
     URL: [switzerland_youtube_video](https://www.youtube.com/watch?v=0iw5IP94m0Q)  
-    The frame rate of the video is 30 frames per second. We cut a shorter video for sampling and annotation because the video was longer than one hour.
+    The frame rate of the video is 30 frames per second. We cut a shorter video for sampling and annotation. The original video was longer than one hour.
   - `Zurich`: This subset consists of **50** images of Zurich city provided by the Cityscapes training set in package [leftImg8bit_trainvaltest.zip](https://www.cityscapes-dataset.com/file-handling/?packageID=3)
   - `Stuttgart`: This subset consists of **69** images of Stuttgart city provided by the Cityscapes training set in package [leftImg8bit_trainvaltest.zip](https://www.cityscapes-dataset.com/file-handling/?packageID=3)
   - `Strasbourg`: This subset consists of **50** images of Strasbourg city provided by the Cityscapes training set in package [leftImg8bit_trainvaltest.zip](https://www.cityscapes-dataset.com/file-handling/?packageID=3)