Update README.md

README.md

@@ -18,10 +18,10 @@ Therefore, I painstakingly labeled each and every image using RectLabel on my Ma
 
 Though I'd planned for 500 epochs, it ended early and determined that the best was at the 93rd epoch.
 
-I included a lot of my own generated images, as well as some stock images; anime, 3D models, and realistic images; male and female, varying skin tones, and various footwear configurations as well as barefoot images. That being said, there are some things it still cannot handle well, such as unconventional poses (like images rotated by 90 degrees), and images where the foot is the subject of composition. My guess is because the vast majority of the training images were of that with the feet taking up a small percentage of the canvas, not enough training was dedicated for closeups of feet. On the other hand, my intent was to use this model to refine the feet that isn't the focus.
+I included a lot of my own generated images, as well as some stock images; anime, 3D models, and realistic images; male and female, varying skin tones, and various footwear configurations as well as barefoot images. That being said, there are some things it still cannot handle well, such as unconventional poses (like images rotated by 90 degrees), and images where the foot is the subject of composition. My guess is because the vast majority of the training images were of that with the feet taking up a small percentage of the canvas, not enough training was dedicated for closeups of feet. On the other hand, my intent was to use this model to refine feet that would otherwise be neglected, as is the case when standing full body images in landscape are involved.
 
 ### Version 2.0
-V2 was done as a result of me noticing that I mislabeled my training/validation folders (i.e. my training folder was actually my validation folder, and vice-versa). So, I renamed the folders to what they're supposed to be, and I migrated a few of the images from the validation folder into the training folder, and added ~160 new images into the training dataset. I set the epochs for 200, but it determined that epoch no.
+V2 was done as a result of me noticing that I mislabeled my training/validation folders for v1.0 (i.e. my training folder was actually my validation folder, and vice-versa). So, I renamed the folders to what they're supposed to be, and I migrated a few of the images from the validation folder into the training folder, and added ~160 new images into the training dataset. I set the epochs for 200, but it determined that epoch no.
 148 was the best, so this is what it is.
 
 All the images below were detected with this version 2 model.