Update README.md

 (5*2 + number_of_classes)*7*7, as an example, assuming no other parameters are modified.

README.md

@@ -52,7 +52,9 @@ For questions or issues please use the [Google Group](https://groups.google.com/
    (2) In [src/yolo_kernels.cu](https://github.com/Guanghan/darknet/blob/master/src/yolo_kernels.cu), change class numbers.
 
    (3) Now we are able to train with new classes, but there is one more thing to deal with. In YOLO, the number of parameters of the second last layer is not arbitrary, instead it is defined by some other parameters including the number of classes, the side(number of splits of the whole image). Please read [the paper](http://arxiv.org/abs/1506.02640)  
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+       (5*2 + number_of_classes)*7*7, as an example, assuming no other parameters are modified.  
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        Therefore, in [cfg/yolo.cfg](https://github.com/Guanghan/darknet/blob/master/cfg/yolo.cfg), change the "output" in line 218, and "classes" in line 222.
 
    (4) Now we are good to go. If we need to change the number of layers and experiment with various parameters, just mess with the cfg file. For the original yolo configuration, we have the [pre-trained weights](http://pjreddie.com/media/files/extraction.conv.weights) to start from. For arbitrary configuration, I'm afraid we have to generate pre-trained model ourselves.