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6 changes: 3 additions & 3 deletions docs/yolo/yolo.rst
Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ You can print them to the console with::
ln = net.getLayerNames()
print(len(ln), ln)

The 524 elements consist of convolutional layers (``conv``),
The 254 elements consist of convolutional layers (``conv``),
rectifier linear units (``relu``) etc.::

254 ['conv_0', 'bn_0', 'relu_0', 'conv_1', 'bn_1', 'relu_1', 'conv_2', 'bn_2',
Expand All @@ -62,7 +62,7 @@ It has the following parameters:
* the **scale** factor (1/255 to scale the pixel values to [0..1])
* the **size**, here a 416x416 square image
* the **mean** value (default=0)
* the option **swapBR=True** (since OpenCV uses BGR)
* the option **swapRB=True** (since OpenCV uses BGR)

A blob is a 4D numpy array object (images, channels, width, height).
The image below shows the red channel of the blob.
Expand Down Expand Up @@ -148,4 +148,4 @@ Sources
Tutorials:

* https://www.pyimagesearch.com/2017/08/21/deep-learning-with-opencv/
* https://www.learnopencv.com/deep-learning-based-object-detection-using-yolov3-with-opencv-python-c/
* https://www.learnopencv.com/deep-learning-based-object-detection-using-yolov3-with-opencv-python-c/