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fix some spelling and grammar errors
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@ -74,7 +74,7 @@
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// DNN module uses template-based network declaration that leads to very long
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// type names. Visual Studio will produce Warning C4503 in such cases. https://msdn.microsoft.com/en-us/library/074af4b6.aspx says
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// that correct binaries are still produced even when this warning happens, but linker errors from visual studio, if they occurr could be confusing.
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// that correct binaries are still produced even when this warning happens, but linker errors from visual studio, if they occur could be confusing.
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#pragma warning( disable: 4503 )
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@ -42,7 +42,7 @@ namespace dlib
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operator--(int) // post decrement
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the other comparason operators(>, !=, <=, and >=) are
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the other comparison operators(>, !=, <=, and >=) are
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available and come from the templates in dlib::relational_operators
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THREAD SAFETY
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@ -24,7 +24,7 @@ namespace dlib
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of finding which subset a particular integer belongs to as well as
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merging subsets. It also allows you to find out how big each subset is. It
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is therefore essentially the same thing as dlib::disjoint_subsets, except
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it also keeps track of of the size of each subset.
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it also keeps track of the size of each subset.
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!*/
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public:
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@ -121,7 +121,7 @@ namespace dlib
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present in the pixel at all and 255 indicating that the color
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is present in the pixel with maximum intensity.
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Note that the structure, order, and size of of this struct are
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Note that the structure, order, and size of this struct are
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implementation dependent. It will always contain fields called
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red, green, and blue but they may not be in that order and there
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may be padding.
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@ -562,7 +562,7 @@ namespace dlib
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// this case here covers the unlikly event that you click on a button,
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// move the mouse off the button and then move it back very quickly and
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// release the mouse button. It is possible that this mouse up event
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// will occurr before any mouse move event so you might not have set
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// will occur before any mouse move event so you might not have set
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// that the button is depressed yet.
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// So we should say that this triggers an on_button_down() event and
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@ -2842,7 +2842,7 @@ namespace dlib
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{
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rgb_alpha_pixel color;
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assign_pixel(color, graph_.node(i).data.color);
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// this node is in area so lets draw it and all of it's edges as well
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// this node is in area so lets draw it and all of its edges as well
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draw_solid_circle(c,center,rad-3,color,area);
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color.alpha = 240;
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draw_circle(c,center,rad-3,color,area);
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@ -39,7 +39,7 @@ namespace dlib
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That is, the output vector has a dimensionality that is equal to the number
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of hash bins times the dimensionality of the lower level vector plus one.
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The value in the extra dimension concatenated onto the end of the vector is
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always a constant value of of 1 and serves as a bias value. This means
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always a constant value of 1 and serves as a bias value. This means
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that, if there are N hash bins, these vectors are capable of representing N
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different linear functions, each operating on the vectors that fall into
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their corresponding hash bin.
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@ -428,7 +428,7 @@ namespace dlib
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dlib/image_processing/generic_image.h
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- pixel_traits<typename image_traits<image_type>::pixel_type>::has_alpha == false
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ensures
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- Resizes img so that each of it's dimensions are size_scale times larger than img.
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- Resizes img so that each of its dimensions are size_scale times larger than img.
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In particular, we will have:
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- #img.nr() == std::round(size_scale*img.nr())
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- #img.nc() == std::round(size_scale*img.nc())
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@ -1035,7 +1035,7 @@ namespace dlib
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- #angle == 0
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- #rows and #cols is set such that the total size of the chip is as close
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to size_ as possible but still matches the aspect ratio of rect_.
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- As long as size_ and the aspect ratio of of rect_ stays constant then
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- As long as size_ and the aspect ratio of rect_ stays constant then
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#rows and #cols will always have the same values. This means that, for
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example, if you want all your chips to have the same dimensions then
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ensure that size_ is always the same and also that rect_ always has the
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@ -1057,7 +1057,7 @@ namespace dlib
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- #angle == angle_
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- #rows and #cols is set such that the total size of the chip is as close
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to size_ as possible but still matches the aspect ratio of rect_.
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- As long as size_ and the aspect ratio of of rect_ stays constant then
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- As long as size_ and the aspect ratio of rect_ stays constant then
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#rows and #cols will always have the same values. This means that, for
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example, if you want all your chips to have the same dimensions then
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ensure that size_ is always the same and also that rect_ always has the
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@ -42,7 +42,7 @@ namespace dlib
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numbers and we also perform basic centering to ensure the plane passes
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though the data.
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- This function uses the supplied random number generator, rnd, to drive part
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of it's processing. Therefore, giving different random number generators
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of its processing. Therefore, giving different random number generators
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will produce different outputs.
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!*/
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@ -108,7 +108,7 @@ namespace dlib
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We train it on randomly selected and randomly labeled points from v.
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The C SVM parameter is set to the given C argument.
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- This function uses the supplied random number generator, rnd, to drive part
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of it's processing. Therefore, giving different random number generators
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of its processing. Therefore, giving different random number generators
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will produce different outputs.
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!*/
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@ -165,7 +165,7 @@ namespace dlib
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were independent events. The larger the magnitude of COR the more
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evidence we have for the correlation.
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- COR < 0: There is evidence that A and B are anti-correlated. That is,
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when A happens B is unlikely to happen and vise versa. The larger the
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when A happens B is unlikely to happen and vice versa. The larger the
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magnitude of COR the more evidence we have for the anti-correlation.
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- This function implements the simple likelihood ratio test discussed in the
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following paper:
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@ -144,7 +144,7 @@ namespace dlib
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Also note that sample risk is an upper bound on a sample's loss. So
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you can think of this epsilon value as saying "solve the optimization
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problem until the average loss per sample is within epsilon of it's
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problem until the average loss per sample is within epsilon of its
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optimal value".
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!*/
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@ -123,7 +123,7 @@ namespace dlib
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Also note that sample risk is an upper bound on a sample's loss. So
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you can think of this epsilon value as saying "solve the optimization
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problem until the average loss per sample is within epsilon of it's
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problem until the average loss per sample is within epsilon of its
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optimal value".
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!*/
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@ -692,7 +692,7 @@
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That is, the output vector has a dimensionality that is equal to the number
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of hash bins times the dimensionality of the lower level vector plus one.
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The value in the extra dimension concatenated onto the end of the vector is
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always a constant value of of 1 and serves as a bias value. This means
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always a constant value of 1 and serves as a bias value. This means
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that, if there are N hash bins, these vectors are capable of representing N
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different linear functions, each operating on the vectors that fall into
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their corresponding hash bin.
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@ -718,7 +718,7 @@ void process_file (
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if (class_stack.size() > 0 && namespaces.back() == class_stack.top().name)
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{
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// If this class is a inner_class of another then push it into the
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// public_inner_classes or protected_inner_classes field of it's containing class.
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// public_inner_classes or protected_inner_classes field of its containing class.
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if (class_stack.size() > 1)
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{
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tok_class_record temp = class_stack.top();
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@ -247,7 +247,7 @@ void register_extract_image_chip (py::module& m)
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- self.angle == 0 \n\
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- self.rows and self.cols is set such that the total size of the chip is as close \n\
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to size as possible but still matches the aspect ratio of rect. \n\
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- As long as size and the aspect ratio of of rect stays constant then \n\
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- As long as size and the aspect ratio of rect stays constant then \n\
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self.rows and self.cols will always have the same values. This means \n\
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that, for example, if you want all your chips to have the same dimensions \n\
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then ensure that size is always the same and also that rect always has \n\
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@ -261,7 +261,7 @@ void register_extract_image_chip (py::module& m)
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- self.angle == 0
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- self.rows and self.cols is set such that the total size of the chip is as close
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to size as possible but still matches the aspect ratio of rect.
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- As long as size and the aspect ratio of of rect stays constant then
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- As long as size and the aspect ratio of rect stays constant then
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self.rows and self.cols will always have the same values. This means
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that, for example, if you want all your chips to have the same dimensions
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then ensure that size is always the same and also that rect always has
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@ -278,7 +278,7 @@ void register_extract_image_chip (py::module& m)
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- self.angle == angle \n\
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- self.rows and self.cols is set such that the total size of the chip is as \n\
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close to size as possible but still matches the aspect ratio of rect. \n\
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- As long as size and the aspect ratio of of rect stays constant then \n\
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- As long as size and the aspect ratio of rect stays constant then \n\
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self.rows and self.cols will always have the same values. This means \n\
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that, for example, if you want all your chips to have the same dimensions \n\
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then ensure that size is always the same and also that rect always has \n\
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@ -292,7 +292,7 @@ void register_extract_image_chip (py::module& m)
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- self.angle == angle
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- self.rows and self.cols is set such that the total size of the chip is as
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close to size as possible but still matches the aspect ratio of rect.
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- As long as size and the aspect ratio of of rect stays constant then
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- As long as size and the aspect ratio of rect stays constant then
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self.rows and self.cols will always have the same values. This means
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that, for example, if you want all your chips to have the same dimensions
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then ensure that size is always the same and also that rect always has
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