5. OpenCV Tutorial - Learn Classic Computer Vision & Face Detection (OPTIONAL)/11. Image Translations - Moving Images Up, Down. Left And Right.srt

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So let's talk a bit about transitions.

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Transitions are actually very simple and it's basically moving an image in one direction can be left

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right up down or even diagonally.

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If you implement an x and y traslation at the same time.

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So to perform a translation we actually use Open see these C-v to walk a fine function but that function

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requires what we call the translation matrix.

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So we are getting into too much high school geometry a translation matrix basically is is in this form

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and takes an x and y value as these elements here.

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Now what misrepresents here is a shift along the x axis horizontally and Y is shift along the y axis

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vertically.

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And these are the directions each shift takes place.

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So images all the start of being at the top left corner and retranslated in any direction using the

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transition matrix here.

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So let's implement this and quite quickly.

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So let's implement transitions using open C-v now.

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So we're going through line by line.

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I'll quickly show you what's being done here.

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The important thing to note is that are using to see V2 warp and function.

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And that's been implemented down here so quickly going through the image as we've done before we extract

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the height and the width of the image using non-pay see function taking only the first two elements

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of the ship three that it retains.

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Next I have a line here where we extract quarter of the height and width of do it.

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That's going to be a T x and y value in our translation Matrix.

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That's the direction or sorry the amount of pixels we're going to shift to image.

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And we actually use not by fluke to the two that actually defines the read data type for where translations

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matrix.

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And by using some square brackets here we actually created a T matrix here.

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It may or may not be important for you understand this but just take note of the form of this t matrix

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here.

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So the warp find function takes away image.

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So if we look at it in the matrix that we created and all within a height as a table and it actually

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returns the translated image.

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So let's actually run this and see what it looks like.

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Tulla this is a translated image here as you can see it's shifted image of an extraction a quarter of

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the initial dimensions.

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And similarly for the White image and we're just done with.

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So it's important to know that we should just take a look at a T matrix to give give you an understanding

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of what we have done here.

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So this is exactly what we wanted in 0 2 metrics.

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It's 1 0 in disorder anti-X and the way this being a quarter of the height and a quarter of the weight

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respectively.