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| 1 | +--- |
| 2 | +Title: '.getextrema()' |
| 3 | +Description: 'Returns the minimum and maximum pixel values for each band in an image.' |
| 4 | +Subjects: |
| 5 | + - 'Computer Science' |
| 6 | + - 'Data Visualization' |
| 7 | +Tags: |
| 8 | + - 'Images' |
| 9 | + - 'Methods' |
| 10 | + - 'Pillow' |
| 11 | + - 'Python' |
| 12 | +CatalogContent: |
| 13 | + - 'learn-python-3' |
| 14 | + - 'paths/computer-science' |
| 15 | +--- |
| 16 | + |
| 17 | +The **`.getextrema()`** method in the Pillow library quickly finds the minimum and maximum (darkest and brightest) pixel values in an image, showing the range of pixel intensities present. |
| 18 | + |
| 19 | +## Syntax |
| 20 | + |
| 21 | +```pseudo |
| 22 | +Image.getextrema() |
| 23 | +``` |
| 24 | + |
| 25 | +**Return value:** |
| 26 | + |
| 27 | +- **For single-band images (e.g., grayscale):** Returns a tuple `(min, max)` showing the darkest and brightest pixel values. |
| 28 | +- **For multi-band images (e.g., RGB or RGBA):** Returns a tuple of tuples like `((min_R, max_R), (min_G, max_G), (min_B, max_B))`, providing the minimum and maximum values for each color channel separately. |
| 29 | + |
| 30 | +## Example |
| 31 | + |
| 32 | +The image used in the example is: |
| 33 | + |
| 34 | + |
| 35 | + |
| 36 | +The following example demonstrates the usage of the `.getextrema()` method: |
| 37 | + |
| 38 | +```py |
| 39 | +from PIL import Image |
| 40 | + |
| 41 | +# Open the image file |
| 42 | +cute_dog_image = Image.open("funny_husky.jpg") |
| 43 | + |
| 44 | +# Get extrema for the image |
| 45 | +extrema = cute_dog_image.getextrema() |
| 46 | + |
| 47 | +print("Extrema of the image:", extrema) |
| 48 | +``` |
| 49 | + |
| 50 | +Here is the output generated by this code: |
| 51 | + |
| 52 | +```shell |
| 53 | +Extrema of the image: ((0, 255), (0, 255), (0, 255)) |
| 54 | +``` |
| 55 | + |
| 56 | +### Usefulness of `.getextrema()` |
| 57 | + |
| 58 | +- **Quick Overview of Pixel Value Range:** It provides a quick way to understand the overall contrast or brightness spread in an image. For example, if the extrema of a grayscale image are `(10, 245)`, this means the darkest pixel has a value of `10`, and the brightest pixel has a value of `245`, giving an insight into the image's contrast. |
| 59 | + |
| 60 | +- **Preprocessing and Analysis:** Knowing the pixel value range is useful for several image processing tasks, such as: |
| 61 | + - Adjusting contrast to enhance image features. |
| 62 | + - Performing thresholding to segment objects based on pixel intensity. |
| 63 | + - Identifying potential saturation issues or underexposure in the image. |
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