Moins d’arêtes

Essayons maintenant de ne repérer que la forme extérieure des pamplemousses, c’est‑à‑dire les cercles. Pour cela, appliquez un filtre gaussien plus fort afin de lisser davantage l’image. Vous pouvez y parvenir en indiquant un sigma plus élevé dans la fonction canny.

Dans cet exercice, vous allez tester différentes valeurs de sigma de la fonction canny().

Grapefruits

Image préchargée sous le nom grapefruit.

La fonction show_image est déjà préchargée.

Cet exercice fait partie du cours

<cours>Traitement d’images en Python</cours>

Exercice interactif pratique

Essayez cet exercice en complétant ce code d’exemple.

# Apply canny edge detector with a sigma of 1.8
canny_edges = canny(grapefruit, sigma=____)

Modifier et exécuter le code

Cet exercice fait partie du cours

<cours>Traitement d’images en Python</cours>

IntermédiaireNiveau de compétence

4.8+

Commencer le cours gratuitement

Jump into digital image structures and learn to process them! Extract data, transform and analyze images using NumPy and Scikit-image. With just a few lines of code, you will convert RGB images to grayscale, get data from them, obtain histograms containing very useful information, and separate objects from the background!

Exercise 1: Make images come alive with scikit-image Exercise 2: Is this gray or full of color?Exercise 3: RGB to grayscale Exercise 4: NumPy for images Exercise 5: Flipping out Exercise 6: Histograms Exercise 7: Getting started with thresholding Exercise 8: Apply global thresholding Exercise 9: When the background isn't that obvious Exercise 10: Trying other methods Exercise 11: Apply thresholding

You will learn to <strong>detect object shapes</strong> using edge detection filters, <strong>improve medical images</strong> with contrast enhancement <strong>and even enlarge pictures to five times its original size! </strong> You will also apply morphology to make thresholding more accurate when segmenting images and go to the next level of processing images with Python.

Exercise 1: Jump into filtering Exercise 2: Edge detection Exercise 3: Blurring to reduce noise Exercise 4: Contrast enhancement Exercise 5: What's the contrast of this image?Exercise 6: Medical images Exercise 7: Aerial image Exercise 8: Let's add some impact and contrast Exercise 9: Transformations Exercise 10: Aliasing, rotating and rescaling Exercise 11: Enlarging images Exercise 12: Proportionally resizing Exercise 13: Morphology Exercise 14: Handwritten letters Exercise 15: Improving thresholded image

So far, you have done some very cool things with your image processing skills! In this chapter, you will apply <strong>image restoration to remove objects, logos, text, or damaged areas</strong> in pictures! You will also learn how to apply noise, use segmentation to speed up processing, and find elements in images by their contours.

Exercise 1: Image restoration Exercise 2: Let's restore a damaged image Exercise 3: Removing logos Exercise 4: Noise Exercise 5: Let's make some noise!Exercise 6: Reducing noise Exercise 7: Reducing noise while preserving edges Exercise 8: Superpixels & segmentation Exercise 9: Number of pixels Exercise 10: Superpixel segmentation Exercise 11: Finding contours Exercise 12: Contouring shapes Exercise 13: Find contours of an image that is not binary Exercise 14: Count the dots in a dice's image

After completing this chapter, you will have a deeper knowledge of image processing as you will be able to <strong>detect edges, corners, and even faces! </strong> You will learn how to detect not just front faces but also face profiles, cat, or dogs. You will apply your skills to more complex <strong>real-world applications.</strong> Learn to master several widely used image processing techniques with very few lines of code!

Exercise 1: Détecter les contours avec Canny Exercise 2: Contours Exercise 3: Moins d’arêtes

Exercice actuel

Exercise 4: Juste au coin de la rue Exercise 5: Perspective Exercise 6: Moins d’angles Exercise 7: Détection de visages Exercise 8: Y a-t-il quelqu’un ?Exercise 9: Visages multiples Exercise 10: Segmentation et détection de visages Exercise 11: Applications concrètes Exercise 12: Protection de la vie privée Exercise 13: Aidez Sally à restaurer sa photo de remise de diplôme Exercise 14: Excellent travail !