Virando tudo

Como brincadeira, alguém deixou uma foto de uma viagem a Sevilha de cabeça para baixo e espelhada! Agora precisamos endireitar a imagem, invertendo-a.

Cidade de Sevilha de cabeça para baixo

Imagem carregada como flipped_seville. Usando os métodos do NumPy aprendidos no curso, inverta a imagem horizontal e verticalmente. Em seguida, exiba a imagem corrigida usando a função show_image().

NumPy já está importado como np.

Este exercicio faz parte do curso

Processamento de Imagens em Python

exercicio interativo prático

Tente este exercicio completando este código de exemplo.

# Flip the image vertically
seville_vertical_flip = ____.____(flipped_seville)

Editar e Executar Código

Este exercicio faz parte do curso

Processamento de Imagens em Python

IntermediárioNível de habilidade

4.8+

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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: Dê vida às imagens com scikit-image Exercise 2: Esta é cinza ou cheia de cor?Exercise 3: RGB para tons de cinza Exercise 4: NumPy para imagens Exercise 5: Virando tudo

Exercicio Atual

Exercise 6: Histogramas Exercise 7: Começando com limiarização Exercise 8: Aplicar limiarização global Exercise 9: Quando o plano de fundo não é tão óbvio Exercise 10: Testando outros métodos Exercise 11: Aplicar limiarização

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: Finding the edges with Canny Exercise 2: Edges Exercise 3: Less edgy Exercise 4: Right around the corner Exercise 5: Perspective Exercise 6: Less corners Exercise 7: Face detection Exercise 8: Is someone there?Exercise 9: Multiple faces Exercise 10: Segmentation and face detection Exercise 11: Real-world applications Exercise 12: Privacy protection Exercise 13: Help Sally restore her graduation photo Exercise 14: Amazing work!