Image rotation and zoom in SciPy - Step-by-Step Execution

Concept Flow - Image rotation and zoom

Load Image Data

↓

Apply Rotation

↓

Apply Zoom

↓

Output Transformed Image

The image is first loaded, then rotated by a given angle, followed by zooming in or out, resulting in a transformed image.

Execution Sample

SciPy

from scipy.ndimage import rotate, zoom
import numpy as np

image = np.array([[1,2],[3,4]])
rotated = rotate(image, 90, reshape=False)
zoomed = zoom(rotated, 2)

This code rotates a 2x2 image by 90 degrees and then zooms it by a factor of 2.

Execution Table

Step	Action	Input Shape	Parameters	Output Shape	Output Snapshot
1	Load Image	-	-	(2, 2)	[[1, 2], [3, 4]]
2	Rotate Image	(2, 2)	angle=90, reshape=False	(2, 2)	[[2, 4], [1, 3]]
3	Zoom Image	(2, 2)	zoom=2	(4, 4)	[[2, 2, 4, 4], [2, 2, 4, 4], [1, 1, 3, 3], [1, 1, 3, 3]]

💡 All transformations applied; final image shape is (4,4)

Variable Tracker

Variable	Start	After Rotation	After Zoom
image	[[1, 2], [3, 4]]	[[1, 2], [3, 4]]	[[1, 2], [3, 4]]
rotated	N/A	[[2, 4], [1, 3]]	[[2, 4], [1, 3]]
zoomed	N/A	N/A	[[2, 2, 4, 4], [2, 2, 4, 4], [1, 1, 3, 3], [1, 1, 3, 3]]

Key Moments - 3 Insights

Why does the rotated image still have shape (2, 2) after a 90-degree rotation?

Because the input image is square (2x2), rotating by 90 degrees swaps rows and columns but the shape remains (2, 2), as shown in step 2 of the execution_table.

Why does the zoomed image shape become (4, 4) after zooming by 2?

Zooming by a factor of 2 doubles each dimension, so (2, 2) becomes (4, 4), as shown in step 3 of the execution_table.

What does the output snapshot represent after zooming?

It shows the pixel values repeated to enlarge the image, visually confirming the zoom effect, as seen in the last row of the execution_table.

Visual Quiz - 3 Questions

Look at the execution_table at step 2. What is the rotated image's shape?

A (1, 2)

B (4, 4)

C (2, 2)

D (3, 3)

💡 Hint

Check the 'Output Shape' column at step 2 in the execution_table.

At which step does the image shape change from (2, 2) to (4, 4)?

A Step 3

B Step 1

C Step 2

D No shape change

💡 Hint

Look at the 'Output Shape' column in the execution_table for each step.

If the zoom factor was changed to 3, what would be the new output shape after zooming?

A (9, 9)

B (6, 6)

C (3, 3)

D (2, 2)

💡 Hint

Zoom multiplies each dimension by the zoom factor; see variable_tracker for zoom effect.

Concept Snapshot

Image rotation and zoom with scipy.ndimage:
- Use rotate(image, angle, reshape=False) to rotate without changing shape.
- Use zoom(image, factor) to resize.
- Rotation keeps shape for square images when reshape=False.
- Zoom multiplies image dimensions.
- Output is a transformed numpy array.

Full Transcript

This visual execution trace shows how an image represented as a 2x2 numpy array is first rotated by 90 degrees using scipy.ndimage.rotate with reshape=False, which keeps the shape the same because the image is square. Then, the rotated image is zoomed by a factor of 2 using scipy.ndimage.zoom, which doubles each dimension, resulting in a 4x4 image. The execution table details each step's input and output shapes and shows the pixel values before and after transformations. The variable tracker follows the changes in variables image, rotated, and zoomed. Key moments clarify common confusions about shape changes during rotation and zoom. The quiz tests understanding of these transformations and their effects on image shape.