Drawing circles on an image with Matplotlib and NumPy

Drawing circles on an image combines image processing with matplotlib's patch functionality. This technique is useful for highlighting regions of interest, marking detected objects, or creating visual annotations.

Basic Circle Drawing

Here's how to draw circles on a sample image using matplotlib patches ?

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Circle

# Set figure size and layout
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# Read an image from file
img = plt.imread('bird.jpg')

# Generate random positions for circles
x = np.random.rand(5) * img.shape[1]
y = np.random.rand(5) * img.shape[0]

# Create figure and axis
fig, ax = plt.subplots(1)

# Display the image
ax.imshow(img)
ax.axis('off')

# Add circles at random positions
for xx, yy in zip(x, y):
    circ = Circle((xx, yy), 50, color='red')
    ax.add_patch(circ)

plt.show()

Creating a Synthetic Image Example

Let's create a complete example using a synthetic image that can run without external files ?

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Circle

# Create a synthetic image (gradient background)
height, width = 300, 400
img = np.zeros((height, width, 3))
for i in range(height):
    for j in range(width):
        img[i, j] = [i/height, j/width, 0.5]

# Define circle positions and properties
circle_data = [
    (100, 100, 30, 'red'),
    (200, 150, 40, 'blue'),
    (300, 80, 25, 'green')
]

# Create figure and axis
fig, ax = plt.subplots(figsize=(8, 6))

# Display the synthetic image
ax.imshow(img)
ax.axis('off')

# Add circles with different colors and sizes
for x, y, radius, color in circle_data:
    circle = Circle((x, y), radius, color=color, fill=False, linewidth=2)
    ax.add_patch(circle)

plt.title('Circles on Synthetic Image')
plt.show()

Circle Properties and Customization

You can customize circles with various properties ?

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Circle

# Create a simple background
img = np.ones((200, 300, 3)) * 0.8

fig, ax = plt.subplots(figsize=(8, 5))
ax.imshow(img)
ax.axis('off')

# Different circle styles
circles = [
    Circle((50, 50), 20, color='red', fill=True, alpha=0.7),      # Filled with transparency
    Circle((150, 50), 20, color='blue', fill=False, linewidth=3), # Outline only
    Circle((250, 50), 20, color='green', fill=True),              # Solid filled
    Circle((50, 150), 20, facecolor='yellow', edgecolor='black', linewidth=2), # Custom colors
    Circle((150, 150), 20, color='purple', linestyle='--', fill=False), # Dashed outline
]

for circle in circles:
    ax.add_patch(circle)

plt.title('Different Circle Styles')
plt.show()

Key Properties

Conclusion

Drawing circles on images with matplotlib is straightforward using the Circle patch class. Use add_patch() to overlay circles with customizable colors, sizes, and transparency for effective image annotation.