HoG (Histogram of Oriented Gradients)
Visualize HoG feature descriptors commonly used for object detection and recognition.
Usage
import cv2
import imvf
# Load image
image = cv2.imread("path/to/image.jpg")
# Create visualizer
visualizer = imvf.HoGVisualizer()
# Apply visualization
result = visualizer(image)
# Display result
cv2.imshow("HoG Features", result.hog)
cv2.waitKey(0)
Result Structure
The HogResult dataclass contains:
hog: HoG feature visualization
What is HoG?
HoG (Histogram of Oriented Gradients) is a feature descriptor used in computer vision for object detection. It:
- Divides the image into small cells
- Computes gradient histograms for each cell
- Normalizes across blocks of cells
- Creates a feature vector describing the image
Use Cases
- Object detection (pedestrians, vehicles, etc.)
- Shape recognition
- Image classification
- Feature extraction for machine learning
See Also
- API Reference - Complete API documentation
- HogResult - Result type details
- scikit-image HoG documentation