Module 7: Machine Learning
Traditional machine learning algorithms in OpenCV for classification, regression, and clustering.
Topics Covered
- K-Nearest Neighbors (KNN)
- Support Vector Machines (SVM)
- K-Means clustering
- Decision Trees
- HOG + SVM classification
Tutorial Files
| File |
Description |
01_ml_basics.py |
KNN, SVM, K-Means, Decision Trees fundamentals |
02_digit_recognition.py |
Handwritten digit classification with real data |
03_hog_svm.py |
HOG features + SVM for pedestrian detection |
04_kmeans_segmentation.py |
Image segmentation using K-Means clustering |
Key Functions Reference
| Function |
Description |
cv2.ml.KNearest_create() |
Create KNN classifier |
cv2.ml.SVM_create() |
Create SVM classifier |
cv2.ml.DTrees_create() |
Create Decision Tree |
cv2.kmeans() |
K-Means clustering |
cv2.HOGDescriptor() |
HOG feature extraction |
model.train() |
Train model |
model.predict() |
Make predictions |
model.save() |
Save model to file |
Further Reading