/DMDK1001_Group_Project

Data Mining and Knowledge Discovery (1001) Group Project

Primary LanguagePythonMIT LicenseMIT

DMDK1001_Group_Project

Data Mining and Knowledge Discovery (1001) Group Project

1. Project Question

2. Using Package

  • NumPy

  • Opencv-python

  • Matplotlib

3. Install Project

git clone (project repo name)
conda create -n md python=3.7
conda activate md
pip install -r requirements.txt

4. Using Project

4.1 Using cv2 Kmeans Method

python main.py --img (str) --clustersNum (int)

# Easy Example
python main.py

4.2 Using Our Numpy-made Kmeans Methods

python run.py --img (str) --clustersNum (int)

# Easy Example
python run.py

4.3 Using Sklearn Kmeans Method

python sklearn_kmeans.py

4.4 Confusion Matrix for Evaluation

python eval.py --img (str) (str)

5. Example Result

5.1 cv2 Kmeans Method Result (3 clusters)

example.jpeg

5.2 Ours Restult (2 clusters)

ours_res_example.jpeg

5.3 Sklearn Kmeans Result (3 clusters)

sklearn_res_example.jpeg

6. Acknowledgement

The implementation took reference from [Opencv K-Means Clusters](K-Means Clustering in OpenCV — OpenCV-Python Tutorials beta documentation), Numpy, [Sklearn](sklearn.cluster.KMeans — scikit-learn 1.1.3 documentation)

We thank the authors for their generosity to release code.