Computer Vision Nanodegree:

Computer Vision Nanodegree Notes and Projects Computer Vision Nanodegree.

Nanodegree Overview:

For more details about the program please have a look at the Nanodegree Syllabus or visit Computer Vision Nanodegree.

Projects:

	P1: Facial Keypoints Detection Use image processing techniques and deep learning techniques to detect faces in an image and find facial keypoints, such as the position of the eyes, nose, and mouth on a face.
	P2: Image Captioning Combine image processing and deep learning knowledge to create CNN-RNN model that will be trained on the COCO image dataset to produce captions given an input images.

Notes:

	Module 1: Classical Computer Vision Utilise basic Classical Computer Vision techniques such as Image Filtering, Masking, Canny Edge Detection, Hough Lines, Fast Fourier Transform.
	PyTorch Templates - CNN MNIST TODO

Setup:

Setup conda environment for Computer Vision Nanodegree using official guide or instruction below:

# 1. Create conda environment and activate it
conda create --name cv-nd python=3.6
activate cv-nd

# 2. Add environment to Jupyter Kernels:
conda install pip
conda install ipykernel
python -m ipykernel install --user --name <cv-nd> --display-name "<cv-nd>"

# 3. Install PyTorch and OpenCV
pip install opencv-python
conda install -c pytorch pytorch
conda install -c pytorch torchvision

# 4. Install other required packages:
pip install -r requirements.txt