CV Capstone Project

Submission Files

CV_project.ipynb --> all required python functions are completed in the main notebook. CV_project.ipynb TODO items should all be completed.

Add eye detections to the current face detection setup.

The submission returns proper code detecting and marking eyes in the given test image.

De-noise an image for better face detection.

The submission completes de-noising of the given noisy test image with perfect face detections then performed on the cleaned image.

Blur and edge detect a test image.

The submission returns an edge-detected image that has first been blurred, then edge-detected, using the specified parameters.

Find and blur the face of an individual in a test image.

The submission should provide code to automatically detect the face of a person in a test image, then blur their face to mask their identity.

Specify a convolutional network architecture for learning correspondence between input faces and facial keypoints.

The submission successfully provides code to build an appropriate convolutional network.

Compile and train the CNN for facial keypoint detection.

The submission successfully compiles and trains the CNN.

Answer a few questions about your training and visualize the loss function.

The submission successfully discusses any potential issues with their training, and answers all of the provided questions.

Combine OpenCV face detection with your trained CNN facial keypoint detector.

The submission successfully combines OpenCV's pre-processing techniques and face detection with a trained CNN keypoint detector.