As part of the Face Login system, I have access to a number of images of faces that were used to train the face recognition system. It would make sense to be able to display a profile image of the logged-in user using one of these photographs.
The plan is to upload all the images of users to Amazon S3, make each image publicly accessible, and then display the relevant image by linking to the image from the profile page of the Face Login system
Continue reading “DAT602 – Face Login – Profile Image/Amazon S3”
Having spent many hours tinkering with Amazon’s Rekognition API and making little progress, I decided to investigate the face recognition Face API provided as part of Microsoft Azure Cognitive Services (Microsoft, no date).
The API provides functionality to implement face detection (“detect one or more human faces in an image and get back face rectangles for where in the image the faces are, along with face attributes which contain machine learning-based predictions of facial features. The face attribute features available are: Age, Emotion, Gender, Pose, Smile, and Facial Hair along with 27 landmarks for each face in the image”) and face verification (“check the likelihood that two faces belong to the same person. The API will return a confidence score about how likely it is that the two faces belong to one person”).
Continue reading “DAT602 – Face Recognition with Azure Face API and Python”
The Brief: Python Webservice APIs
For the next practical exercise you must create an auto-tweet agent.
Your program should identify the most recent page viewed by your browser (by looking in either the “Current Session” or “History” file). It should then acquire the title of the page last viewed.
For example, the title of the Ebay main page is: Electronics, Cars, Fashion, Collectibles, Coupons and More | eBay.
Your program should then tweet the fact that you liked the page:
I’m really liking Electronics, Cars, Fashion, Collectibles…
You’ll get more marks if you use the History file (it’s harder !) Include a loop so that it tweets about the most recent page every hour.
Continue reading “DAT 505 – Assignment Part 4 – Python Webservice APIs”
The Brief – Python Multimedia:
In the next practical you must create a graphical visualisation of a textual data file (to be given out in the practical). Read in the data and use it to generate some kind of visual output.
Rather than using Pygame to create your visualisation (which is powerful, but can be tricky to install), we will be using a library called graphics.py. This can just be dropped into your folder and used (no install needed). Continue reading “DAT 505 – Assignment – Part 3 – Python Multimedia”
The Brief – Python Chatbot:
In the practical session you will create an interactive Python chatbot. This should engage the user in interesting and intelligent conversation. The bot should be able to ask and answer questions. Try to make it as realistic and life-like as possible.
Continue reading “DAT 505 – Assignment Part 2 – Python Chatbot”