Run the mini tutorials (demos)

In the EasyCV Control Center, make sure that the services have been started. Then click the "Terminal Window" button. Once the window has opened, change the current directory to the root installation folder, such as
cd /Applications/EasyComputerVision.app/Contents/Resources or
cd C:\Program Files\EasyComputerVision or
cd C:\EasyCV\CVAC_binary-0.8.99-Win7

A link to the local code and online code is provided below. You can also see these mini tutorials and their program output in a manual to an earlier version of EasyCV. We might update this if desired.

Invoke each of the following demos with Python like so:
python demo/prerequisites.py

• Prerequisites: import cv, import easy: prerequisites.py (see code online)

• Apply a pre-trained detector: detect.py (see code online)

• Train a custom detection model: training.py (see code online)

• Test your client against a pre-installed detector service and remotely train a detector for your objects: remote_services.py (see code online)

• Understand what a RunSet is and how to construct it: runset.py (see code online)

• Utilize a ready-made Corpus, learn about Labels vs. Purposes, understand result labels: full_image_corpus.py (see code online)

• Bootstrap a multi-class detector, that is, train it repeatedly on on more and more labeled data: bootstrapping.py (see code online)

• K-fold cross-validation, detector comparisons: evaluation.py (see code online)

• Obtain a LabelMe corpus and edit a corpus properties file: labelme_corpus.py (see code online)