ObjectDetector uses OpenCV Haar cascade classifiers to detect different objects in images and videos with Python.
Firstly, I wrote two programs, which used the default haar cascade classifier for faces to find those in images and video. They are located in the return-face folder. Then I used a classifier for bananas from coding-robin and did the same, which can be found in return-banana. After that I repeated the process with a classifier for wallclocks from Celal Caoyn Elgun. The result can be found in, you guessed it, 'return-wallclock'.
Above you can also see results from a 24 second segment of the youtube video "How to Keep Bananas Fresh for Longer". The detected bananas were 3534, and about 35% of these were fake positives.
Then, I trained my own classifier for cars using the UIUC Image Database for car detection. Find more in the folder 'return-car'.
Finally, I trained a classifier for cats in boxes using the ImageNet database (yes, they do have this synset). Find more in the 'return-catbox' folder.
This project was inteded simply as an exepriment and for fun.