Bringing advanced computer vision on the Anki Vector robot. By using Vector's API to fetch image data and TinyYoloV3 neural network, vector is able to recognize objects in a scene.
- Vector's API are used to fectch image data from Vector's camera
- Images are preprocessed (reshaped,...)
- Preprocessed images are sent to TinyYoloV3, which is a smaller version of Yolo optimized to reduced computational needs (which means higher framerates for less computational power)
- Output of Yolo are decoded
- Results are printed on Vector's screen + the captured frame from the camera
- Results can also be spoken by Vector (which is cool in a first place but annoying finally)
- And the process goes over and over again
- A Vector robot here: https://anki.com/en-us/vector.html or here https://www.digitaldreamlabs.com (the second link is the new owner of the Vector)
- Tested on Python3.7 with dependencies:
- tensorflow
- numpy
- Pillow
- anki_vector SDK from: https://github.com/anki/vector-python-sdk
- (It should be all the dependencies, sorry if I missed one)
- Official Anki's Vector SDK: https://github.com/anki/vector-python-sdk
- Yolo models: https://pjreddie.com/darknet/yolo/