Machine to sort bricks using machine learning. A Raspiberry PI is used to control the individual motors and to take the images. The images are then sent to another computer, which uses the ML model to make a prediction of what type of brick it is. The sorter is operated via an HTML interface.
More details and a video of the brick sorter can be found here.
- Place bricks in the feeder by the conveyor belt.
- Belt moves bricks to a vibrating plate.
- Vibrating plate tries to get the bricks into a sequence
- To get only one brick on the plate, a Gate opens for a very short time and then closes it again the gate (in a loop).
- If a brick is detected on the tilt plate, a image is taken and the belt, plate and gate are stopped.
- Brick image is sent to a server.
- Server uses the learned model and tries to determine the brick type and returns the type. The server stores also the image in the images directory.
- Depending on the brick type the hub is moved to the corresponding slot.
- Tilt plate is tilted briefly so that the bricks slides on the hub and then into a slot.
- Belt, plate and gate are started again.
The model is based on VGG16 with an own top layer.
The images to calculate the model have been taken with the brick sorter. They are stored in the data directory, all images of one type in a separate directory, e.g. 1x1 or 2x4.
To calculate a new model as h5 file run the following command in the model directory
python3 model.py -reread
In the model directory call
python3 predict_server.py
In the sorter directory call
python3 sorter_server.py
The address of the predict server must be configured in sorter_server.py.
HTML Overview page on <sorter server>:5000 to start transpart and detection. It shows also the latest image with the prediction.