fvilmos / shape_color_position_detection

A multi-headed DNN to detect shape type (circle, rectangle, triangle) shape color and position of the center point.

Multi headed DNN predictor, detects object coordinates, color and shape type

Toy DNN to demonstrate the usage of the multi-headed output in Keras. The task is to learn to detect basic shapes (circle, triangle, rectangle...and color) and the position of the shape center point. The target was to create a slim network with an optimal number of trainable variables ( this has ~290 k).

Steps:

1. Create a toy database, generate shapes, color it. Prepare the data to be fed to DNN normalize values (values- mean)/ standard deviation and rescale the coordinate values from [0..128,0..128] -> [0..1,0..1].

2. Create the multiheaded Keras functional model

3. Train and test the DNN. After ~400 steps the network reaches about 93% accuracy on position prediction, 85% for shape, and 88% on colors. Take a look at the 'data' folder for better training results.

Links

1. keras

/Enjoy.