# STM32 CUBE.AI on OpenMV MNIST Example # See https://github.com/openmv/openmv/blob/master/src/stm32cubeai/README.MD import sensor, image, time, nn_st sensor.reset() # Reset and initialize the sensor. sensor.set_contrast(3) sensor.set_brightness(0) sensor.set_auto_gain(True) sensor.set_auto_exposure(True) sensor.set_pixformat(sensor.GRAYSCALE) # Set pixel format to Grayscale sensor.set_framesize(sensor.QQQVGA) # Set frame size to 80x60 sensor.skip_frames(time = 2000) # Wait for settings take effect. clock = time.clock() # Create a clock object to track the FPS. # [CUBE.AI] Initialize the network net = nn_st.loadnnst('network') nn_input_sz = 28 # The NN input is 28x28 while(True): clock.tick() # Update the FPS clock. img = sensor.snapshot() # Take a picture and return the image. # Crop in the middle (avoids vignetting) img.crop((img.width()//2-nn_input_sz//2, img.height()//2-nn_input_sz//2, nn_input_sz, nn_input_sz)) # Binarize the image img.midpoint(2, bias=0.5, threshold=True, offset=5, invert=True) # [CUBE.AI] Run the inference out = net.predict(img) print('Network argmax output: {}'.format( out.index(max(out)) )) img.draw_string(0, 0, str(out.index(max(out)))) print('FPS {}'.format(clock.fps())) # Note: OpenMV Cam runs about half as fast when connected