例程讲解25-Machine-Learning->nn_cifar10神经网络例程

视频教程22 - cifar10神经网络：https://singtown.com/learn/50045/

运行此例程前，请先在OpenMV IDE->工具->机器视觉->CNN网络库 中，将相应的神经网络文件保存到OpenMV的SD内存卡中哦。

# cifar10例程
import sensor, image, time, os, nn

sensor.reset()                         # Reset and initialize the sensor.
sensor.set_contrast(3)
sensor.set_pixformat(sensor.RGB565)    # Set pixel format to RGB565
sensor.set_framesize(sensor.QVGA)      # Set frame size to QVGA (320x240)
sensor.set_windowing((128, 128))       # Set 128x128 window.
sensor.skip_frames(time=1000)
sensor.set_auto_gain(False)
sensor.set_auto_exposure(False)

# 加载cifar10网络。OpenMV3 M7上使用此网络可能会超出内存。
#net = nn.load('/cifar10.network')

# 更快，更小，更准确。建议OpenMV3 M7上使用此网络。
net = nn.load('/cifar10_fast.network')
labels = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']

clock = time.clock()                # Create a clock object to track the FPS.
while(True):
    clock.tick()                    # Update the FPS clock.
    img = sensor.snapshot()         # Take a picture and return the image.
    out = net.forward(img)
    max_idx = out.index(max(out))
    score = int(out[max_idx]*100)
    if (score < 70):
        score_str = "??:??%"
    else:
        score_str = "%s:%d%% "%(labels[max_idx], score)
    img.draw_string(0, 0, score_str, color=(255, 0, 0))

    print(clock.fps())             # Note: OpenMV Cam runs about half as fast when connected
                                   # to the IDE. The FPS should increase once disconnected.

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