能不能使用RGB模式来识别？

# Hello World Example
#
# Welcome to the OpenMV IDE! Click on the green run arrow button below to run the script!

import sensor, image, time,nn

sensor.reset()                      # Reset and initialize the sensor.
sensor.set_pixformat(sensor.GRAYSCALE) # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA)   # Set frame size to QVGA (320x240)
sensor.skip_frames(time = 100)     # Wait for settings take effect.
net = nn.load('/lenet.network')
labels = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']

clock = time.clock()                # 创建一个时钟对象来跟踪FPS帧率。
while(True):
    clock.tick()                    # 更新FPS帧率时钟。
    img = sensor.snapshot()         # 拍一张照片并返回图像。
    out = net.forward(img.copy().binary([(150, 255)], invert=True))
    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=(0,0,0))

    print(score)
    # 注意: 当连接电脑后，OpenMV会变成一半的速度。当不连接电脑，帧率会增加。
    #打印当前的帧率。

此代码的作用是识别数字，但是为什么我在识别数字的时候必须设置成灰度GRAYSCALE，不能用RGB565的模式输出，设置成RGB模式 的时候无法正确识别数字，只有设置成灰度的时候才能识别数字

Edge Impulse - OpenMV Image Classification Example

import sensor, image, time, os, tf

sensor.reset() # Reset and initialize the sensor.
sensor.set_pixformat(sensor.RGB565) # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA) # Set frame size to QVGA (320x240)
sensor.set_windowing((240, 240)) # Set 240x240 window.
sensor.skip_frames(time=2000) # Let the camera adjust.

net = "trained.tflite"
labels = [line.rstrip('\n') for line in open("labels.txt")]

clock = time.clock()
while(True):
clock.tick()

img = sensor.snapshot()

# default settings just do one detection... change them to search the image...
for obj in tf.classify(net, img, min_scale=1.0, scale_mul=0.8, x_overlap=0.5, y_overlap=0.5):
    print("**********\nPredictions at [x=%d,y=%d,w=%d,h=%d]" % obj.rect())
    img.draw_rectangle(obj.rect())
    # This combines the labels and confidence values into a list of tuples
    predictions_list = list(zip(labels, obj.output()))

    for i in range(len(predictions_list)):
        print("%s = %f" % (predictions_list[i][0], predictions_list[i][1]))

print(clock.fps(), "fps")