@l3uz
查了一下午，网上提到的大概有这几个思路：

1. 在训练模型时将模型由默认的MoblieNetV2改为MobileNetV1
   
   2.在Creat impluse中将Image width 与Image height改小。
   
2. 前面的方法都是将模型变小。最后一种方法是我尝试出来的，即牺牲画面。

@kidswong999 我下午在google上搜了一下，得知可能是硬件限制。于是我将sensor.set_windowing的（240， 240）改为（120， 120）.程序正常跑起来了。

还有一个问题。tf.load函数报出异常“e”后打印了这些信息。我想要进入load函数的实现看一看具体是那一步出了问题。此时我发现我找不到函数的库在哪里。请问有没有人可以告诉我怎么查看我所调用的库的源码。

我将训练的模型保存在了openmv中。

程序运行时报出了以下错误：

以下是运行的代码，代码为Edge Impluse生成。

# Edge Impulse - OpenMV Image Classification Example

import sensor, image, time, os, tf, uos, gc

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 = None
labels = None

try:
    # load the model, alloc the model file on the heap if we have at least 64K free after loading
    net = tf.load("trained.tflite", load_to_fb=uos.stat('trained.tflite')[6] > (gc.mem_free() - (64*1024)))
except Exception as e:
    print(e)
    raise Exception('Failed to load "trained.tflite", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')

try:
    labels = [line.rstrip('\n') for line in open("labels.txt")]
except Exception as e:
    raise Exception('Failed to load "labels.txt", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')

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 net.classify(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")

请问这是什么问题？