自己训练的模型无法读取
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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?
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我也遇到了这个问题,蹲个回复
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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。
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如果用的OpenMV4 H7,使用edge impulse训练的模型太大了,无法运行。
解决办法:使用星瞳AI云服务训练。https://ai.singtown.com/
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@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。
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@l3uz
查了一下午,网上提到的大概有这几个思路:- 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。
- 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。
- 在训练模型时将模型由默认的MoblieNetV2改为MobileNetV1