这是从edge impulse 直接导出来的代码,但是直接运行就会像这样报错 是什么问题
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# 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")
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最后一行不是代码,是图片没传上去
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你的硬件是OpenMV4 Plus吗?OpenMV4不能运行edge impulse的分类。
如果是OpenMV4,可以用FOMO的小模型:https://singtown.com/learn/50918/
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@kidswong999
我的是H7 plus 也是这个问题,求解
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@2ge1 什么意思勒?图片没有上传上去是什么呀这,可是明明edge impulse里边是上传了呀
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是需要把模型下载下来,然后烧录到板子里。看视频步骤 https://singtown.com/learn/50872/