如何在垃圾识别代码上写代码使识别到的垃圾上画框圈住,并且返回那个框的中心坐标
-
import sensor, image, time, os, tf, lcd
from pyb import UART
uart = UART(3, 19200)
a = 0
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((240, 240))
sensor.skip_frames(time=2000)
lcd.init()
net = "trained.tflite"
labels = [line.rstrip('\n') for line in open("labels.txt")]
clock = time.clock()
while(True):
clock.tick()
img = sensor.snapshot()
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())
predictions_list = list(zip(labels, obj.output()))
b =(max(zip( obj.output(),labels)))
b =b[1]
print(b)
uart.write(b+'\n')
if uart.readline():
c = uart.readline()
print(c)
time.sleep_ms(2000)
if b == ('blank'):
a = a
else:
a = a+1
img.draw_string(10,10,str(a)+'\n' + str(b)+'\n'+'1'+'\n'+'ok')
lcd.display(img)
time.sleep_ms(3000)
for i in range(len(predictions_list)):
print("%s = %f" % (predictions_list[i][0], predictions_list[i][1]))
print(clock.fps(), "fps")
-
目前神经网络只有分类,不能目标查找。