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  • 怎么在追小球小车的颜色识别里面再加一个目标大小的识别?



    • from pyb import millis
      from math import pi, isnan

      class PID:
      _kp = _ki = _kd = _integrator = _imax = 0
      _last_error = _last_derivative = _last_t = 0
      _RC = 1/(2 * pi * 20)
      def init(self, p=0, i=0, d=0, imax=0):
      self._kp = float(p)
      self._ki = float(i)
      self._kd = float(d)
      self._imax = abs(imax)
      self._last_derivative = float('nan')

      def get_pid(self, error, scaler):
          tnow = millis()
          dt = tnow - self._last_t
          output = 0
          if self._last_t == 0 or dt > 1000:
              dt = 0
              self.reset_I()
          self._last_t = tnow
          delta_time = float(dt) / float(1000)
          output += error * self._kp
          if abs(self._kd) > 0 and dt > 0:
              if isnan(self._last_derivative):
                  derivative = 0
                  self._last_derivative = 0
              else:
                  derivative = (error - self._last_error) / delta_time
              derivative = self._last_derivative + \
                                       ((delta_time / (self._RC + delta_time)) * \
                                          (derivative - self._last_derivative))
              self._last_error = error
              self._last_derivative = derivative
              output += self._kd * derivative
          output *= scaler
          if abs(self._ki) > 0 and dt > 0:
              self._integrator += (error * self._ki) * scaler * delta_time
              if self._integrator < -self._imax: self._integrator = -self._imax
              elif self._integrator > self._imax: self._integrator = self._imax
              output += self._integrator
          return output
      def reset_I(self):
          self._integrator = 0
          self._last_derivative = float('nan')


    • blob.area() 返回色块的外框的面积。应该等于(w * h)