138 lines
4.4 KiB
Python
138 lines
4.4 KiB
Python
from __future__ import print_function
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from __future__ import division
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import cv2
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import numpy as np
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import imutils
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from naoqi import ALProxy
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from collections import deque
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# Nao configuration
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nao_ip = '192.168.0.11'
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nao_port = 9559
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res = (1, (240, 320)) # NAOQi code and acutal resolution
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fps = 30
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cam_id = 1 # 0 := top, 1 := bottom
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# Recognition stuff
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red_lower = (0, 185, 170) # HSV coded red interval
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red_upper = (2, 255, 255)
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min_radius = 5
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resized_width = None # Maybe we need it maybe don't (None if don't)
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def get_frame_nao(cam_proxy, subscriber, width, height):
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result = cam_proxy.getImageRemote(subscriber)
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cam_proxy.releaseImage(subscriber)
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if result == None:
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raise RuntimeError('cannot capture')
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elif result[6] == None:
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raise ValueError('no image data string')
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else:
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return np.frombuffer(result[6], dtype=np.uint8).reshape(
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height, width, 3
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)
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# i = 0
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# for y in range(res[1][0]):
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# for x in range(res[1][1]): # columnwise
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# image.itemset((y, x, 0), values[i + 0])
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# image.itemset((y, x, 1), values[i + 1])
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# image.itemset((y, x, 2), values[i + 2])
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# i += 3
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# return image
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def find_colored_ball(frame, hsv_lower, hsv_upper, min_radius):
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hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
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# construct a mask for the color "green", then perform a series of
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# dilations and erosions to remove any small blobs left in the mask
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mask = cv2.inRange(hsv, hsv_lower, hsv_upper)
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mask = cv2.erode(mask, None, iterations=2)
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mask = cv2.dilate(mask, None, iterations=2)
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cv2.imshow('ball_mask', mask)
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cv2.waitKey(1)
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# find contours in the mask and initialize the current
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# (x, y) center of the ball
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cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
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cv2.CHAIN_APPROX_SIMPLE)[-2]
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# only proceed if at least one contour was found
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if len(cnts) == 0:
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return None
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# find the largest contour in the mask, then use it to compute
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# the minimum enclosing circle and centroid
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c = max(cnts, key=cv2.contourArea)
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((x, y), radius) = cv2.minEnclosingCircle(c)
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if radius < min_radius:
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return None
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M = cv2.moments(c)
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center = (int(M["m10"] / M["m00"]),int(M["m01"] // M["m00"]))
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return center, int(radius)
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def draw_ball_markers(frame, center, radius, history):
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# draw the enclosing circle and ball's centroid on the frame,
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if center is not None and radius is not None:
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cv2.circle(frame, center, radius, (255, 255, 0), 1)
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cv2.circle(frame, center, 5, (0, 255, 0), -1)
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# loop over the set of tracked points
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for i in range(1, len(history)):
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# if either of the tracked points are None, ignore them
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if history[i - 1] is None or history[i] is None:
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continue
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# otherwise, compute the thickness of the line and
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# draw the connecting lines
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thickness = int(np.sqrt(64 / float(i + 1)) * 2.5)
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cv2.line(frame, history[i - 1], history[i], (0, 255, 0), thickness)
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return frame
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def nao_demo():
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cv2.namedWindow('ball_mask')
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cv2.namedWindow('Frame')
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vd_proxy = ALProxy('ALVideoDevice', nao_ip, nao_port)
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cam_subscriber = vd_proxy.subscribeCamera(
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"ball_finder", cam_id, res[0], 13, fps
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)
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history = deque(maxlen=64)
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try:
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while True:
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frame = get_frame_nao(vd_proxy, cam_subscriber, res[1][1],
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res[1][0])
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# maybe resize the frame, maybe blur it
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if resized_width is not None:
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frame = imutils.resize(frame, width=resized_width)
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# blurred = cv2.GaussianBlur(frame, (11, 11), 0)
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try:
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center, radius = find_colored_ball(
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frame, red_lower, red_upper, min_radius
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)
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history.appendleft(center)
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draw_ball_markers(frame, center, radius, history)
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except TypeError: # No red ball found and function returned None
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history.appendleft(None)
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draw_ball_markers(frame, None, None, history)
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# show the frame to screen
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cv2.imshow("Frame", frame)
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cv2.waitKey(1)
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finally:
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vd_proxy.unsubscribe(cam_subscriber)
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cv2.destroyAllWindows()
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if __name__ == '__main__':
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nao_demo()
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