119 lines
3.8 KiB
Python
119 lines
3.8 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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from naoqi import ALProxy
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from collections import deque
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import numpy as np
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import imutils
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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 = (3, (960, 1280)) # NAOQi code and acutal resolution
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fps = 1
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cam_id = 0 # 0 := top, 1 := bottom
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# Recognition stuff
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red_lower = (0, 17, 225) # HSV coded red interval
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red_upper = (42, 255, 255)
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min_radius = 10
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resized_width = 600
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def get_frame(cam_proxy, subscriber):
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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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# create image
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image = np.zeros((res[1][0], res[1][1], 3), np.uint8)
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values = map(ord, list(result[6]))
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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]):
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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_red_ball(frame):
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hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
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# construct a mask for the color "green", then perform
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# a series of dilations and erosions to remove any small
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# blobs left in the mask
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mask = cv2.inRange(hsv, red_lower, red_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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# 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
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# it to compute the minimum enclosing circle and
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# 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 = (M["m10"] // M["m00"], M["m01"] // M["m00"])
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return center, radius
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if __name__ == '__main__':
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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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pts = deque(maxlen=64)
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try:
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while True:
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frame = get_frame(vd_proxy, cam_subscriber)
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# resize the frame, blur it
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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_red_ball(frame)
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except TypeError: # No red ball found and function returned None
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pts.appendleft(None)
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continue
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# draw the circle and centroid on the frame,
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cv2.circle(frame, center, radius, (0, 255, 255), 1)
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cv2.circle(frame, center, 5, (0, 255, 0), -1)
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pts.appendleft(center)
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# loop over the set of tracked points
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for i in range(1, len(pts)):
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# if either of the tracked points are None, ignore them
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if pts[i - 1] is None or pts[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, pts[i - 1], pts[i], (0, 0, 255), thickness)
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# show the frame to our screen
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cv2.imshow("Frame", frame)
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key = cv2.waitKey(1) & 0xFF
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finally:
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vd_proxy.unsubscribe(cam_subscriber)
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print(vd_proxy.unsubscribe(cam_subscriber))
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