Files
kick-it/scripts/live_recognition.py
2018-05-27 18:47:16 +02:00

138 lines
4.4 KiB
Python

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