Files
kick-it/scripts/live_recognition.py

120 lines
4.0 KiB
Python

from __future__ import print_function
from __future__ import division
import json
import cv2
import numpy as np
# import imutils
from imagereaders import NaoImageReader, VideoReader
from collections import deque
red_lower = (0, 185, 170) # HSV coded red interval
red_upper = (2, 255, 255)
class BallFinder(object):
def __init__(self, hsv_lower, hsv_upper, min_radius, width,
viz=False):
self.hsv_lower = hsv_lower
self.hsv_upper = hsv_upper
self.min_radius = min_radius
self.width = width
self.history = deque(maxlen=64)
self.last_center = None
self.last_radius = None
self.viz = viz
if self.viz:
cv2.namedWindow('ball_mask')
cv2.namedWindow('Frame')
def find_colored_ball(self, frame):
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# construct a mask for the color, then perform a series of
# dilations and erosions to remove any small blobs left in the mask
mask = cv2.inRange(hsv, self.hsv_lower, self.hsv_upper)
mask = cv2.erode(mask, None, iterations=2)
mask = cv2.dilate(mask, None, iterations=2)
if self.viz:
cv2.imshow('ball_mask', mask)
# 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:
print('Nothin there')
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 < self.min_radius:
return None
M = cv2.moments(c)
center = (int(M["m10"] / M["m00"]),int(M["m01"] // M["m00"]))
return center, int(radius)
def next_frame(self, frame):
# maybe resize the frame, maybe blur it
# if self.width is not None:
# frame = imutils.resize(frame, width=self.width)
try:
self.last_center, self.last_radius = self.find_colored_ball(frame)
except TypeError: # No red ball found and function returned None
self.last_center, self.last_radius = None, None
self.history.appendleft(self.last_center)
self.draw_ball_markers(frame)
# show the frame to screen
if self.viz:
cv2.imshow("Frame", frame)
return cv2.waitKey(2)
def draw_ball_markers(self, frame):
# draw the enclosing circle and ball's centroid on the frame,
if self.last_center is not None and self.last_radius is not None:
cv2.circle(frame, self.last_center, self.last_radius,
(255, 255, 0), 1)
cv2.circle(frame, self.last_center, 5, (0, 255, 0), -1)
# loop over the set of tracked points
for i in range(1, len(self.history)):
# if either of the tracked points are None, ignore them
if self.history[i - 1] is None or self.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, self.history[i - 1], self.history[i],
(0, 255, 0), thickness)
return frame
def load_hsv_config(self, filename):
with open(filename) as f:
hsv = json.load(f)
self.hsv_lower = tuple(map(hsv.get, ('low_h', 'low_s', 'low_v')))
self.hsv_upper = tuple(map(hsv.get, ('high_h', 'high_s', 'high_v')))
if __name__ == '__main__':
# video = NaoImageReader('192.168.0.11')
video = VideoReader(0, loop=True)
finder = BallFinder(red_lower, red_upper, 5, None)
try:
while True:
finder.next_frame(video.get_frame())
finally:
video.close()