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cleaned up recognition a little

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This commit is contained in:
Pavel Lutskov
2018-05-25 19:00:31 +02:00
parent 5980589c6f
commit 0377240382
4 changed files with 226 additions and 0 deletions
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9
README.md
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# Kicker project # Kicker project
## Prerequisites
1. (L)ubuntu 14.04 32-bit
2. Git installed:
```sh
sudo apt-get install git
```
## How to start working ## How to start working
```sh ```sh

118
scripts/live_recognition.py Normal file
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from __future__ import print_function
from __future__ import division
import cv2
from naoqi import ALProxy
from collections import deque
import numpy as np
import imutils
# Nao configuration
nao_ip = '192.168.0.11'
nao_port = 9559
res = (3, (960, 1280)) # NAOQi code and acutal resolution
fps = 1
cam_id = 0 # 0 := top, 1 := bottom
# Recognition stuff
red_lower = (0, 17, 225) # HSV coded red interval
red_upper = (42, 255, 255)
min_radius = 10
resized_width = 600
def get_frame(cam_proxy, subscriber):
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:
# create image
image = np.zeros((res[1][0], res[1][1], 3), np.uint8)
values = map(ord, list(result[6]))
i = 0
for y in range(res[1][0]):
for x in range(res[1][1]):
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_red_ball(frame):
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, red_lower, red_upper)
mask = cv2.erode(mask, None, iterations=2)
mask = cv2.dilate(mask, None, iterations=2)
# 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 = (M["m10"] // M["m00"], M["m01"] // M["m00"])
return center, radius
if __name__ == '__main__':
vd_proxy = ALProxy('ALVideoDevice', nao_ip, nao_port)
cam_subscriber = vd_proxy.subscribeCamera(
"ball_finder", cam_id, res[0], 13, fps
)
pts = deque(maxlen=64)
try:
while True:
frame = get_frame(vd_proxy, cam_subscriber)
# resize the frame, blur it
frame = imutils.resize(frame, width=resized_width)
# blurred = cv2.GaussianBlur(frame, (11, 11), 0)
try:
center, radius = find_red_ball(frame)
except TypeError: # No red ball found and function returned None
pts.appendleft(None)
continue
# draw the circle and centroid on the frame,
cv2.circle(frame, center, radius, (0, 255, 255), 1)
cv2.circle(frame, center, 5, (0, 255, 0), -1)
pts.appendleft(center)
# loop over the set of tracked points
for i in range(1, len(pts)):
# if either of the tracked points are None, ignore them
if pts[i - 1] is None or pts[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, pts[i - 1], pts[i], (0, 0, 255), thickness)
# show the frame to our screen
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
finally:
vd_proxy.unsubscribe(cam_subscriber)
print(vd_proxy.unsubscribe(cam_subscriber))

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setup/install_nao_ros.sh Normal file
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#!/bin/sh
echo "make naqui dir"
mkdir ~/naoqi
sleep 1
echo "copy the files into the naoqi folder"
#cp naoqi-sdk-2.1.4.13-linux32.tar.gz pynaoqi-python2.7-2.1.4.13-linux32.tar.gz ~/naoqi
cp pynaoqi-python2.7-2.1.4.13-linux32.tar.gz ~/naoqi
cd ~/naoqi
sleep 1
echo "Extract them"
#tar xzf naoqi-sdk-2.1.4.13-linux32.tar.gz
tar xzf pynaoqi-python2.7-2.1.4.13-linux32.tar.gz
echo "Add the NAOqi library path to PYTHONPATH"
export PYTHONPATH=~/naoqi/pynaoqi-python2.7-2.1.4.13-linux32:$PYTHONPATH
echo "make this permanently available for every future terminal"
echo 'export PYTHONPATH=~/naoqi/pynaoqi-python2.7-2.1.4.13-linux32:$PYTHONPATH' >> ~/.bashrc
echo "install ros packages for nao"
sudo apt-get install ros-indigo-nao-robot
'''
echo "Setting up sources.list"
sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
sleep 1
echo "Set up your keys"
sudo apt-key adv --keyserver hkp://ha.pool.sks-keyservers.net:80 --recv-key 421C365BD9FF1F717815A3895523BAEEB01FA116
sleep 1
echo "Doing apt update"
sudo apt update
sleep 1
echo "installing ros"
#sudo apt-get install ros-indigo-desktop-full
sudo apt-get install ros-indigo-desktop
sleep 1
echo "Initialize rosdep"
sudo rosdep init
sleep 1
rosdep update
sleep 1
echo "Environment setup"
echo "source /opt/ros/indigo/setup.bash" >> ~/.bashrc
sleep 1
source ~/.bashrc
sleep 1
echo "getting rosinstall"
sudo apt install python-rosinstall
'''
exit 0

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setup/install_ros.sh Normal file
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#!/bin/sh
echo "Setting up sources.list"
sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
sleep 1
echo "Set up your keys"
sudo apt-key adv --keyserver hkp://ha.pool.sks-keyservers.net:80 --recv-key 421C365BD9FF1F717815A3895523BAEEB01FA116
sleep 1
echo "Doing apt update"
sudo apt update
sleep 1
echo "installing ros"
#sudo apt-get install ros-indigo-desktop-full
sudo apt-get install ros-indigo-desktop
sleep 1
echo "Initialize rosdep"
sudo rosdep init
sleep 1
rosdep update
sleep 1
echo "Environment setup"
echo "source /opt/ros/indigo/setup.bash" >> ~/.bashrc
sleep 1
source ~/.bashrc
sleep 1
echo "getting rosinstall"
sudo apt install python-rosinstall
exit 0