def callback(self, ros_data):
'''Callback function of subscribed topic.
Here images get converted and features detected'''
if VERBOSE :
print 'received image of type: "%s"' % ros_data.format
#### direct conversion to CV2 ####
np_arr = np.fromstring(ros_data.data, np.uint8)
image_np = cv2.imdecode(np_arr, cv2.CV_LOAD_IMAGE_COLOR)
#### Feature detectors using CV2 ####
# "","Grid","Pyramid" +
# "FAST","GFTT","HARRIS","MSER","ORB","SIFT","STAR","SURF"
#method = "FAST"
#feat_det = cv2.FeatureDetector_create(method)
#convert np image to grayscale
# grey_imagenp = cv2.cvtColor(image_np, cv2.COLOR_BGR2GRAY)
# print 'The image is being processed'
predictionArray, centroidArray = tS.processAndClassify(image_np)
#featPoints,des,keyImage = dd.featureDetectDesORB(grey_imagenp)
#
# for featpoint in featPoints:
# x,y = featpoint.pt
# cv2.circle(image_np,(int(x),int(y)), 3, (0,0,255), -1)
#
print 'The image is being processed'
cv2.imshow('cv_img', frameBoundingBox)
cv2.waitKey(2)
#### Create CompressedIamge ####
msg = CompressedImage()
msg.header.stamp = rospy.Time.now()
msg.format = "jpeg"
msg.data = np.array(cv2.imencode('.jpg', image_np)[1]).tostring()
# Publish new image
self.image_pub.publish(msg)
def callback(self, ros_data):
'''Callback function of subscribed topic.
Here images get converted and features detected'''
if VERBOSE:
print 'received image of type: "%s"' % ros_data.format
#### direct conversion to CV2 ####
np_arr = np.fromstring(ros_data.data, np.uint8)
image_np = cv2.imdecode(np_arr, cv2.CV_LOAD_IMAGE_COLOR)
#### Feature detectors using CV2 ####
# "","Grid","Pyramid" +
# "FAST","GFTT","HARRIS","MSER","ORB","SIFT","STAR","SURF"
#method = "FAST"
#feat_det = cv2.FeatureDetector_create(method)
#convert np image to grayscale
# grey_imagenp = cv2.cvtColor(image_np, cv2.COLOR_BGR2GRAY)
# print 'The image is being processed'
predictionArray, centroidArray = tS.processAndClassify(image_np)
#featPoints,des,keyImage = dd.featureDetectDesORB(grey_imagenp)
#
# for featpoint in featPoints:
# x,y = featpoint.pt
# cv2.circle(image_np,(int(x),int(y)), 3, (0,0,255), -1)
#
print 'The image is being processed'
cv2.imshow('cv_img', frameBoundingBox)
cv2.waitKey(2)
#### Create CompressedIamge ####
msg = CompressedImage()
msg.header.stamp = rospy.Time.now()
msg.format = "jpeg"
msg.data = np.array(cv2.imencode('.jpg', image_np)[1]).tostring()
# Publish new image
self.image_pub.publish(msg)
def processImage(rosImage):
global predictionArray, centroidArray,labels
frame = np.array(rosImage, dtype=np.uint8)
# Process the frame using the process_image() function
predictionArray, centroidArray,labels = tS.processAndClassify(frame)
return predictionArray, centroidArray,labels
def processImage(self, frame, codeBookCenters, svm):
predictionArray, centroidArray,labels = tS.processAndClassify(frame, codeBookCenters, svm)
return predictionArray, centroidArray,labels
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 15 19:28:03 2016
@author: 4chennur
"""
import cv2
import testSegmented as tS
frame = cv2.imread('frame0032.jpg')
tS.processAndClassify(frame)
def processImage(self, frame, codeBookCenters, svm):
predictionArray, centroidArray, labels = tS.processAndClassify(
frame, codeBookCenters, svm)
return predictionArray, centroidArray, labels
