def callback(image_msg):
bridge = CvBridge();
cv2_image = bridge.imgmsg_to_cv2(image_msg,"bgr8")
cv2_image = np.array(cv2_image,dtype=np.uint8)
(bbox,detected_flag) = fd.faceDetect(cv2_image,classifier_xml_dir);
cv2.imshow('image_subscriber',cv2_image)
cv2.waitKey(1000/30);
# rospy.loginfo(str(detected_flag))
print detected_flag
def execute_cb(self, goal):
print 'goal rx'
self.feedback_.busy_code = 0
face_found = 0
while not face_found:
self.action_server_.publish_feedback(self.feedback_)
print '[FD] wait for image'
image_msg = rospy.wait_for_message("/usb_cam/image_raw", Image)
print '[FD] Got image'
cv_image_gray = image_msg_to_grayscale(image_msg)
(bbox, face_found) = faceDetect.faceDetect(cv_image_gray,
classifier_xml_dir)
print('[FD] result ', face_found)
self.result_.detected_gender = face_found
self.action_server_.set_succeeded(self.result_)
import numpy as np
import cv2
import faceDetect as fd
#Create Video capture variable
camera_id = 1 # 0 - default webcam, 1 - usb webcam
cap = cv2.VideoCapture(camera_id)
# cv2.namedWindow('image');
FPS = 30;
while (True):
#Capture frames
retvar,img = cap.read()
print img.shape # (480,640,3)
print type(img)
#Compute gist
#gistfeat = computeGist(img)
#Classify the image from the above gist
#sceneClass = classifyMulticlass(svmModel,gistfeat)
bbox,flag = fd.faceDetect(img)
# print type(bbox)
# print(bbox)
print(flag)
#Display the frame'
# if flag:
# cv2.rectangle(img,(bbox[0,1],bbox[0,1]),(bbox[0,2],bbox[0,3]),1)
# cv2.imshow('image',img)
cv2.waitKey(1000/FPS)
cap.release()
cv2.destroyAllWindows()
import cv2
import gorgeous
import faceDetect
import picKit
import edge
import copy
img = cv2.imread('test.jpeg')
height, width = img.shape[:2]
img = picKit.resize(img, 500, width * 500 / height)
faces = faceDetect.faceDetect(img)
newimg = copy.copy(img)
for (x, y, w, h) in faces:
newimg = cv2.rectangle(newimg, (x, y), (x + w, y + h), (255, 0, 0), 2)
edgeImage = edge.canny(img[(y - 20):(y + h + 20), (x - 20):(x + w + 20)])
image, contours, hierarchy = cv2.findContours(copy.copy(edgeImage),
cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
image = cv2.drawContours(edgeImage, contours, 1, (255, 255, 255), 3)
cv2.imshow('edges', image)
cv2.waitKey()
cv2.imshow('image', newimg)
cv2.waitKey()
img = gorgeous.gorgeous(img, faces, 8)
cv2.imshow('image2', img)
cv2.waitKey()
#!/usr/bin/env python
import numpy as np
import cv2
import faceDetect as fd
#Create Video capture variable
camera_id = 1 # 0 - default webcam, 1 - usb webcam
cap = cv2.VideoCapture(camera_id)
# cv2.namedWindow('image');
FPS = 30
while (True):
#Capture frames
retvar, img = cap.read()
print img.shape # (480,640,3)
print type(img)
#Compute gist
#gistfeat = computeGist(img)
#Classify the image from the above gist
#sceneClass = classifyMulticlass(svmModel,gistfeat)
bbox, flag = fd.faceDetect(img)
# print type(bbox)
# print(bbox)
print(flag)
#Display the frame'
# if flag:
# cv2.rectangle(img,(bbox[0,1],bbox[0,1]),(bbox[0,2],bbox[0,3]),1)
# cv2.imshow('image',img)
cv2.waitKey(1000 / FPS)
cap.release()
cv2.destroyAllWindows()
