class Ludan():
img = None # keep image data from C langauge
_fast_rcnn = None
'''
C invokes the sendImge() to send a image from C to Python
'''
def sendImg(self, frame, height, width, channels):
self.img = np.frombuffer(frame, np.uint8)
self.img = np.reshape(self.img, (height, width, channels))
print self.img.shape
return 110, 50, 600, 50
'''
C invokes the showImge() to show a image which has been sent by sendImg
'''
def showImg(self):
print self.img.shape
cv2.imshow('ShowImg', self.img)
"""
while True:
cv2.imshow('showImg', self.img)
k = 0xFF & cv2.waitKey(30)
# key bindings
if k == 27: # esc to exit
break
"""
return 'Hi Ludan'
def call_fast_rcnn_frame(self, frame, height, width, channels):
#print 'Call Fast-RCNN Frame -> height: {} width: {} channels: {}'.format(height, width, channels)
#print type(frame)
#img = np.frombuffer(frame, np.uint8)
img = np.reshape(frame, (height, width, channels))
print 'Detect object from C -> reshape: {}'.format(img.shape)
#Create Fast_RCNN C Interface
if self._fast_rcnn is None:
self._fast_rcnn = Fast_RCNN_C_Interface()
# Run Fast-RCNN
hand5_max_detection = self._fast_rcnn.detect_object(img)
print 'HAND5 MAX DETECTION IS: {}'.format(hand5_max_detection)
return hand5_max_detection
def call_fast_rcnn_frame(self, frame, height, width, channels):
#print 'Call Fast-RCNN Frame -> height: {} width: {} channels: {}'.format(height, width, channels)
#print type(frame)
#img = np.frombuffer(frame, np.uint8)
img = np.reshape(frame, (height, width, channels))
print 'Detect object from C -> reshape: {}'.format(img.shape)
#Create Fast_RCNN C Interface
if self._fast_rcnn is None:
self._fast_rcnn = Fast_RCNN_C_Interface()
# Run Fast-RCNN
hand5_max_detection = self._fast_rcnn.detect_object(img)
print 'HAND5 MAX DETECTION IS: {}'.format(hand5_max_detection)
return hand5_max_detection
#Test Call Fast-RCNN
if __name__ == '__main__':
#Use OpenCV get Camera Image
cap = None
#Open Camera
cap = cv2.VideoCapture(0)
#Set Camera
#cap.set(3, 1280)
#cap.set(4, 720)
if cap is None or not cap.isOpened():
print 'Warning: unable to open video source: video0'
sys.exit()
#Create Fast_RCNN C Interface
fast_rcnn = Fast_RCNN_C_Interface()
#Get Camera Image
while True:
#Read Image
ret, img = cap.read()
#Detect Object and Show FPS
timer = Timer()
timer.tic()
# Run Fast-RCNN
hand5_max_detection = fast_rcnn.detect_object(img)
print 'HAND5 MAX DETECTION IS: {}'.format(hand5_max_detection)
timer.toc()
print 'Detection took {:.3f}s for ONE IMAGE !! '.format(timer.total_time)
#Draw the Biggest Rectangle
