class GazeDirection(object):
"""Main class, retriving video frames from the webcam, acquiring data and estimating the look direction
"""
ROLLING_WINDOW_LENGTH = 3
def __init__(self):
self.dataset = Dataset()
self.cap = None
self.showMoments = False
self.showEvaluation = False
self.bufferFace = Buffer(self.ROLLING_WINDOW_LENGTH)
self.bufferLeftEye = Buffer(self.ROLLING_WINDOW_LENGTH)
self.bufferRightEye = Buffer(self.ROLLING_WINDOW_LENGTH)
def startCapture(self):
"""Start the webcam recording
"""
self.cap = cv2.VideoCapture(0)
def stopCapture(self):
"""Stop the camera recording
"""
# When everything done, release the capture
self.cap.release()
cv2.destroyAllWindows()
def run(self):
"""Main loop
"""
self.startCapture()
data_collector = DataCollector(self.dataset)
keepLoop = True
while keepLoop:
pressed_key = cv2.waitKey(1)
img = self.getCameraImage()
face, left_eye, right_eye = img.detectEyes(self.bufferFace,
self.bufferLeftEye,
self.bufferRightEye)
if face:
face.draw(img)
if left_eye:
left_eye.draw(face)
if right_eye:
right_eye.draw(face)
# Controls
if pressed_key & 0xFF == ord('q'):
keepLoop = False
if pressed_key & 0xFF == ord('s'):
self.dataset.save()
if pressed_key & 0xFF == ord('l'):
self.dataset.load()
if pressed_key & 0xFF == ord('m'):
self.showMoments = not self.showMoments
if pressed_key & 0xFF == ord('e'):
self.showEvaluation = not self.showEvaluation
data_collector.step(img.canvas, pressed_key, left_eye, right_eye)
txt = 'Dataset: {} (s)ave - (l)oad'.format(len(self.dataset))
cv2.putText(img.canvas, txt, (21, img.canvas.shape[0] - 29),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (32, 32, 32), 2)
cv2.putText(img.canvas, txt, (20, img.canvas.shape[0] - 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 126, 255), 2)
if left_eye and right_eye:
direction = self.dataset.estimateDirection(
left_eye.computeMomentVectors(),
right_eye.computeMomentVectors())
txt = 'Estimated direction: {}'.format(direction.name)
cv2.putText(img.canvas, txt, (21, img.canvas.shape[0] - 49),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (32, 32, 32), 2)
cv2.putText(img.canvas, txt, (20, img.canvas.shape[0] - 50),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 126, 255), 2)
img.show()
if self.showEvaluation:
fig = self.dataset.showValidationScoreEvolution()
plt.show()
self.showEvaluation = False
if self.showMoments:
fig = self.dataset.drawVectorizedMoments()
plt.show()
# cv2.imshow('moments', self.fig2cv(fig))
# plt.close(fig)
self.showMoments = False
self.stopCapture()
def fig2cv(self, fig):
"""Convert a matplotlib figure to a cv2 image that can be displayed
Args:
fig (plt.Figure): Original matplotlib figure
Returns:
cv2.Image: Converted cv2 image
"""
fig.canvas.draw()
img = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
img = img.reshape(fig.canvas.get_width_height()[::-1] + (3, ))
# img is rgb, convert to opencv's default bgr
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
return img
def getCameraImage(self):
"""Retrieves the current frame from the webcam
Returns:
Image: Image frame captured
"""
# Capture frame-by-frame
ret, frame = self.cap.read()
frame = cv2.resize(frame, (640, 480))
frame = cv2.flip(frame, 1)
return Image(frame)
