def process(picture_path):
frame = cv2.imread(picture_path, cv2.CV_LOAD_IMAGE_GRAYSCALE)
faces_raw = detect_feature(frame, FACE_CASCADES)
faces = []
for (x, y, w, h) in faces_raw:
image = frame.copy()
# Get the right offsets for top and bottom
offset_y_top, offset_y_bottom = get_offset(y, h, image.shape[0])
y -= offset_y_top
h += offset_y_bottom
# Crop to the face Region of Interest
face_roi = image[y:y + h, x:x + w]
# Try to detect eyes in this face
face_eyes = detect_feature(face_roi, EYES_CASCADES)
# If we find both eyes, calculate the center and rotate the frame to align the eyes
if face_eyes.size == 8:
eyes = [get_center(face_eyes[0]), get_center(face_eyes[1])]
sort_eyes(eyes)
eyes = to_frame_coordinates(eyes, x, y)
image = rotate(image, get_angle_from_eyes(eyes[0], eyes[1]),
eyes[0])
# Crop to the face
image = image[y:y + h, x:x + w]
# Rezise the face to a standard size
image = cv2.resize(image, (FACE_WIDTH, FACE_HEIGHT),
interpolation=cv2.INTER_CUBIC)
# Apply the Tan Triggs transformation
image = tantriggs.tantriggs(image)
debug_save(image)
faces.append(image)
return faces
def process(picture_path):
frame = cv2.imread(picture_path, cv2.CV_LOAD_IMAGE_GRAYSCALE)
faces_raw = detect_feature(frame, FACE_CASCADES)
faces = []
for (x, y, w, h) in faces_raw:
image = frame.copy()
# Get the right offsets for top and bottom
offset_y_top, offset_y_bottom = get_offset(y, h, image.shape[0])
y -= offset_y_top
h += offset_y_bottom
# Crop to the face Region of Interest
face_roi = image[y:y + h, x:x + w]
# Try to detect eyes in this face
face_eyes = detect_feature(face_roi, EYES_CASCADES)
# If we find both eyes, calculate the center and rotate the frame to align the eyes
if face_eyes.size == 8:
eyes = [get_center(face_eyes[0]), get_center(face_eyes[1])]
sort_eyes(eyes)
eyes = to_frame_coordinates(eyes, x, y)
image = rotate(image, get_angle_from_eyes(eyes[0], eyes[1]), eyes[0])
# Crop to the face
image = image[y:y + h, x:x + w]
# Rezise the face to a standard size
image = cv2.resize(image, (FACE_WIDTH, FACE_HEIGHT), interpolation=cv2.INTER_CUBIC)
# Apply the Tan Triggs transformation
image = tantriggs.tantriggs(image)
debug_save(image)
faces.append(image)
return faces
def process(frame):
# frame = cv2.imread(picture_path, cv2.CV_LOAD_IMAGE_GRAYSCALE)
faces_raw = detect_feature(frame, FACE_CASCADES)
faces = []
for (x, y, w, h) in faces_raw:
image = frame.copy()
# Crop to the face Region of Interest
# TODO: there's an error when y - offset goes off limits
face_roi = image[y - FACE_OFFSET_Y:y + h + FACE_OFFSET_Y, x:x + w]
# Try to detect eyes in this face
face_eyes = detect_feature(face_roi, EYES_CASCADES)
# If we find both eyes, calculate the center and rotate the frame to align the eyes
if face_eyes.size == 8:
eyes = [get_center(face_eyes[0]), get_center(face_eyes[1])]
sort_eyes(eyes)
eyes = to_frame_coordinates(eyes, x, y)
image = rotate(image, get_angle_from_eyes(eyes[0], eyes[1]),
eyes[0])
# Crop to the face
image = image[y - FACE_OFFSET_Y:y + h + FACE_OFFSET_Y, x:x + w]
# Rezise the face to a standard size
image = cv2.resize(image, (FACE_WIDTH, FACE_HEIGHT),
interpolation=cv2.INTER_CUBIC)
# Apply the Tan Triggs transformation
image = tantriggs.tantriggs(image)
debug_save(image)
faces.append(image)
return faces
def process(frame):
# frame = cv2.imread(picture_path, cv2.CV_LOAD_IMAGE_GRAYSCALE)
faces_raw = detect_feature(frame, FACE_CASCADES)
faces = []
for (x, y, w, h) in faces_raw:
image = frame.copy()
# Crop to the face Region of Interest
# TODO: there's an error when y - offset goes off limits
face_roi = image[y - FACE_OFFSET_Y:y + h + FACE_OFFSET_Y, x:x + w]
# Try to detect eyes in this face
face_eyes = detect_feature(face_roi, EYES_CASCADES)
# If we find both eyes, calculate the center and rotate the frame to align the eyes
if face_eyes.size == 8:
eyes = [get_center(face_eyes[0]), get_center(face_eyes[1])]
sort_eyes(eyes)
eyes = to_frame_coordinates(eyes, x, y)
image = rotate(image, get_angle_from_eyes(eyes[0], eyes[1]), eyes[0])
# Crop to the face
image = image[y - FACE_OFFSET_Y:y + h + FACE_OFFSET_Y, x:x + w]
# Rezise the face to a standard size
image = cv2.resize(image, (FACE_WIDTH, FACE_HEIGHT), interpolation=cv2.INTER_CUBIC)
# Apply the Tan Triggs transformation
image = tantriggs.tantriggs(image)
debug_save(image)
faces.append(image)
return faces
def main_loop(directory):
image_index = 0
image = numpy.empty(0)
# Open the default webcam
capture = cv2.VideoCapture(0)
while True:
# Read a frame from the capture device and show it
_, frame = capture.read()
cv2.imshow(MAIN_WINDOW, frame)
key = 0xFF & cv2.waitKey(10)
if key == 13 or key == 10: # Enter
faces = detect_feature(frame, face_cascades)
# We want just one face, because we're training the detector
if faces.size == 4:
x, y, w, h = faces[0]
face_roi = frame[y:y + h, x:x + w]
# Try to detect eyes in this face
eyes = detect_feature(face_roi, eyes_cascades)
# Create a window with custom attributes
cv2.namedWindow(FACE_WINDOW, CV_WINDOW_AUTOSIZE | CV_GUI_NORMAL)
# Initialize our state machine for the eyes
eyes_fsm = EyesFSM.EyesFSM(face_roi.shape)
# Setup a callback function for mouse events
cv2.setMouseCallback(FACE_WINDOW, on_mouse_event, (eyes_fsm, face_roi))
# Make a copy of the image to save it later
image = frame.copy()
# Populate the state machine with the eyes just found
for e in eyes:
eyes_fsm.set_current_eye_pos(e)
eyes_fsm.next()
# Update the window to show the eyes
eyes_fsm.update_window(FACE_WINDOW, face_roi)
elif key == ord('s') and image.size > 0 and eyes_fsm and eyes_fsm.is_valid():
# Find a non-existing filename for the new image
while True:
filename = os.path.join(directory, '%s.png' % image_index)
if not os.path.exists(filename):
break
image_index += 1
# Sort the eyes
eyes_fsm.sort_eyes()
# Get the eyes position relative to the frame from the face ROI
eye_left = eyes_fsm.get_frame_coordinates(eyes_fsm.eyes[0], x, y)
eye_right = eyes_fsm.get_frame_coordinates(eyes_fsm.eyes[1], x, y)
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# Rotate the whole frame to align eyes
image = rotate(image, get_angle_from_eyes(eye_left, eye_right), eye_left)
# Crop to the face
image = image[y - FACE_OFFSET_Y: y + h + FACE_OFFSET_Y, x: x + w]
# Rezise the face to a standard size
image = cv2.resize(image, (260, 315), interpolation=cv2.INTER_CUBIC)
# cv2.destroyWindow(FACE_WINDOW)
cv2.imshow(FINAL_FACE_WINDOW, image)
image = tantriggs.tantriggs(image)
cv2.imshow(TANTRIGGS_WINDOW, image)
print("Saving image to %s." % filename)
cv2.imwrite(filename, image)
image_index += 1
image = numpy.empty(0)
elif key == ord('f'):
cv2.imwrite(os.path.join(directory, "%s%s%s%s.png" % (x, y, h, w)), frame)
elif key == 27: # Escape
break