Files
pigo/examples/blinkdet/blinkdet.py
2020-10-21 11:03:06 +03:00

144 lines
4.6 KiB
Python

from ctypes import *
import subprocess
import numpy as np
import os
import cv2
import time
os.system('go build -o blinkdet.so -buildmode=c-shared blinkdet.go')
pigo = cdll.LoadLibrary('./blinkdet.so')
os.system('rm blinkdet.so')
MAX_NDETS = 2024
ARRAY_DIM = 6
# Number of consecutive frames the eye must be below the threshold
EYE_CLOSED_CONSEC_FRAMES = 6
# define class GoPixelSlice to map to:
# C type struct { void *data; GoInt len; GoInt cap; }
class GoPixelSlice(Structure):
_fields_ = [
("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
]
# Obtain the camera pixels and transfer them to Go through C types.
def process_frame(pixs):
dets = np.zeros(ARRAY_DIM * MAX_NDETS, dtype=np.float32)
pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
# call FindFaces
faces = GoPixelSlice(pixels, len(pixs), len(pixs))
pigo.FindFaces.argtypes = [GoPixelSlice]
pigo.FindFaces.restype = c_void_p
# Call the exported FindFaces function from Go.
ndets = pigo.FindFaces(faces)
data_pointer = cast(ndets, POINTER((c_longlong * ARRAY_DIM) * MAX_NDETS))
if data_pointer :
buffarr = ((c_longlong * ARRAY_DIM) * MAX_NDETS).from_address(addressof(data_pointer.contents))
res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, 5,))
# The first value of the buffer aray represents the buffer length.
dets_len = res[0][0]
res = np.delete(res, 0, 0) # delete the first element from the array
# We have to consider the pupil pair added into the list.
# That's why we are multiplying the detection length with 3.
dets = list(res.reshape(-1, 5))[0:dets_len*3]
return dets
# initialize the camera
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
# Changing the camera resolution introduce a short delay in the camera initialization.
# For this reason we should delay the object detection process with a few milliseconds.
time.sleep(0.4)
show_pupil = True
show_eyes = False
face_posy = 0
count_left, count_right = 0, 0
while(True):
ret, frame = cap.read()
pixs = np.ascontiguousarray(frame[:, :, 1].reshape((frame.shape[0], frame.shape[1])))
pixs = pixs.flatten()
# Verify if camera is intialized by checking if pixel array is not empty.
if np.any(pixs):
dets = process_frame(pixs) # pixs needs to be numpy.uint8 array
if dets is not None:
# We know that the detected faces are taking place in the first positions of the multidimensional array.
for det in dets:
if det[4] == 1: # 1 == face; 0 == pupil
face_posy = det[1]
cv2.rectangle(frame,
(int(det[1])-int(det[2]/2), int(det[0])-int(det[2]/2)),
(int(det[1])+int(det[2]/2), int(det[0])+int(det[2]/2)),
(0, 0, 255), 2
)
else:
if show_pupil:
count_left += 1
count_right += 1
x1, x2 = int(det[0])-int(det[2]*1.2), int(det[0])+int(det[2]*1.2)
y1, y2 = int(det[1])-int(det[2]*1.2), int(det[1])+int(det[2]*1.2)
subimg = frame[x1:x2, y1:y2]
if subimg is not None:
gray = cv2.cvtColor(subimg, cv2.COLOR_BGR2GRAY)
img_blur = cv2.medianBlur(gray, 1)
if img_blur is not None:
max_radius = int(det[2]*0.45)
circles = cv2.HoughCircles(img_blur, cv2.HOUGH_GRADIENT, 1, int(det[2]*0.45),
param1=60, param2=21, minRadius=4, maxRadius=max_radius)
if circles is not None:
circles = np.uint16(np.around(circles))
for i in circles[0, :]:
if i[2] < max_radius and i[2] > 0:
# Draw outer circle
cv2.circle(frame, (int(det[1]), int(det[0])), i[2], (0, 255, 0), 2)
# Draw inner circle
cv2.circle(frame, (int(det[1]), int(det[0])), 2, (255, 0, 255), 3)
else:
if face_posy < y1:
count_left = 0
else:
count_right = 0
if count_left < EYE_CLOSED_CONSEC_FRAMES:
cv2.putText(frame, "Left blink!", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
elif count_right < EYE_CLOSED_CONSEC_FRAMES:
cv2.putText(frame, "Right blink!", (frame.shape[1]-150, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.circle(frame, (int(det[1]), int(det[0])), 4, (0, 0, 255), -1, 8, 0)
if show_eyes:
cv2.rectangle(frame,
(int(det[1])-int(det[2]), int(det[0])-int(det[2])),
(int(det[1])+int(det[2]), int(det[0])+int(det[2])),
(0, 255, 0), 2
)
cv2.imshow('', frame)
key = cv2.waitKey(1)
if key & 0xFF == ord('q'):
break
elif key & 0xFF == ord('w'):
show_pupil = not show_pupil
elif key & 0xFF == ord('e'):
show_eyes = not show_eyes
cap.release()
cv2.destroyAllWindows()