Talk detection example

examples/talk_detector/talkdet.py

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+from ctypes import *
+
+import subprocess
+import numpy as np
+import os
+import cv2
+import time
+
+os.system('go build -o talkdet.so -buildmode=c-shared talkdet.go')
+pigo = cdll.LoadLibrary('./talkdet.so')
+os.system('rm talkdet.so')
+
+MAX_NDETS = 2024
+ARRAY_DIM = 5
+
+# 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 trough Ctypes.
+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, ARRAY_DIM,))
+
+		# 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 multiply the detection length with the total 
+		# detection points(face, pupils and facial lendmark points), in total 18
+		dets = list(res.reshape(-1, ARRAY_DIM))[0:dets_len*18]
+		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)
+
+showFaceDet = True
+showPupil = True
+showLandmarkPoints = True
+
+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[3] > 50:
+					if det[4] == 0: # 0 == face;
+						if showFaceDet:
+							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
+							)
+					elif det[4] == 1: # 1 == pupil;
+						if showPupil:
+							cv2.circle(frame, (int(det[1]), int(det[0])), 4, (0, 0, 255), -1, 8, 0)						
+					elif det[4] == 2: # 2 == facial landmark;
+						if showLandmarkPoints:
+							cv2.circle(frame, (int(det[1]), int(det[0])), 4, (0, 255, 0), -1, 8, 0)
+
+	cv2.imshow('', frame)
+
+	key = cv2.waitKey(1)
+	if key & 0xFF == ord('q'):
+		break
+	elif key & 0xFF == ord('w'):
+		showFaceDet = not showFaceDet
+	elif key & 0xFF == ord('e'):
+		showPupil = not showPupil
+	elif key & 0xFF == ord('r'):
+		showLandmarkPoints = not showLandmarkPoints
+
+cap.release()
+cv2.destroyAllWindows()