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Update python code
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esimov
@@ -15,39 +15,65 @@ ARRAY_DIM = 6
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MOUTH_AR_THRESH = 0.2
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def verify_alpha_channel(frame):
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try:
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frame.shape[3] # 4th position
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except IndexError:
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2BGRA)
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return frame
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def alpha_blend(frame_1, frame_2, mask):
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alpha = mask/255.0
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blended = cv2.convertScaleAbs(frame_1*(1-alpha) + frame_2*alpha)
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return blended
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def apply_circle_focus_blur(frame, x, y):
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frame = verify_alpha_channel(frame)
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height, width, _ = frame.shape
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mask = np.zeros((height, width, 4), dtype='uint8')
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cv2.circle(mask, (int(x), int(y)), int(x/2),
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(255, 255, 255), -1, cv2.LINE_AA)
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mask = cv2.GaussianBlur(mask, (41, 41), cv2.BORDER_DEFAULT)
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blured = cv2.GaussianBlur(frame, (41, 41), cv2.BORDER_DEFAULT)
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blended = alpha_blend(frame, blured, 255-mask)
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frame = cv2.cvtColor(blended, cv2.COLOR_BGRA2BGR)
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return frame
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# define class GoPixelSlice to map to:
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# C type struct { void *data; GoInt len; GoInt cap; }
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class GoPixelSlice(Structure):
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_fields_ = [
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("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
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]
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_fields_ = [
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("pixels", POINTER(c_ubyte)), ("len", c_longlong), ("cap", c_longlong),
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]
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# Obtain the camera pixels and transfer them to Go trough Ctypes.
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# Obtain the camera pixels and transfer them to Go trough Ctypes
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def process_frame(pixs):
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dets = np.zeros(ARRAY_DIM * MAX_NDETS, dtype=np.float32)
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pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
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dets = np.zeros(ARRAY_DIM * MAX_NDETS, dtype=np.float32)
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pixels = cast((c_ubyte * len(pixs))(*pixs), POINTER(c_ubyte))
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# call FindFaces
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faces = GoPixelSlice(pixels, len(pixs), len(pixs))
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pigo.FindFaces.argtypes = [GoPixelSlice]
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pigo.FindFaces.restype = c_void_p
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# call FindFaces
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faces = GoPixelSlice(pixels, len(pixs), len(pixs))
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pigo.FindFaces.argtypes = [GoPixelSlice]
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pigo.FindFaces.restype = c_void_p
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# Call the exported FindFaces function from Go.
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ndets = pigo.FindFaces(faces)
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data_pointer = cast(ndets, POINTER((c_longlong * ARRAY_DIM) * MAX_NDETS))
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# Call the exported FindFaces function from Go.
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ndets = pigo.FindFaces(faces)
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data_pointer = cast(ndets, POINTER((c_longlong * ARRAY_DIM) * MAX_NDETS))
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if data_pointer :
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buffarr = ((c_longlong * ARRAY_DIM) * MAX_NDETS).from_address(addressof(data_pointer.contents))
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res = np.ndarray(buffer=buffarr, dtype=c_longlong, shape=(MAX_NDETS, ARRAY_DIM,))
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if data_pointer:
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buffarr = ((c_longlong * ARRAY_DIM) *
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MAX_NDETS).from_address(addressof(data_pointer.contents))
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res = np.ndarray(buffer=buffarr, dtype=c_longlong,
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shape=(MAX_NDETS, ARRAY_DIM,))
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# The first value of the buffer aray represents the buffer length.
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dets_len = res[0][0]
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res = np.delete(res, 0, 0) # delete the first element from the array
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# The first value of the buffer aray represents the buffer length.
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dets_len = res[0][0]
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res = np.delete(res, 0, 0) # delete the first element from the array
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# We have to multiply the detection length with the total
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# detection points(face, pupils and facial lendmark points), in total 18
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dets = list(res.reshape(-1, ARRAY_DIM))[0:dets_len*19]
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return dets
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# We have to multiply the detection length with the total
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# detection points(face, pupils and facial lendmark points), in total 18
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dets = list(res.reshape(-1, ARRAY_DIM))[0:dets_len*19]
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return dets
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# initialize the camera
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cap = cv2.VideoCapture(0)
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@@ -58,48 +84,53 @@ cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
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# For this reason we should delay the object detection process with a few milliseconds.
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time.sleep(0.4)
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showFaceDet = True
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showFaceDet = False
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showPupil = True
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showLandmarkPoints = True
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while(True):
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ret, frame = cap.read()
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pixs = np.ascontiguousarray(frame[:, :, 1].reshape((frame.shape[0], frame.shape[1])))
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pixs = pixs.flatten()
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ret, frame = cap.read()
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pixs = np.ascontiguousarray(
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frame[:, :, 1].reshape((frame.shape[0], frame.shape[1])))
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pixs = pixs.flatten()
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# Verify if camera is intialized by checking if pixel array is not empty.
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if np.any(pixs):
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dets = process_frame(pixs) # pixs needs to be numpy.uint8 array
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# Verify if camera is intialized by checking if pixel array is not empty.
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if np.any(pixs):
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dets = process_frame(pixs) # pixs needs to be numpy.uint8 array
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if dets is not None:
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# We know that the detected faces are taking place in the first positions of the multidimensional array.
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for row, col, scale, q, det_type, mouth_ar in dets:
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if q > 50:
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if det_type == 0: # 0 == face;
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if showFaceDet:
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cv2.rectangle(frame, (col-scale/2, row-scale/2), (col+scale/2, row+scale/2), (0, 0, 255), 2)
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elif det_type == 1: # 1 == pupil;
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if showPupil:
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cv2.circle(frame, (int(col), int(row)), 4, (0, 0, 255), -1, 8, 0)
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elif det_type == 2: # 2 == facial landmark;
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if showLandmarkPoints:
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cv2.circle(frame, (int(col), int(row)), 4, (0, 255, 0), -1, 8, 0)
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elif det_type == 3:
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if mouth_ar < MOUTH_AR_THRESH: # mouth is open
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cv2.putText(frame, "TALKING!", (10, 30),
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cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
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if dets is not None:
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# We know that the detected faces are taking place in the first positions of the multidimensional array.
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for row, col, scale, q, det_type, mouth_ar in dets:
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if q > 50:
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if det_type == 0: # 0 == face;
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if showFaceDet:
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cv2.rectangle(
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frame, (col-scale/2, row-scale/2), (col+scale/2, row+scale/2), (0, 0, 255), 2)
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elif det_type == 1: # 1 == pupil;
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if showPupil:
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cv2.circle(frame, (int(col), int(row)),
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4, (0, 0, 255), -1, 8, 0)
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elif det_type == 2: # 2 == facial landmark;
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if showLandmarkPoints:
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cv2.circle(frame, (int(col), int(row)),
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4, (0, 255, 0), -1, 8, 0)
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elif det_type == 3:
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if mouth_ar < MOUTH_AR_THRESH: # mouth is open
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frame = apply_circle_focus_blur(frame, col, row)
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cv2.putText(frame, "TALKING!", (10, 30),
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cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
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cv2.imshow('', frame)
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cv2.imshow('', frame)
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key = cv2.waitKey(1)
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if key & 0xFF == ord('q'):
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break
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elif key & 0xFF == ord('w'):
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showFaceDet = not showFaceDet
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elif key & 0xFF == ord('e'):
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showPupil = not showPupil
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elif key & 0xFF == ord('r'):
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showLandmarkPoints = not showLandmarkPoints
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key = cv2.waitKey(1)
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if key & 0xFF == ord('q'):
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break
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elif key & 0xFF == ord('w'):
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showFaceDet = not showFaceDet
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elif key & 0xFF == ord('e'):
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showPupil = not showPupil
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elif key & 0xFF == ord('r'):
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showLandmarkPoints = not showLandmarkPoints
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cap.release()
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cv2.destroyAllWindows()
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