def main():
# Capture RTMP video stream
port = 'Input the port number here'
host = 'Input the SDK endpoint'
password = '******'
cert_path = 'Input the certificate path'
chrys = chrysalis.Connect(host=host,
port=port,
password=password,
ssl_ca_cert=cert_path)
while True:
# Read the frame
chrysframe = chrys.VideoLatestImage()
if chrysframe is not None:
frame = chrysframe.data
cv2.imshow('Video From server', frame)
# if the 'ESC' key is pressed, stop the loop
if cv2.waitKey(1) & 0xFF == 27:
break
cv2.destroyAllWindows()
def validate_param(param_name):
"""
Validating OS environment variables
"""
if param_name not in os.environ:
raise ValueError("missing environment variable " + param_name)
return os.environ[param_name]
if __name__ == "__main__":
port = validate_param('chrys_port')
host = validate_param('chrys_host')
password = validate_param('chrys_password')
cert_path = validate_param('chrys_cert')
chrys = chrysalis.Connect(host=host,
port=port,
password=password,
ssl_ca_cert=cert_path)
while True:
img = chrys.VideoLatestImage()
if img is not None:
frame = img.data
frame = add_face_markers(frame)
cv2.imshow("facemarkers", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
def main():
# Capture RTMP video stream
port = validate_param('chrys_port')
host = validate_param('chrys_host')
password = validate_param('chrys_password')
cert_path = validate_param('chrys_cert')
chrys = chrysalis.Connect(host=host,
port=port,
password=password,
ssl_ca_cert=cert_path)
# Load the front face detector cascade
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
while True:
# Read the frame
chrysframe = chrys.VideoLatestImage()
if chrysframe is not None:
frame = chrysframe.data
# copy to store face region and cropped forehead region
frameFullFace = frame.copy()
frameForehead = frame.copy()
frame_copy = frame.copy()
# Convert to grayscale
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Detect the faces
faces = face_cascade.detectMultiScale(gray, 1.1, 4)
# use for display
displayFrame = frame.copy()
x = 0
y = 0
w = 0
h = 0
# Draw the rectangle around the face
for (x, y, w, h) in faces:
frameFullFace = frame[y:y + h, x:x + w]
cv2.rectangle(displayFrame, (x, y), (x + w, y + h),
(255, 0, 0), 2)
# Draw a rectangle around the foread region
newx = int(x + w / 4)
newy = int(y + h / 4)
newx_w = newx + int(w / 2)
newy_h = newy + int(h / 2)
frameForehead = frame[newy:newy_h, newx:newx_w]
cv2.rectangle(displayFrame, (newx, newy), (newx_w, newy_h),
(0, 255, 0), 2)
# Display the input with Face detection
cv2.imshow('Face detection', displayFrame)
# find sking regions in the frame
skin_mask = find_skin(frame, frameForehead)
# Black out the region so as to minimize the search region for the hand
skin_mask[y:y + h, x:x + w] = 0
# segment out the hand region
hand = segment(skin_mask)
# First check if we were able to actually detect a hand
if hand is not None:
# unpack
thresholded, hand_segment = hand
# Draw contours around hand segment
cv2.drawContours(frame_copy, [hand_segment], -1, (255, 0, 0),
1)
# Count the fingers
fingers = count_fingers(thresholded, hand_segment)
# Display count
if fingers <= 10:
cv2.putText(frame_copy, str(fingers), (70, 45),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
# display the thresholded image, if required for reference
# cv2.imshow("Thesholded", thresholded)
# Display the frame with segmented hand
cv2.imshow("Finger Count", frame_copy)
# if the 'ESC' key is pressed, stop the loop
if cv2.waitKey(1) & 0xFF == 27:
break
# close any open windows
cv2.destroyAllWindows()