def test_webcam():
camera = Camera.Subsystem(type="WEB",
name=None,
camera_path=None,
storage_path=None)
camera.initialize()
frame = camera.capture_image()
while True:
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
cv2.destroyAllWindows()
camera.shutdown()
["Core", "PreProcessing", "face_detector", "deploy.prototxt"])
weightsPath = os.path.sep.join([
"Core", "PreProcessing", "face_detector",
"res10_300x300_ssd_iter_140000.caffemodel"
])
faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)
predictor_path = "Core/FacialFeatureDetection/shape_predictor_68_face_landmarks.dat"
mouth_xml = "Core/FacialFeatureDetection/cascade-files/haarcascade_mcs_mouth.xml"
nose_xml = "Core/FacialFeatureDetection/cascade-files/haarcascade_mcs_nose.xml"
camera = Camera.Subsystem(
type=options.
camera, # "IP" for ip camera, "WEB" for web camera
name=None,
camera_path=None,
storage_path=None)
preprocessor = PreProcessor.Subsystem(frame=None)
face_detection = FaceDetection.Subsystem(frame=None,
height=None,
width=None,
blob=None,
faceNet=None)
mask_detection = MaskDetection.SubSystem()
facial_feat_detection = FacialFeatureDetection.Subsystem(
detector=None,
predictor=None,
mouthCascade=None,
noseCascade=None)
mask_eval = MaskEvaluate.Subsystem(noseflag=None,
def main():
prototxtPath = os.path.sep.join(
["..", "PreProcessing", "face_detector", "deploy.prototxt"])
weightsPath = os.path.sep.join([
"..", "PreProcessing", "face_detector",
"res10_300x300_ssd_iter_140000.caffemodel"
])
faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)
camera = Camera.Subsystem(type=None,
name=None,
camera_path=None,
storage_path=None)
preprocessor = PreProcessor.Subsystem(frame=None)
face_detection = FaceDetection.Subsystem(frame=None,
height=None,
width=None,
blob=None,
faceNet=None)
postprocessor = PostProcessing.SubSystem()
camera.initialize()
preprocessor.initialize()
face_detection.initialize(faceNet)
postprocessor.initialize()
while True:
frame = camera.capture_image()
# Face Detection Module
face_detection.setFrame(frame)
faces, locations = face_detection.runFaceDetect()
# Pre Process Module
prepared = []
if len(faces) > 0:
for face in faces:
preprocessor.setFrame(face)
modified = preprocessor.prepareFace()
cv2.imshow("modified", modified)
prepared.append(modified)
# Drawing box around face location
for box in locations:
# will make a box around face not mask area because these are Kenneth's coordinates
(startX, startY, endX, endY) = box
# Post-Processing Module
# 1) will always yield green box because mask > noMask; probability = 100% mask
# 2) switch tuple to (0, 1) if testing mask < noMask (red box); probability = 100% no mask
# 3) to test probability reading, play with different numbers in tuple
# ie. (0.38, 0.62) -> probability = 62% no mask
postprocessing = PostProcessing.SubSystem()
output_frame = postprocessing.prepareOutputFrame(
frame, (0, 1), startX, startY, endX, endY)
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
cv2.destroyAllWindows()
camera.shutdown()
def main():
prototxtPath = os.path.sep.join(["..",
"PreProcessing",
"face_detector",
"deploy.prototxt"])
weightsPath = os.path.sep.join(["..",
"PreProcessing",
"face_detector",
"res10_300x300_ssd_iter_140000.caffemodel"])
faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)
camera = Camera.Subsystem(
type=None,
name=None,
camera_path=None,
storage_path=None
)
preprocessor = PreProcessor.Subsystem(
frame=None
)
face_detection = FaceDetection.Subsystem(
frame=None,
height=None,
width=None,
blob=None,
faceNet=None
)
camera.initialize()
preprocessor.initialize()
face_detection.initialize(faceNet)
while True:
frame = camera.capture_image()
# Face Detection Module
face_detection.setFrame(frame)
faces, locations = face_detection.runFaceDetect()
# Pre Process Module
prepared = []
if len(faces) > 0:
for face in faces:
preprocessor.setFrame(face)
modified = preprocessor.prepareFace()
cv2.imshow("modified", modified)
prepared.append(modified)
# Drawing box around face location
for box in locations:
(startX, startY, endX, endY) = box
color = (0, 255, 0) # GREEN outline
cv2.rectangle(frame, (startX, startY), (endX, endY), color, 2)
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
cv2.destroyAllWindows()
camera.shutdown()
def main():
prototxtPath = os.path.sep.join(
["..", "PreProcessing", "face_detector", "deploy.prototxt"])
weightsPath = os.path.sep.join([
"..", "PreProcessing", "face_detector",
"res10_300x300_ssd_iter_140000.caffemodel"
])
faceNet = cv2.dnn.readNet(prototxtPath, weightsPath)
predictor_path = "shape_predictor_68_face_landmarks.dat"
mouth_xml = "cascade-files/haarcascade_mcs_mouth.xml"
nose_xml = "cascade-files/haarcascade_mcs_nose.xml"
camera = Camera.Subsystem(type="WEB",
name=None,
camera_path=None,
storage_path=None)
preprocessor = PreProcessor.Subsystem(frame=None)
face_detection = FaceDetection.Subsystem(frame=None,
height=None,
width=None,
blob=None,
faceNet=None)
facial_feat_detection = FacialFeatureDetection.Subsystem(detector=None,
predictor=None,
mouthCascade=None,
noseCascade=None)
camera.initialize()
preprocessor.initialize()
face_detection.initialize(faceNet)
facial_feat_detection.initialize(predictor_path, mouth_xml, nose_xml)
while True:
frame = camera.capture_image()
# Face Detection Module
# face_detection.setFrame(frame)
# faces, locations = face_detection.runFaceDetect()
# Pre Process Module
# prepared = []
# if len(faces) > 0:
# for face in faces:
# preprocessor.setFrame(face)
# modified = preprocessor.prepareFace()
# cv2.imshow("modified", modified)
# prepared.append(modified)
# Facial Feature Module
gray = preprocessor.cvtToGRAY(frame)
shape = facial_feat_detection.detect_facial_landmarks(gray)
mouth_rects = facial_feat_detection.cascade_detect(gray, "mouth")
nose_rects = facial_feat_detection.cascade_detect(gray, "nose")
# Draw facial feature dots
if len(shape) > 0:
for (x, y) in shape:
cv2.circle(frame, (x, y), 1, (0, 0, 255), -1)
# Draw nose and mouth using haar cascade
if len(nose_rects) > 0:
for (startX, startY, endX, endY) in nose_rects:
cv2.rectangle(frame, (startX, startY), (endX, endY),
(0, 255, 0), 1)
if len(mouth_rects) > 0:
for (startX, startY, endX, endY) in mouth_rects:
cv2.rectangle(frame, (startX, startY), (endX, endY),
(0, 255, 0), 1)
# Drawing box around face location
# for box in locations:
# (startX, startY, endX, endY) = box
#
# color = (0, 255, 0) # GREEN outline
# cv2.rectangle(frame, (startX, startY), (endX, endY), color, 2)
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
cv2.destroyAllWindows()
camera.shutdown()