def __get_video__(self):
file_dir = filedialog.askopenfilename()
filetype = os.path.splitext(file_dir)[1]
if len(file_dir) > 0:
if filetype in ['.mov']:
model = load_model("ModelandPickle/AlexnetRP.model")
# Open the computer web cam.
cap = cv2.VideoCapture(file_dir)
while True:
# Capture the frame from the web camera.
ret, frame = cap.read()
facedector = Detector()
face = facedector.detect_face(frame)
for (x, y, w, h) in face:
color = (0, 0, 255)
stroke = 2
cv2.rectangle(frame, (x, y), (x + w, y + h), color, stroke)
# Capture the face from the frame and then test it
Capture_face = frame[y: y + h, x + 10: x + w - 10]
Capture_face = cv2.resize(Capture_face, (Image_size, Image_size))
Capture_face = Capture_face.astype("float")
Capture_face = img_to_array(Capture_face)
face = np.expand_dims(Capture_face, axis=0)
preds = model.predict(face)[0]
j = np.argmax(preds)
result = int(j)
label = image_label[result]
if (label == 'real'):
label = "{}".format(label)
cv2.putText(frame, label, (x, y - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
cv2.rectangle(frame, (x, y), (x + w, y + h),
(0, 255, 0), 2)
elif (label == 'fake'):
label = "{}".format(label)
cv2.putText(frame, label, (x, y - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.rectangle(frame, (x, y), (x + w, y + h),
(0, 0, 255), 2)
frame = cv2.putText(frame, 'Press Q to exit', (0, 10), cv2.FONT_HERSHEY_COMPLEX, 1.2,
(255, 255, 255), 1)
# Display the real time frame.
cv2.imshow('Face Detection', frame)
# If user type Q from the keyboard the loop could be break.
if cv2.waitKey(20) & 0xFF == ord('q'):
break
# Release the resource and destroy all windows.
cap.release()
cv2.destroyAllWindows()
else:
messagebox.showerror('error',
message='The file type is wrong, please upload .mov file')
def __Real_time__(self):
# Loading the Realtime liveness test model...
model = load_model("ModelandPickle/Realtimev2.model")
# le = pickle.loads(open('Userpickle2.pickle', "rb").read())
# Open the computer web cam.
cap = cv2.VideoCapture(0)
while True:
# Capture the frame from the web camera.
ret, frame = cap.read()
facedector = Detector()
face = facedector.detect_face(frame)
for (x, y, w, h) in face:
color = (0, 0, 255)
stroke = 2
cv2.rectangle(frame, (x, y), (x + w, y + h), color, stroke)
# Capture the face from the frame and then test it
Capture_face = frame[y + 10: y + h - 10, x + 10: x + w - 10]
Capture_face = cv2.resize(Capture_face, (Image_size, Image_size))
Capture_face = Capture_face.astype("float")
Capture_face = img_to_array(Capture_face)
face = np.expand_dims(Capture_face, axis=0)
preds = model.predict(face)[0]
j = np.argmax(preds)
result = int(j)
label = image_label[result]
if (label == 'real'):
label = "{}: {:.3f}".format(label, preds[j])
cv2.putText(frame, label, (x, y - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
cv2.rectangle(frame, (x, y), (x + w, y + h),
(0, 255, 0), 2)
elif (label == 'fake'):
label = "{}: {:.3f}".format(label, preds[j])
cv2.putText(frame, label, (x, y - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.rectangle(frame, (x, y), (x + w, y + h),
(0, 0, 255), 2)
frame = cv2.putText(frame, 'Press Q to exit', (50, 50), cv2.FONT_HERSHEY_COMPLEX, 1.2, (255, 255, 255), 2)
# Display the real time frame.
cv2.imshow('Face Detection', frame)
# If user type Q from the keyboard the loop could be break.
if cv2.waitKey(20) & 0xFF == ord('q'):
break
# Release the resource and destroy all windows.
cap.release()
cv2.destroyAllWindows()
def __face_detect__(self):
global panelA
global panelB
if panelA is None:
messagebox.showerror('error', message='No image has been upload..')
if self.image is None:
messagebox.showerror('error', message='No image has been upload..')
else:
facedector = Detector()
# print(self.image)
face = facedector.detect_face(self.image)
if len(face) > 0:
for (x, y, w, h) in face:
color = (0, 0, 255)
stroke = 2
# cv2.rectangle(self.image, (x, y), (x + w, y + h), color, stroke)
image = cv2.cvtColor(self.image, cv2.COLOR_BGR2RGB)
# Get the image dimensions
height, width, no_channels = image.shape
image = PIL.Image.fromarray(image)
image = PIL.ImageTk.PhotoImage(image)
panelA.configure(image=image)
panelA.image = image
self.Crop_image = self.image[y: y + h, x: x + w]
Crop_image = cv2.cvtColor(self.Crop_image, cv2.COLOR_BGR2RGB)
Crop_image = PIL.Image.fromarray(Crop_image)
Crop_image = PIL.ImageTk.PhotoImage(Crop_image)
if panelB is None:
face_detect_frame = tkinter.Frame(self.root)
face_image_lb = tkinter.Label(face_detect_frame, text="The Crop Image",
font=('微软雅黑', 20), fg="black")
face_image_lb.pack()
panelB = tkinter.Label(face_detect_frame, image=Crop_image)
panelB.image = Crop_image
panelB.pack()
# face_detect_frame.pack(side="left", fill='y',padx=10, pady=10)
face_detect_frame.pack(anchor='nw',padx=10, pady=10)
# otherwise, update the image panels
else:
# update the pannels
panelB.configure(image=Crop_image)
panelB.image = Crop_image
else:
messagebox.showerror('error', message='No face has been detected..')
def Getface(Filename,Video_Dir,FramNum,Save_Dir):
count = 0
for filenames in Filename:
for filename in filenames:
Videoname= Video_Dir+'/'+filename
vc = cv2.VideoCapture(Videoname)
flag, frame = vc.read()
# Calculating total frames
frame_count = 0
while (flag):
ret, frame = vc.read()
if ret is False:
break
frame_count = frame_count + 1
vc.release()
gap = frame_count // FramNum
c = 1
vc = cv2.VideoCapture(Videoname)
flag, frame = vc.read()
while (flag):
flag, frame = vc.read()
if (flag == 0):
break
if (c % gap == 0):
facedector = Detector()
# print(self.image)
face = facedector.detect_face(frame)
if len(face) > 0:
for (x, y, w, h) in face:
Crop_face = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
Crop_image = Crop_face[y: y + h, x: x + w]
Crop_image = cv2.cvtColor(Crop_image, cv2.COLOR_BGR2RGB)
Crop_image = cv2.resize(Crop_image,(IMG_SIZE, IMG_SIZE))
cv2.imwrite(Save_Dir + '/' + str(count) + '.jpg', Crop_image)
print("image saving....")
count = count + 1
c = c + 1
cv2.waitKey(1)
