from facial_emotion_recognition import EmotionRecognition
import cv2
import cv2
er = EmotionRecognition(device='gpu')
cam = cv2.Videocapture(0)
while True:
success, frame = cam.read()
frame = er.recognise_emotion(frame, return_type='BGR')
cv2.imshow('frame', frame)
key = cv2.waitKey(1)
if key == 27:
break
cam.release()
cv2.destroyAllWindows
import numpy as np
import cv2
start = 'true'
cap = cv2.Videocapture(0)
while (true):
ret, frame = cap.read()
if ret == true:
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
if start == 'true':
start = 'false'
current = gray
a = current[:, 0, 0].size
b = current[0, :, 0].size
x = np.arange(0, a, 1)
y = np.arange(0, b, 1)
delay = zeros[a, b]
for i1 in x:
for i1 in y:
if current[i1, i2] < gray[i1, i2]:
current[i1, i2] += 1
if frame[i1, i2, 2] > 180 and farme[i1, i2,
1] < 50 and frame[i1, i2,
0] < 50:
current[i1, i2] = 0
cv2.imshow('frame', current)
if cv2.waitkey(1) & 0xFF == ord('q'):
def monitor(self):
success, image = self.cap.read()
if not self.cap.isOpened():
self.cap = cv2.Videocapture(self.streamAddr)
success, image = self.cap.read()
if image != None:
image_copy = image.copy()
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
if success:
self._cnt += 1
if self._cnt == 10:
self._handler.baseImg.append(image_copy)
self._handler.add_diff_value(image_copy)
# self._handler.add_candidate_img(image_copy)
# cv2.rectangle(image, (480, 360), (1440, 900), (255, 0, 0))
show_img = QImage(image.data, image.shape[1], image.shape[0],
QImage.Format_RGB888)
photo = QPixmap.fromImage(show_img)
self._images.append(photo)
n = len(self._images)
if n >= 9:
tmp = self._images[n - 9:n] # 优化缓存qpixmap的list
del self._images
self._images = tmp
if len(self._images) >= 9:
flag, self._abnormal_rois, self._draw_index = self._handler.hasAbnormal(
)
if flag or self._is_real_normal:
if self._cnt_flag < 8:
self._handler.check_bg(image_copy)
self._is_real_normal = True
self._cnt_flag += 1
else:
self._is_real_normal = False
print "现在可能有异常了，前面的处理完了没－－"
ab_pixmap = self._images[4]
updated_candidate = self._handler.img_to_candidate()
self._cnt_flag = 0
if self._step2_processed: # second process finish
print "可以处理新的数据了--------"
if self._handler.candidate_valid():
self._step2_processed = False
if updated_candidate:
self._handler.saveImg(self._cnt)
self._buffers[0] = POJO(
ab_pixmap, self._handler.get_candidate())
self._notify_event.set()
else:
print "没有被判定可用的图像－－"
else:
print "还没处理完，你再等会儿－－－－"
utils.set_label_pic(self._window.video, photo)
if self._updated_abnormal_pic:
self._updated_abnormal_pic = False
self.update_show()
else:
self._warning_timer.stop()
else:
self.cap.release()
import cv2
cap = cv2.Videocapture(r'C:\Users\ravillalavanya\Downloads\vtest.avi')
#videos are just a squences of images
#so,we will add while loop to capture the frame continuously
facecascade = cv2.cascadeclassifier(r"C:\Users\ravillalavanya\Downloads\haarcascade_fullbody.xml")
while True:
success, frame = cap.read() #frame variable will capture the video & success variable will tell us whether it was captured success are not
imgGray = cv2.cvtcolor(frame, cv2.COLOR_BGR2GRAY)
faces = facecascade.detectMultiscale(imgGray,1.1, 4)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x,y), (x+w, y+h), (0, 0, 255), 2)
cv2.imshow("video", frame)
if cv2.waitkey(1) == ord('q'): #This adds a Delay and looks for the Key press inorder to break the loop
break
cap.release() #Release the resources after recording
cv2.destroyAllWindows()
strTime = datetime.datetime.now().strftime("%H:%M:%S")
speak(f" the time is {strTime}")
print("the time is " + strTime)
elif 'whats the temperature' in query:
res = app.query(query)
speak(next(res.results).text)
elif 'Calculater' in query:
speak("what should i calculatre?")
gh = takecommand().lower()
res = app.query(gh)
speak(next(res.results).text)
elif "open camera" in query:
nar = cv2.Videocapture(0)
while True:
cv2.inshow('camera,img')
k = cv2.waitkey(58)
if k == 27:
break
nar.release()
cv2.destroyAllwindows()
elif "ip address" in query:
ip = get("https://api.ipify.org").text
speak(f"your IP address is {ip}")
print(f"your IP address is {ip} ")
elif "take screenshot" in query or "take a screenshot" in query:
speak("sir, please tell me the name for this screenshot file")
import argparse, datetime
import imutils
import time
import cv2
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the video file")
ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area")
args = vars(ap.parse_args())
if args.get("video", None) is None:
camera = cv2.VideoCapture(0)
time.sleep(0.25)
else:
camera = cv2.Videocapture(args["video"])
firstFrame = None
while True:
(grabbed, frame) = camera.read()
text = "Unoccupied"
b = 0
if not grabbed:
break
frame = imutils.resize(frame, width=500)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (21, 21), 0)
if firstFrame is None:
firstFrame = gray