def threadBoth(source=0):
"""
Dedicated thread for grabbing video frames with VideoGet object.
Dedicated thread for showing video frames with VideoShow object.
Main thread serves only to pass frames between VideoGet and
VideoShow objects/threads.
"""
video_getter = VideoGet(source).start()
video_shower = VideoShow(video_getter.frame, '1').start()
video_getter2 = VideoGet('http://192.168.1.4:8080/video').start()
video_shower2 = VideoShow(video_getter2.frame, '2').start()
cps = CountsPerSec().start()
while True:
# if video_getter.stopped or video_shower.stopped:
# video_shower.stop()
# video_getter.stop()
# break
frame = video_getter.frame
frame = putIterationsPerSec(frame, cps.countsPerSec())
video_shower.frame = frame
frame2 = video_getter2.frame
frame2 = putIterationsPerSec(frame2, cps.countsPerSec())
video_shower2.frame = frame2
cps.increment()
def threadBoth(source=0):
"""
Dedicated thread for grabbing video frames with VideoGet object.
Dedicated thread for showing video frames with VideoShow object.
Main thread serves only to pass frames between VideoGet and
VideoShow objects/threads.
"""
video_getter = VideoGet(source).start()
video_shower = VideoShow(video_getter.frame).start()
cps = CountsPerSec().start()
while True:
if video_getter.stopped or video_shower.stopped:
video_shower.stop()
video_getter.stop()
break
frame = video_getter.frame
# frame = putIterationsPerSec(frame, cps.countsPerSec())
'''prediction, frame = detect_object(
yolo,
frame,
postfix=FLAGS.postfix,
)'''
video_shower.frame = frame
cps.increment()
def main():
finger_detect = FingerDetection().start()
key_listener = KeyListener().start()
video_getter = VideoGet(0).start()
video_shower = VideoShow(video_getter.frame).start()
while True:
if video_getter.stopped or video_shower.stopped:
video_shower.stop()
video_getter.stop()
break
frame = video_getter.frame
frame = cv2.flip(frame, 1)
img = normalizeFrame(frame, x0, y0)
frame = drawDetectionArea(frame, x0, y0, width, (0, 255, 0))
cv2.putText(frame, u"NONE = NONE, ONE = LEFT", (0, 80), font, 1.0,
(0, 0, 255), 2, 1)
cv2.putText(frame, "TWO = RIGHT, FOUR = DOWN", (0, 120), font, 1.0,
(0, 0, 255), 2, 1)
cv2.putText(frame, "UP = FIVE", (0, 160), font, 1.0, (0, 0, 255), 2, 1)
finger_detect.frame = img
prediction = handDetect(frame, finger_detect.detect(), x0, y0)
# if prediction == "NONE" or prediction == "FIVE":
key_listener.prediction = prediction
key_listener.handle()
video_shower.frame = frame
def predict_video(data_dir, sess, image_shape, logits, keep_prob, input_image):
print('Predicting Video...')
video_getter = VideoGet(data_dir, sess, image_shape, logits, keep_prob, input_image).start()
video_shower = VideoShow(video_getter.frame).start()
while True:
if video_getter.stopped or video_shower.stopped:
video_shower.stop()
video_getter.stop()
break
frame = video_getter.frame
video_shower.frame = frame
def threadVideoShow(source=0):
"""
Dedicated thread for showing video frames with VideoShow object.
Main thread grabs video frames.
"""
cap = cv2.VideoCapture(source)
(grabbed, frame) = cap.read()
video_shower = VideoShow(frame).start()
cps = CountsPerSec().start()
while True:
(grabbed, frame) = cap.read()
if not grabbed or video_shower.stopped:
video_shower.stop()
break
# frame = putIterationsPerSec(frame, cps.countsPerSec())
video_shower.frame = frame
cps.increment()
def read_zed(sess, image_shape, logits, keep_prob, input_image):
count = 0
video_zed = VideoZed(sess, image_shape, logits, keep_prob, input_image).start()
while type(video_zed.frame) == type(None):
if count == 3:
exit("Error to open ZED")
print("Waiting for zed")
count+=1
time.sleep(1)
video_shower = VideoShow(video_zed.frame).start()
while True:
if video_zed.stopped or video_shower.stopped:
video_shower.stop()
video_zed.stop()
break
frame = video_zed.frame
video_shower.frame = frame
def threadBoth(source=0):
"""
Dedicated thread for grabbing video frames with VideoGet object.
Dedicated thread for showing video frames with VideoShow object.
Main thread serves only to pass frames between VideoGet and
VideoShow objects/threads.
"""
video_getter = VideoGet(source).start()
video_shower = VideoShow(video_getter.frame).start()
cps = CountsPerSec().start()
while True:
if video_getter.stopped or video_shower.stopped:
video_shower.stop()
video_getter.stop()
break
frame = video_getter.frame
frame = putIterationsPerSec(frame, cps.countsPerSec())
video_shower.frame = frame
def threadBoth(source=0):
"""
Dedicated thread for grabbing video frames with VideoGet object.
Dedicated thread for showing video frames with VideoShow object.
Main thread serves only to pass frames between VideoGet and
VideoShow objects/threads.
"""
video_getter = VideoGet(source).start()
video_shower = VideoShow(video_getter.frame).start()
save_image = SaveImage(video_getter.frame)
save_image.start()
while True:
if video_getter.stopped or video_shower.stopped:
video_shower.stop()
video_getter.stop()
save_image.stop()
#save_image.join()
break
frame = video_getter.frame
video_shower.frame = frame
save_image.frame = frame
def gesture_guy():
model = load_model('my_model.h5')
model.load_weights('model_weights.h5')
gb = GestureBrain(model)
print("start ======")
counter = 0
i = 0
cap = cv2.VideoCapture(0)
(grabbed, frame) = cap.read()
video_shower = VideoShow(frame).start()
mode_i = None
action2 = None
while True:
(grabbed, frame) = cap.read()
if not grabbed or video_shower.stopped:
video_shower.stop()
break
cv2.putText(frame, "Current Gesture: {}".format(action2), (10, 450),
cv2.FONT_HERSHEY_TRIPLEX, 0.8, (0, 255, 255))
cv2.putText(frame, "Mode: {}".format(mode_i), (10, 400),
cv2.FONT_HERSHEY_TRIPLEX, 0.8, (0, 255, 255))
video_shower.frame = frame
counter += 1
screen = np.array(cv2.resize(frame, (88, 50)))
gb.push_img(screen)
if counter != 40:
continue
else:
counter = 0
mode = [
'Recognition mode', 'Explorer mode', 'Photo mode', 'Video mode'
]
selectMode = mode[i]
print(selectMode)
action = gb.regonize()
print("predict type :", action)
if selectMode == mode[0]:
if action == 0:
print(labels_want[0])
elif action == 1:
print(labels_want[1])
elif action == 2:
print(labels_want[2])
elif action == 3:
print(labels_want[3])
elif action == 4:
print(labels_want[4])
elif action == 5:
print(labels_want[5])
elif action == 6:
print(labels_want[6])
elif action == 7:
print(labels_want[7])
elif action == 8:
print(labels_want[8])
elif action == 9:
print(labels_want[9])
elif action == 10:
print(labels_want[10])
i += 1
if i != 4:
continue
else:
i = 0
elif action == 11:
print(labels_want[11])
elif action == 12:
print(labels_want[12])
if selectMode == mode[2]:
if action == 0:
print(labels_want[0])
pyautogui.press('left')
elif action == 1:
print(labels_want[1])
pyautogui.press('right')
elif action == 4:
print(labels_want[4])
pyautogui.press('left')
elif action == 5:
print(labels_want[5])
pyautogui.press('right')
elif action == 6:
print(labels_want[6])
# pyautogui.hotkey('altleft','f4')
elif action == 7:
print(labels_want[7])
pyautogui.hotkey('enter')
elif action == 8:
print(labels_want[8])
pyautogui.hotkey('ctrl', '+')
elif action == 9:
print(labels_want[9])
pyautogui.hotkey('ctrl', '-')
elif action == 10:
print(labels_want[10])
i += 1
if i != 4:
continue
else:
i = 0
elif action == 11:
print(labels_want[11])
pyautogui.press('winleft')
if selectMode == mode[3]:
if action == 0:
print(labels_want[0])
video_seekb(0.4)
elif action == 1:
print(labels_want[1])
video_seekf(0.4)
elif action == 4:
print(labels_want[4])
vol_up(0.8)
elif action == 5:
print(labels_want[5])
vol_down(0.8)
elif action == 6:
print(labels_want[6])
pyautogui.press('space')
elif action == 7:
print(labels_want[6])
pyautogui.press('space')
elif action == 9:
print(labels_want[9])
elif action == 10:
print(labels_want[10])
i += 1
if i != 4:
continue
else:
i = 0
elif action == 11:
print(labels_want[11])
if selectMode == mode[1]:
if action == 0:
print(labels_want[0])
pyautogui.press('left')
elif action == 1:
print(labels_want[1])
pyautogui.press('right')
elif action == 2:
print(labels_want[2])
pyautogui.press('down')
elif action == 3:
print(labels_want[3])
pyautogui.press('up')
elif action == 4:
print(labels_want[4])
pyautogui.press('enter')
elif action == 5:
print(labels_want[5])
pyautogui.press('backspace')
elif action == 6:
print(labels_want[6])
# pyautogui.hotkey('altleft','f4')
elif action == 9:
print(labels_want[9])
elif action == 10:
print(labels_want[10])
i += 1
if i != 4:
continue
else:
i = 0
elif action == 11:
print(labels_want[11])
pyautogui.press('winleft')
# if selectMode == mode[4]:
# if action == 0 :
# print(labels_want[0])
# pyautogui.press('left')
# elif action == 1 :
# print(labels_want[1])
# pyautogui.press('right')
# elif action == 2 :
# print(labels_want[2])
# pyautogui.press('down')
# elif action == 3 :
# print(labels_want[3])
# pyautogui.press('up')
# elif action == 4 :
# print(labels_want[4])
# pyautogui.press('pagedown')
# elif action == 5 :
# print(labels_want[5])
# pyautogui.press('pageup')
# elif action == 10:
# print(labels_want[10])
# i += 1
# if i != 5 :
# continue
# else:
# i = 0
# elif action == 11:
# print(labels_want[10])
# pyautogui.press('winleft')
# cv2.putText(frame, "{}".format(action),(10, 450), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (255, 255, 255))
mode_i = mode[i]
action2 = labels_want[action[0]]
def threadBoth(source=1):
"""
Dedicated thread for grabbing video frames with VideoGet object.
Dedicated thread for showing video frames with VideoShow object.
Main thread serves only to pass frames between VideoGet and
VideoShow objects/threads.
"""
video_getter = VideoGet(source).start()
SIFT = SIFTThread(video_getter.frame).start()
video_shower = VideoShow(video_getter.frame).start()
fgbg = cv.createBackgroundSubtractorMOG2()
frameCount = 0
oldPoint = None
while True:
if video_getter.stopped or video_shower.stopped:
video_shower.stop()
video_getter.stop()
break
frame = video_getter.frame
SIFT.frame = frame
# apply mask to extract forgeound object
fgmask = fgbg.apply(frame)
# preprocessing: blurring and eroding to remove small finnicky bits
kernel = np.ones((5, 5), np.uint8)
morph = cv.medianBlur(fgmask, 13)
morph = cv.erode(morph, kernel, iterations=3)
# get the contours
_, contours, _ = cv.findContours(morph, cv.RETR_TREE,
cv.CHAIN_APPROX_SIMPLE)
if len(contours) != 0:
# find the biggest countour by area
c = max(contours, key=cv.contourArea)
area = cv.contourArea(c)
# make sure contour area is bigger than threshold, don't want little contours
if area > threshold_area:
# determine the top-most extreme points along the contour
extTop = tuple(c[c[:, :, 1].argmin()][0])
# assign first value
if (oldPoint is None):
oldPoint = extTop
# if the finger stays for a few frames, we know someone is pointing
if ((oldPoint[0] - 5 <= extTop[0] <= oldPoint[0] + 5)
and (oldPoint[1] - 5 <= extTop[1] <= oldPoint[1] + 5)):
if (extTop[0] != 0 and extTop[1] != 0):
frameCount += 1
if frameCount == 20:
frameCount = 0
SIFT.run()
#print([SIFT.newCoords.astype(int)])
for i in range(len(SIFT.zone.coords)):
res = cv.pointPolygonTest(SIFT.zone.coords[i],
extTop,
measureDist=False)
print(res)
if (res == 1):
webbrowser.open(SIFT.zone.zones[i][1],
new=2)
oldPoint = extTop
else:
frameCount = 0
oldPoint = extTop
# draw a circle at the top-most point
cv.circle(frame, extTop, 8, (100, 0, 255), -1)
video_shower.frame = frame
def startDetecting(self):
capture = VideoGet(0).start()
video_shower = VideoShow(capture.frame).start()
while capture.isOpened():
if capture.stopped or video_shower.stopped:
video_shower.stop()
capture.stop()
break
#Chụp khung hình từ camera
frame = capture.frame
# Nhận dữ liệu tay từ cửa sổ phụ hình chữ nhật
cv2.rectangle(frame,(100,100),(300,300),(0,255,0),0)
crop_image = frame[100:300, 100:300]
#1.
# Áp dụng Gaussian blur
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
exMask = executor.submit(self.maskHSV, crop_image)
mask = exMask.result()
#2.
# Tìm đường viền (contours)
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
exContours = executor.submit(self.findContours, mask)
contours, hierarchy = exContours.result()
#3.
try:
contour = max(contours, key = lambda x: cv2.contourArea(x))
x,y,w,h = cv2.boundingRect(contour)
cv2.rectangle(crop_image,(x,y),(x+w,y+h),(0,0,255),0)
hull = cv2.convexHull(contour)
drawing = np.zeros(crop_image.shape,np.uint8)
cv2.drawContours(drawing,[contour],-1,(0,255,0),0)
cv2.drawContours(drawing,[hull],-1,(0,0,255),0)
hull = cv2.convexHull(contour, returnPoints=False)
defects = cv2.convexityDefects(contour,hull)
count_defects = 0
for i in range(defects.shape[0]):
s,e,f,d = defects[i,0]
start = tuple(contour[s][0])
end = tuple(contour[e][0])
far = tuple(contour[f][0])
# 4.
#angle = 360;
with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor:
exAngle = executor.submit(self.findAngle, start, end, far)
angle = exAngle.result()
if angle <= 90:
count_defects += 1
cv2.circle(crop_image,far,1,[0,0,255],-1)
cv2.line(crop_image,start,end,[0,255,0],2)
if count_defects >= 4:
pyautogui.press('space')
cv2.putText(frame,"JUMP", (450,110), cv2.FONT_HERSHEY_SIMPLEX, 2, 2, 2)
except:
pass
video_shower.frame = frame
if cv2.waitKey(1) == ord('q'):
capture.release()
cv2.destroyAllWindows()
break
import numpy as np
import rpyc
import cv2
from VideoShow import VideoShow
conn = rpyc.connect("localhost", 18861)
y = conn.root.threadBoth(0)
print(len(y))
nparr = np.fromstring(y[0], np.uint8)
img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
video_shower = VideoShow(img).start()
for i in y:
nparr = np.fromstring(i, np.uint8)
img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
video_shower.frame = img
def thread_video(input):
"""
Dedicated thread for grabbing video frames with VideoGet object.
Main thread shows video frames.
"""
video_getter = VideoGet(input).start()
video_shower = VideoShow(video_getter.frame).start()
while True:
if video_getter.stopped or video_shower.stopped:
video_shower.stop()
video_getter.stop()
break
frame = video_getter.frame
rgb_frame = frame[:, :, ::-1]
# Find all the faces and face encodings in the current frame of video
face_location = face_recognition.face_locations(rgb_frame)
if len(face_location) == 0:
pass
elif len(face_location) > 1:
pass
else:
unknown_face_encoding = face_recognition.face_encodings(
rgb_frame, face_location)[0]
index = utils.recognize_face(unknown_face_encoding,
known_faces_encoding)
name = known_names[index]
cv2.putText(frame, name, (100, 100), cv2.FONT_HERSHEY_SIMPLEX, 0.7,
(0, 0, 255), 2)
top, right, bottom, left = face_location[0]
face_height = bottom - top
# Draw a box around the face
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255))
# Display the resulting frame
#try:
(x, y, w,
h) = mouth_detection.mouth_detection_video(frame, detector, predictor)
if h < 0.2 * face_height:
cv2.putText(frame, "close", (30, 30), cv2.FONT_HERSHEY_SIMPLEX,
0.7, (0, 0, 255), 2)
else:
cv2.putText(frame, "open", (30, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7,
(0, 0, 255), 2)
d = int(0.35 * h)
roi = frame[y + d:y + h, x:x + w]
#cv2.rectangle(frame, (x, y + int(0.2*h)), (x+w, y+h), (0, 255, 0), 2)
(px, py, pw, ph) = utils.color_detection(roi)
if pw != 0:
cv2.rectangle(frame, (x + px, y + d + py),
(x + px + pw, y + d + py + ph), (0, 255, 0), 2)
else:
cv2.putText(frame, "no pill detected", (50, 50),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
#except:
# pass
video_shower.frame = frame
fps.update()