def test_resize():
# Init stabilizer and video reader
max_dim = 30
stabilizer = VidStab(processing_max_dim=max_dim)
assert stabilizer.processing_max_dim == max_dim
# noinspection PyProtectedMember
assert stabilizer._processing_resize_kwargs == {}
vidcap = cv2.VideoCapture(OSTRICH_VIDEO)
_, frame = vidcap.read()
_ = stabilizer.stabilize_frame(input_frame=frame, smoothing_window=1)
_, frame = vidcap.read()
stabilized_frame = stabilizer.stabilize_frame(input_frame=frame,
smoothing_window=1)
assert stabilized_frame.shape == (446, 876, 3)
assert max(stabilizer.prev_gray.shape) <= max_dim
# noinspection PyProtectedMember
assert stabilizer._processing_resize_kwargs == {'width': max_dim}
def test_stabilize_frame():
# Init stabilizer and video reader
stabilizer = VidStab(processing_max_dim=float('inf'))
vidcap = cv2.VideoCapture(OSTRICH_VIDEO)
window_size = 30
while True:
_, frame = vidcap.read()
# Pass frame to stabilizer even if frame is None
stabilized_frame = stabilizer.stabilize_frame(
input_frame=frame, smoothing_window=window_size, border_size=10)
if stabilized_frame is None:
break
check_transforms(stabilizer, is_cv4=imutils.is_cv4())
def test_stabilize_frame():
# Init stabilizer and video reader
stabilizer = VidStab()
vidcap = cv2.VideoCapture(ostrich_video)
window_size = 30
while True:
grabbed_frame, frame = vidcap.read()
# Pass frame to stabilizer even if frame is None
stabilized_frame = stabilizer.stabilize_frame(
input_frame=frame, smoothing_window=window_size, border_size=10)
if stabilized_frame is None:
break
unpickled_transforms = download_pickled_transforms(window_size,
cv4=imutils.is_cv4())
assert np.allclose(stabilizer.transforms, unpickled_transforms[0])
assert np.allclose(stabilizer.trajectory, unpickled_transforms[1])
assert np.allclose(stabilizer.smoothed_trajectory, unpickled_transforms[2])
def main():
# Video Stabilizer
device_val = None
stabilizer = VidStab()
# For webcam input:
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH,
1280) # set new dimensions to cam object (not cap)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
cap.set(cv2.CAP_PROP_FPS, 120)
# Check OS
os = platform.system()
if os == "Linux":
device_val = "/dev/video2"
# Start virtual camera
with pyvirtualcam.Camera(1280,
720,
120,
device=device_val,
fmt=PixelFormat.BGR) as cam:
print('Virtual camera device: ' + cam.device)
while True:
success, img = cap.read()
img = frame_manipulate(img)
# Stabilize the image to make sure that the changes with Zoom are very smooth
img = stabilizer.stabilize_frame(input_frame=img,
smoothing_window=2,
border_size=-20)
# Resize the image to make sure it does not crash pyvirtualcam
img = cv2.resize(img, (1280, 720), interpolation=cv2.INTER_CUBIC)
cam.send(img)
cam.sleep_until_next_frame()
def main():
# ---===--- initialize --- #
fps = FPS().start()
count = 0
count_th = 20
rec = False
sg.theme('Black')
useVideo = False
isFirst = True
now = datetime.now()
isstab = False
cap = None
lastframe = None
# ---===--- define the window layout --- #
tab1_layout = [
[
sg.T('Battery: '),
sg.ProgressBar(100, orientation='h', size=(10, 10), key='battbar'),
sg.Text('Last detected: '),
sg.Text(' ', key='-detected-', size=(20, 1)),
sg.Button('Capture', key='-STOP-'),
sg.Button('Refresh', key='-repic-'),
sg.Button('EXIT', key='-EXIT-')
],
[sg.Image(filename='', key='-image-')],
[
sg.Text('Height: ', size=(15, 1)),
sg.Text('', size=(15, 1), justification='center', key='_HEIGHT_')
],
[
sg.Text('Latitude: ', size=(15, 1)),
sg.Text('', size=(15, 1), justification='center', key='_LATI_')
],
[
sg.Text('Longitude: ', size=(15, 1)),
sg.Text('', size=(15, 1), justification='center', key='_LONGTI_')
],
[
sg.Text('FPS: '),
sg.Text(size=(15, 1), key='-FPS-'),
sg.Button('stabilize', key='-stabilize-')
],
]
column1 = [[
sg.Text('Communication',
background_color='#333333',
justification='center',
size=(20, 1)),
], [sg.Text('Gimbal command: '),
sg.Text(size=(15, 1), key='-Gimbal-')],
[
sg.Text('Object size reference: '),
sg.Image(filename='', key='-ref-')
]]
tab2_layout = [[sg.T('cropped/masked')],
[
sg.Image(filename='', key='-cropped-'),
sg.T(' ' * 30),
sg.Image(filename='', key='-masked-'),
sg.Column(column1, background_color='#333333')
],
[
sg.Text('Size of the object: ', size=(15, 1)),
sg.Text('', size=(10, 1), justification='center'),
sg.Slider(range=(0, 500),
default_value=15,
size=(50, 10),
orientation='h',
key='-slider-')
]]
tab3_layout = [[sg.Image(filename='', key='-histp-')],
[sg.Text(' ', key='-history-', size=(20, 1))],
[
sg.Button('Next'),
sg.Button('Refresh'),
sg.Button('Prev')
]]
layout = [
[
sg.Text('High Altitude Surveillance',
size=(20, 1),
font='Helvetica 20')
],
[
sg.TabGroup([[
sg.Tab('Cam view', tab1_layout),
sg.Tab('Area view', tab2_layout),
sg.Tab('Detected view', tab3_layout)
]], )
],
]
layoutWin2 = [[sg.Text('Tracking and DetectionDemo', key='-STATUS-')],
[
sg.Button('Start', key='-START-', disabled=True),
sg.Button('Connect'),
sg.Button('Source'),
sg.Checkbox('Record',
key='-RECORD-',
size=(12, 1),
default=False)
], [sg.T(' ' * 12), sg.Button('Exit', )]]
# create the window and show it
# main window
window = sg.Window('DemoUI', layout, no_titlebar=False)
# Open Connect Vods window
window2 = sg.Window('DetectedHistory', layoutWin2, no_titlebar=False)
# locate the elements we'll be updating. Does the search only 1 time
image_elem = window['-image-']
cropped_elem = window['-cropped-']
masked_elem = window['-masked-']
# initializing stuffs
mcd = MCDWrapper()
object_bounding_box = None
date_time = now
vodfol = date_time.strftime("%m_%d_%Y,%H-%M-%S")
cropped = None
count, fcount, fmeter = 0, 0, 0
netip = '192.168.0.102'
port = 25000
out = None
s = None
win2_active = True
showhist = False
frame = None
event2, values2 = None, None
capp = os.listdir("cap")
ptr = 1
stabilizer = VidStab(kp_method="GFTT")
if capp:
histpic = capp[len(capp) - ptr]
while True:
ev1, vals1 = window2.Read(timeout=100)
if ev1 is None or ev1 == '-START-':
try:
os.mkdir("cap1/" + vodfol)
os.mkdir("cap1/" + vodfol + "/cap")
os.mkdir("cap1/" + vodfol + "/capc")
except:
pass
window2.Close()
win2_active = False
if window2['-RECORD-'].Get():
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('./recording/%s.avi' % (vodfol), fourcc,
30.0, (1020, 720))
break
if ev1 is None or ev1 == 'Exit':
if out:
out.release()
break
if ev1 is ev1 == 'Source':
filename = sg.popup_get_file('Select Source')
useVideo = True
if filename:
cap = cv2.VideoCapture(filename)
else:
cap = WebcamVideoStream(src=0).start()
if ev1 is ev1 == 'Connect':
try:
s = comm(netip, port)
s = s.start()
cap = WebcamVideoStream(src=0).start()
time.sleep(1)
except:
sg.popup('Error CameraIP not found')
if not cap:
window2['-START-'].update(disabled=True)
else:
'''if useVideo:
captype = 'Video'
else:
captype = 'Aerial camera'
'''
window2['-STATUS-'].update("Ready")
window2['-START-'].update(disabled=False)
# ---===--- LOOP through video file by frame --- #
while True and win2_active == False:
event, values = window.read(timeout=20)
if event in ('-EXIT-', None):
if s:
s.stop()
if out:
out.release()
break
if useVideo == True:
if frame is not None:
lastframe = frame.copy()
try:
ret, frame = cap.read()
except:
frame = cap.read()
else:
if frame is not None:
lastframe = frame.copy()
try:
frame = cap.read()
except:
frame = None
while frame is None:
try:
cap = WebcamVideoStream(
src="http://192.168.0.102:8081").start()
time.sleep(1)
frame = cap.read()
except:
continue
if lastframe:
frame = lastframe
i = 0
now = datetime.now()
date_time = now
vodname = date_time.strftime("%m_%d_%Y,%H-%M-%S")
s1 = date_time.strftime("%m_%d_%Y,%H-%M-%S")
objsize = int(values['-slider-'])
logging.basicConfig(filename='Detected.log',
format='%(asctime)s %(message)s',
datefmt='%m_%d_%Y,%H-%M-%S')
lat = 12.922152
longti = 101.719344
height = 80
batt = 84.235
latllongrand = random.uniform(0, 0.00005)
latllongrand2 = random.uniform(0, 0.00005)
hrand = random.uniform(0, 0.005)
hrand2 = random.uniform(0, 0.005)
lat = lat + latllongrand - latllongrand2
longti = longti + latllongrand - latllongrand2
height = height + hrand - hrand2
data = "XNOTCONNECTED_NOTCONNECTED_NOTCONNECTED_0"
ref = cv2.imread('ref.png')
if objsize > 1:
ref = cv2.resize(ref, (objsize, objsize))
refbytes = cv2.imencode('.png', ref)[1].tobytes() # ditto
window['-ref-'].update(data=refbytes)
if s:
s.getxyhf()
data = s.getxyh()
split = data.split('_')
if len(split) > 3 and split[0][0] == 'X':
window['_LATI_'].update(split[0][1:])
window['_LONGTI_'].update(split[1])
window['_HEIGHT_'].update(split[2])
window['battbar'].update_bar(int(float(split[3][0:2])))
#----------if no frame reuse last frame----------#
if frame is None and lastframe is not None:
frame = lastframe
if out:
frameout = cv2.resize(frame, (1020, 720))
out.write(frameout)
if isstab is True:
stabilized_frame = stabilizer.stabilize_frame(input_frame=frame,
border_size=0)
frame = stabilized_frame[int(stabilized_frame.shape[0] /
8):int(stabilized_frame.shape[0] * 7 /
8),
int(stabilized_frame.shape[1] /
8):int(stabilized_frame.shape[1] * 7 /
8)].copy()
# --------Event handler----------------
if event == '-stabilize-': # stop video
isstab = not isstab
if event == '-STOP-': # stop video
stop = window["-STOP-"]
if frame.sum() > 0:
object_bounding_box = cv2.selectROI("Frame",
frame,
fromCenter=False,
showCrosshair=True)
object_tracker = cv2.TrackerMOSSE_create()
object_tracker.init(frame, object_bounding_box)
cv2.destroyAllWindows()
if event == 'Refresh':
capp = os.listdir("cap1/" + vodfol + "/capc")
ptr = 1
if capp:
histpic = capp[len(capp) - ptr]
histtemp = cv2.imread("cap1/" + vodfol + "/capc/%s" %
(histpic))
histbytes = cv2.imencode('.png',
histtemp)[1].tobytes() # ditto
histpic = histpic.replace('-', ':')
window['-histp-'].update(data=histbytes)
window['-history-'].update(histpic.replace('.jpg', ''))
if event == '-repic-':
cap = WebcamVideoStream(src="http://192.168.0.102:8081").start()
time.sleep(1)
if event == 'Prev' and capp:
if ptr <= len(capp):
ptr += 1
histpic = capp[len(capp) - ptr]
histtemp = cv2.imread("cap1/" + vodfol + "/capc/%s" % (histpic))
histbytes = cv2.imencode('.png', histtemp)[1].tobytes() # ditto
histpic = histpic.replace('-', ':')
window['-histp-'].update(data=histbytes)
window['-history-'].update(histpic.replace('.jpg', ''))
if event == 'Next' and capp:
if ptr > 1:
ptr -= 1
histpic = capp[len(capp) - ptr]
histtemp = cv2.imread("cap1/" + vodfol + "/capc/%s" % (histpic))
histbytes = cv2.imencode('.png', histtemp)[1].tobytes() # ditto
histpic = histpic.replace('-', ':')
window['-histp-'].update(data=histbytes)
window['-history-'].update(histpic.replace('.jpg', ''))
# --------bgsubtraction-----------#
if object_bounding_box is not None:
success, object_bounding_box = object_tracker.update(frame)
if success:
(x, y, w, h) = [int(v) for v in object_bounding_box]
cropped = frame[y:y + h, x:x + w].copy()
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
if (y + (h / 2) - 50) > frame.shape[0] / 2: # order gimbal
if count >= count_th:
inp = "u"
if s:
s.setinp(inp)
s.sendcommand()
window['-Gimbal-'].update(inp)
count = 0
elif (y + (h / 2)) + 50 < frame.shape[0] / 2:
if count >= count_th:
inp = "d"
if s:
s.setinp(inp)
s.sendcommand()
window['-Gimbal-'].update(inp)
count = 0
else:
if count >= count_th:
inp = "s"
if s:
s.setinp(inp)
s.sendcommand()
window['-Gimbal-'].update(inp)
count = 0
count += 1
if cropped is not None and cropped.sum() > 0:
count += 1
if cropped.shape[0] % 4 != 0 or cropped.shape[1] % 4 != 0:
cropped = cv2.resize(cropped, ((cropped.shape[1] // 4) * 4,
(cropped.shape[0] // 4) * 4))
gray = cv2.cvtColor(cropped, cv2.COLOR_RGB2GRAY)
mask = np.zeros(gray.shape, np.uint8)
if (isFirst):
mcd.init(gray)
isFirst = False
else:
try:
mask = mcd.run(gray)
except:
mcd.init(gray)
# find contours in area
(cnts, _) = cv2.findContours(mask.copy(), cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
for contour in cnts:
if (cv2.contourArea(contour) > objsize
and cv2.contourArea(contour) < objsize + 100):
(x, y, w, h) = cv2.boundingRect(contour)
if x <= objsize / 2 or x >= cropped.shape[
1] - objsize / 2 or x + w <= objsize / 2 or x + w >= cropped.shape[
1] - objsize / 2:
if fmeter >= 3:
cv2.imwrite("./cap1/%s/cap/%s.jpg" % (vodfol, s1),
cropped)
cv2.imwrite("./cap1/%s/capc/%s.jpg" % (vodfol, s1),
frame)
logging.warning(" ")
fcount += 1
window['-detected-'].update(s1)
count += 1
fmeter = 0
else:
fmeter += 1
elif y <= objsize / 2 or y >= cropped.shape[
0] - objsize / 2 or y + h <= objsize / 2 or y + h >= cropped.shape[
0] - objsize / 2:
if fmeter >= 3:
cv2.imwrite("./cap1/%s/cap/%s.jpg" % (vodfol, s1),
cropped)
cv2.imwrite("./cap1/%s/capc/%s.jpg" % (vodfol, s1),
frame)
logging.warning(" ")
fcount += 1
window['-detected-'].update(s1)
count += 1
fmeter = 0
else:
fmeter += 1
# showing
imgbytes = cv2.imencode('.png', frame)[1].tobytes() # ditto
image_elem.update(data=imgbytes)
fps.update()
fps.stop()
window['-FPS-'].update("{:.2f}".format(fps.fps() + 2))
if cropped is not None:
try:
# print(cropped.shape)
imgcropped = cv2.imencode('.png', cropped)[1].tobytes()
imgmarked = cv2.imencode('.png', mask)[1].tobytes()
cropped_elem.update(data=imgcropped)
masked_elem.update(data=imgmarked)
except:
continue
# Initialize object tracker, stabilizer, and video reader
object_tracker = cv2.TrackerCSRT_create()
stabilizer = VidStab()
vidcap = cv2.VideoCapture("ostrich.mp4")
# Initialize bounding box for drawing rectangle around tracked object
object_bounding_box = None
cap = cv2.VideoCapture(0)
while True:
# grabbed_frame, frame = vidcap.read()
grabbed_frame, frame = cap.read()
# Pass frame to stabilizer even if frame is None
stabilized_frame = stabilizer.stabilize_frame(input_frame=frame,
border_size=50)
# If stabilized_frame is None then there are no frames left to process
if stabilized_frame is None:
break
# Draw rectangle around tracked object if tracking has started
if object_bounding_box is not None:
success, object_bounding_box = object_tracker.update(stabilized_frame)
if success:
(x, y, w, h) = [int(v) for v in object_bounding_box]
crop_img = stabilized_frame[y:y + h, x:x + w]
cv2.rectangle(stabilized_frame, (x, y), (x + w, y + h),
(0, 255, 0), 2)
cv2.imshow('CROP', crop_img)
download_ostrich_video(ostrich_video_path)
# Init stabilizer and video reader
stabilizer = VidStab()
vidcap = cv2.VideoCapture(ostrich_video_path)
while True:
grabbed_frame, frame = vidcap.read()
if grabbed_frame:
# Do frame pre-processing
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Pass frame to stabilizer even if frame is None
stabilized_frame = stabilizer.stabilize_frame(input_frame=frame,
layer_func=layer_overlay,
border_size=100)
# If stabilized_frame is None then there are no frames left to process
if stabilized_frame is None:
break
# Display stabilized output
cv2.imshow('Stabilized Frame', stabilized_frame)
key = cv2.waitKey(5)
if key == 27:
break
vidcap.release()
cv2.destroyAllWindows()
import time
import cv2
from vidstab import VidStab
stabilizer = VidStab()
vidcap = cv2.VideoCapture(0)
start_time = time.time()
x = 1 # displays the frame rate every 1 second
counter = 0
while True:
grabbed_frame, frame = vidcap.read()
if frame is not None:
pass
stabilized_frame = stabilizer.stabilize_frame(input_frame=frame,smoothing_window=5)
img = cv2.putText(stabilized_frame,str(counter / (time.time() - start_time)),(20,30),cv2.FONT_HERSHEY_COMPLEX,1.2,(0,0,255),2)
if stabilized_frame is None:
break
cv2.imshow('Test',stabilized_frame)
counter+=1
if (time.time() - start_time) > x :
print("FPS: ", counter / (time.time() - start_time))
counter = 0
start_time = time.time()
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Importing libraries
import cv2
from vidstab import VidStab, layer_blend
# Initialize stabilizer and video reader
stabilizer = VidStab()
vidcap = cv2.VideoCapture("v1.mp4")
while True:
# Reading current frame
ret, frame = vidcap.read()
# Stabilization process
# Pass frame to stabilizer even if frame is None
stabilized_frame = stabilizer.stabilize_frame(input_frame=frame,
layer_func=layer_blend,
border_size=30)
# If stabilized_frame is None then there are no frames left to process
if stabilized_frame is None:
break
# Display stabilized output
cv2.imshow('Stabilized output', stabilized_frame)
key = cv2.waitKey(5)
if key == ord('q'):
break
vidcap.release()
cv2.destroyAllWindows()
face_encodings = []
face_names = []
process_this_frame = True
stabilizer = VidStab(kp_method='FAST', threshold=42, nonmaxSuppression=False)
frame0 = cv2.VideoCapture(0)
frame1 = cv2.VideoCapture(1)
while 1:
ret0, img1 = frame0.read()
ret1, img2 = frame1.read()
# img1 = cv2.resize(img0,(360,240))
# img2 = cv2.resize(img00,(360,240))
if (frame0):
cv2.imshow('img1', img1)
ret0, img1 = frame0.read()
stabilized_frame = stabilizer.stabilize_frame(input_frame=img1,
border_size=50)
small_frame = cv2.resize(stabilized_frame, (0, 0), fx=0.25, fy=0.25)
rgb_small_frame = small_frame[:, :, ::-1]
if process_this_frame:
face_locations = face_recognition.face_locations(rgb_small_frame)
face_encodings = face_recognition.face_encodings(
rgb_small_frame, face_locations)
face_names = []
for face_encoding in face_encodings:
matches = face_recognition.compare_faces(known_face_encodings,
face_encoding)
name = "Unknown"
face_distances = face_recognition.face_distance(
known_face_encodings, face_encoding)
best_match_index = np.argmin(face_distances)
if matches[best_match_index]: