from SimpleCV import ColorSegmentation, Image, Camera, VirtualCamera, Display, Color
# Open reference video
cam = VirtualCamera(
'../../Recording/Videos/kiteFlying from Zenith Wind Power-jn9RrUCiWKM.mp4',
'video')
# Select reference image
img = cam.getFrame(50)
modelImage = img.crop(255, 180, 70, 20)
modelImage = Image('../kite_detail.jpg')
ts = []
disp = Display()
for i in range(0, 50):
img = cam.getImage()
while (disp.isNotDone()):
img = cam.getImage()
bb = (255, 180, 70, 20)
ts = img.track("camshift", ts, modelImage, bb, num_frames=1)
modelImage = Image('../kite_detail.jpg')
# now here in first loop iteration since ts is empty,
# img0 and bb will be considered.
# New tracking object will be created and added in ts (TrackSet)
# After first iteration, ts is not empty and hence the previous
# image frames and bounding box will be taken from ts and img0
# and bb will be ignored.
ts.draw()
ts.drawBB()
ts.showCoordinates()
img.show()
from SimpleCV import JpegStreamer, Display, VirtualCamera, VideoStream
import time
import numpy as np
cam = VirtualCamera(
'../Recording/Videos/Flying kite images (for kite steering unit development)-YTMgX1bvrTo.flv',
'video')
port = 8000 + np.random.randint(100)
print port
js = JpegStreamer(hostandport=port, st=0.1)
vs = VideoStream("out.avi", fps=15)
endReached = False
t0 = time.time()
FPS = 25
while not (endReached):
t = time.time() - t0
toDisplay = cam.getFrame(np.ceil(t * FPS))
if toDisplay.size() != (0, 0):
toDisplay.save(js)
else:
endReached = True
time.sleep(0.05)
from SimpleCV import ColorSegmentation, Image, Camera, VirtualCamera, Display, Color
# Open reference video
cam=VirtualCamera('/media/bat/DATA/Baptiste/Nautilab/kite_project/zenith-wind-power-read-only/KiteControl-Qt/videos/kiteFlying.avi','video')
# Select reference image
img=cam.getFrame(50)
modelImage = img.crop(255, 180, 70, 20)
modelImage = Image('kite_detail.jpg')
ts = []
disp=Display()
for i in range(0,50):
img = cam.getImage()
while (disp.isNotDone()):
img = cam.getImage()
bb = (255, 180, 70, 20)
ts = img.track("camshift",ts,modelImage,bb, num_frames = 1)
modelImage = Image('kite_detail.jpg')
# now here in first loop iteration since ts is empty,
# img0 and bb will be considered.
# New tracking object will be created and added in ts (TrackSet)
# After first iteration, ts is not empty and hence the previous
# image frames and bounding box will be taken from ts and img0
# and bb will be ignored.
ts.draw()
ts.drawBB()
ts.showCoordinates()
img.show()
from SimpleCV import JpegStreamer, Display, VirtualCamera, VideoStream
import time
import numpy as np
cam = VirtualCamera('../Recording/Videos/Flying kite images (for kite steering unit development)-YTMgX1bvrTo.flv','video')
port = 8000+np.random.randint(100)
print port
js = JpegStreamer(hostandport=port
, st=0.1)
vs = VideoStream("out.avi", fps=15)
endReached = False
t0 = time.time()
FPS = 25
while not(endReached):
t = time.time()-t0
toDisplay = cam.getFrame(np.ceil(t*FPS))
if toDisplay.size()!=(0,0):
toDisplay.save(js)
else:
endReached = True
time.sleep(0.05)
