from jasf import jasf_cv
import flowUtil
import numpy as np
from flowSubtraction import FlowDiffComputer
if __name__ == "__main__":
cam = cv2.VideoCapture(
'./input/inputTest-butter-from-0.5-to-10-alpha-20-lambda_c-80-chromAtn-0.avi'
)
#get first frame so we set width and whigth of the flow computer
ret, frame = cam.read()
flowComputer = flowUtil.FlowComputer()
width, height = frame.shape[1], frame.shape[0]
grid = flowUtil.getGrid(0, 0, width - 5, height - 5, 10, 10)
flowComputer.setGrid(grid)
#initialize flowComputer with first frame(at this point, we have only one image and no flow is computer)
flowComputer.apply(frame)
#initialize flow diff computer
diffComputer = FlowDiffComputer(flowComputer)
allBlack = np.zeros((height, width), dtype=np.uint8)
#find optimal size for fourrier transform
rows, cols, k = frame.shape
nrows = cv2.getOptimalDFTSize(rows)
ncols = cv2.getOptimalDFTSize(cols)
modeDemoSpectrum = False
import sys
sys.path.insert(0, '../')
import jasf
from jasf import jasf_cv
import cv2
import flowUtil
cam = cv2.VideoCapture(0)
ret, frame = cam.read()
h, w, d = frame.shape
print frame.shape
half_side = 200
grid = flowUtil.getGrid(w / 2 - half_side, h / 2 - half_side, half_side * 2,
half_side * 2, 5, 5)
flowComputer = flowUtil.FlowComputer()
flowComputer.setGrid(grid)
ret, frame = cam.read()
flowFilter = flowUtil.FlowFilter()
flowFilter2 = flowUtil.FlowFilter_ConnectedRegions(frame.shape[:2])
jasf_cv.getInputWindow()
jasf_cv.getSettingsWindow()
jasf.cv.setManyTrackbars(['low', 'upper'], [10, 25], [100, 100])
jasf.cv.setManyTrackbars(['low2', 'upper2'], [150, 50000], [10000, 50000])
while cam.isOpened():
ch = cv2.waitKey(5) & 0xFFFF
if __name__ == "__main__":
def help():
print 'usage: python RangePerCentFlowComputer option'
print 'option maybe "regular" or "window"'
quit()
print 'running test mode of RangePerCentFlowComputer...'
cam = cv2.VideoCapture(0)
if len(sys.argv) != 2 or sys.argv[1] not in ('regular', 'window'):
help()
mode = sys.argv[1]
unit = RangePerCentFlowComputer_regularComputer() if mode == 'regular' else RangePerCentFlowComputer_windowFlow()
h,w = jasf.cv.getVideoCaptureFrameHeightWidth(cam)
unit.setGrid(flowUtil.getGrid(0,0, w, h, 10, 10))
jasf_cv.getBasicWindows()
ret,frame = cam.read()
output = np.zeros_like(frame)
jasf.cv.setManyTrackbars(['min', 'max'], [95, 100], [100,100])
def readSettings():
min,max = jasf.cv.readManyTrackbars(['min', 'max'])
return min/100.0, max/100.0
while True:
ch = cv2.waitKey(30) & 0xFFFF
if ch == ord('q'):
else:
grid = self.flowComputer.grid.astype(np.uint64)
if returnIndo2Draw:
return grid, grid
else:
return grid, np.zeros(grid.shape[0])
if __name__ == "__main__":
cam = cv2.VideoCapture(0)
#get first frame so we set width and whigth of the flow computer
ret, frame = cam.read()
flowComputer = flowUtil.FlowComputer()
width, height = frame.shape[1], frame.shape[0]
grid = flowUtil.getGrid(5, 5, width - 5, height - 5, 10, 10)
flowComputer.setGrid(grid)
#initialize flowComputer with first frame(at this point, we have only one image and no flow is computer)
flowComputer.apply(frame)
#initialize flow diff computer
diffComputer = FlowDiffComputer(flowComputer)
#initialize windows to be used
jasf.cv.getManyWindows(['input', 'flowDiffMag'])
allBlack = np.zeros((height, width), dtype=np.uint8)
while True:
#quit if 'q' is pressed
ch = jasf.cv.waitKey(5)
print 'usage: python RangePerCentFlowComputer option'
print 'option maybe "regular" or "window"'
quit()
print 'running test mode of RangePerCentFlowComputer...'
cam = cv2.VideoCapture(0)
if len(sys.argv) != 2 or sys.argv[1] not in ('regular', 'window'):
help()
mode = sys.argv[1]
unit = RangePerCentFlowComputer_regularComputer(
) if mode == 'regular' else RangePerCentFlowComputer_windowFlow()
h, w = jasf.cv.getVideoCaptureFrameHeightWidth(cam)
unit.setGrid(flowUtil.getGrid(0, 0, w, h, 10, 10))
jasf_cv.getBasicWindows()
ret, frame = cam.read()
output = np.zeros_like(frame)
jasf.cv.setManyTrackbars(['min', 'max'], [95, 100], [100, 100])
def readSettings():
min, max = jasf.cv.readManyTrackbars(['min', 'max'])
return min / 100.0, max / 100.0
while True:
ch = cv2.waitKey(30) & 0xFFFF
if ch == ord('q'):
# debug cv2.imshow('average2', average2)
return good_old, good_new
else:
self.addToAverage(img)
return np.empty((0,0), dtype = np.uint8), np.empty((0,0), dtype = np.uint8)
if __name__ == "__main__":
print 'running test mode of WindowFlowComputer...'
cam = cv2.VideoCapture(0)
unit = WindowFlowComputer()
h,w = jasf.cv.getVideoCaptureFrameHeightWidth(cam)
unit.setGrid(flowUtil.getGrid(w/2,h/2, 100, 100, 10, 10))
jasf.cv.getManyWindows(['input', 'output', 'average1', 'average2'])
ret,frame = cam.read()
output = np.zeros_like(frame)
while True:
ch = cv2.waitKey(30) & 0xFFFF
if ch == ord('q'):
break
ret, frame = cam.read()
frame = jasf_cv.convertBGR2Gray(frame)
old, new = unit.apply(frame)
if old.size != 0:
return good_old, good_new
else:
self.addToAverage(img)
return np.empty((0, 0), dtype=np.uint8), np.empty((0, 0),
dtype=np.uint8)
if __name__ == "__main__":
print 'running test mode of WindowFlowComputer...'
cam = cv2.VideoCapture(0)
unit = WindowFlowComputer()
h, w = jasf.cv.getVideoCaptureFrameHeightWidth(cam)
unit.setGrid(flowUtil.getGrid(w / 2, h / 2, 100, 100, 10, 10))
jasf.cv.getManyWindows(['input', 'output', 'average1', 'average2'])
ret, frame = cam.read()
output = np.zeros_like(frame)
while True:
ch = cv2.waitKey(30) & 0xFFFF
if ch == ord('q'):
break
ret, frame = cam.read()
frame = jasf_cv.convertBGR2Gray(frame)
old, new = unit.apply(frame)
if old.size != 0:
from jasf import jasf_cv
import flowUtil
import numpy as np
from flowSubtraction import FlowDiffComputer
if __name__ == "__main__":
cam = cv2.VideoCapture('./input/inputTest-butter-from-0.5-to-10-alpha-20-lambda_c-80-chromAtn-0.avi')
#get first frame so we set width and whigth of the flow computer
ret, frame = cam.read()
flowComputer = flowUtil.FlowComputer()
width, height = frame.shape[1], frame.shape[0]
grid = flowUtil.getGrid(0,0, width-5, height-5, 10,10)
flowComputer.setGrid(grid)
#initialize flowComputer with first frame(at this point, we have only one image and no flow is computer)
flowComputer.apply(frame)
#initialize flow diff computer
diffComputer = FlowDiffComputer(flowComputer)
allBlack = np.zeros((height, width), dtype=np.uint8)
#find optimal size for fourrier transform
rows,cols,k = frame.shape
nrows = cv2.getOptimalDFTSize(rows)
ncols = cv2.getOptimalDFTSize(cols)
import sys
sys.path.insert(0, '../')
import jasf
from jasf import jasf_cv
import cv2
import flowUtil
cam = cv2.VideoCapture(0)
ret, frame = cam.read()
h,w,d = frame.shape
print frame.shape
half_side = 200
grid = flowUtil.getGrid(w/2-half_side, h/2 - half_side, half_side*2, half_side*2, 5, 5)
flowComputer = flowUtil.FlowComputer()
flowComputer.setGrid(grid)
ret, frame = cam.read()
flowFilter = flowUtil.FlowFilter()
flowFilter2 = flowUtil.FlowFilter_ConnectedRegions(frame.shape[:2])
jasf_cv.getInputWindow()
jasf_cv.getSettingsWindow()
jasf.cv.setManyTrackbars(['low', 'upper'], [10, 25], [100, 100])
jasf.cv.setManyTrackbars(['low2', 'upper2'], [150, 50000], [10000, 50000])
while cam.isOpened():
ch = cv2.waitKey(5) & 0xFFFF