def get_mask_data(maskFile, vid, hMatrix=None, check=False):
"""
Shows user masks overlayed on given image and asks through a dialog box
if they are acceptable. Returns True for 'yes' and False for 'no'.
"""
# Parse input parameters
image = VF.extract_frame(vid, 1, hMatrix=hMatrix)
try:
with open(maskFile) as f:
maskData = pkl.load(f)
except:
print 'Mask file not found, please create it now.'
maskData = IPF.create_mask_data(image, maskFile)
while check:
plt.figure('Evaluate accuracy of predrawn masks for your video')
maskedImage = IPF.mask_image(image, maskData['mask'])
temp = np.dstack((maskedImage, image, image))
plt.imshow(temp)
center = maskData['diskCenter']
plt.plot(center[0], center[1], 'bx')
plt.axis('image')
response = ctypes.windll.user32.MessageBoxA(0, 'Do you wish to keep' + \
' the current mask?','User Input Required', 4)
plt.close()
if response == 6: # 6 means yes
return maskData
else: # 7 means no
print 'Existing mask rejected, please create new one now.'
maskData = IPF.create_mask_data(image, maskFile)
return maskData
def get_homography_matrix(fileName, vid):
"""
Load the homography matrix from file or create it if it does not exist.
"""
# Handle homography data file
if fileName is not None:
try:
with open(fileName, 'rb') as f:
hMatrix = pkl.load(f)
except:
image = VF.extract_frame(vid, 0)
else:
hMatrix = None
return hMatrix
def get_intensity_region(fileName, vid):
"""
Identify a region of the video frames to use for monitoring light
intensity.
"""
try:
with open(fileName, 'rb') as f:
mask = pkl.load(f)
except:
image = VF.extract_frame(vid, 0)
plt.gray()
plt.close()
points = define_outer_edge(
image, 'polygon',
'Define a region for \n' + 'monitoring light intensity.')
mask, points = IPF.create_polygon_mask(image, points)
with open(fileName, 'wb') as f:
pkl.dump(mask, f)
return mask
t0 = tic()
t1 = tic()
# Get list of video files to process
pathToFiles = os.path.join(folder,fileString)
fileList = glob.glob(pathToFiles)
dataList = glob.glob(os.path.join(folder,'*' + suffix))
N = len(fileList)
hMatrix = 0
for i in range(0,N,1):
# Parse the filename to get video info
videoPath = fileList[i]
print os.path.split(videoPath)[1]
dataFile = fileList[i][:-4] + suffix
RPM = VF.get_RPM_from_file_name(videoPath)
fps = VF.get_FPS_from_file_name(videoPath)
flowRate = VF.get_flowRate_from_file_name(videoPath)
vid = VF.get_video_object(videoPath)
# Ignore videos for which the reference frame has been rotated
if '_rot' in videoPath:
continue
# Load homography matrix then mask data
if hMatrix is 0:
# Load homography matrix
hMatrix = UIF.get_homography_matrix(homographyFile,vid)
# Get mask data for ignoring areas not of interest
maskData = UIF.get_mask_data(maskFile,vid,hMatrix,checkMasks)
# Load original data file and video file
temp = glob.glob(dataFile)[0]
with open(temp, 'rb') as f:
container = pkl.load(f)
hMatrix = container['hMatrix']
maskData = container['maskData']
temp = maskData['diskMask']
maskData['mask'] = temp
center = maskData['diskCenter']
R = maskData['diskRadius']
pix_per_cm = container['maskData']['diskRadius'] / diskScale
cropRect = [
center[0] - R, center[0] + R, center[1] - R, center[1] + R
]
vid = VF.get_video_object(videoPath)
# Load rCrit and determine corresponding frame number
rCritQList = rCritData['QList']
rCritRPMList = rCritData['RPMList']
i_Q = [
k for k in range(len(rCritQList)) if QTarget == rCritQList[k]
]
j_RPM = [
k for k in range(len(rCritRPMList)) if RPM == rCritRPMList[k]
]
rCrit = rCritData[condition][i_Q, j_RPM]
num = [
k for k in range(len(aMean))
if aMean[k + 1] >= rCrit and aMean[k] <= rCrit
]