def CheckCropping(videopath,
filename,
x1,
x2,
y1,
y2,
cropping,
videotype,
time=start):
''' Display frame at time "time" for video to check if cropping is fine.
Select ROI of interest by adjusting values in myconfig.py
USAGE for cropping:
clip.crop(x1=None, y1=None, x2=None, y2=None, width=None, height=None, x_center=None, y_center=None)
Returns a new clip in which just a rectangular subregion of the
original clip is conserved. x1,y1 indicates the top left corner and
x2,y2 is the lower right corner of the croped region.
All coordinates are in pixels. Float numbers are accepted.
'''
videos = auxiliaryfunctions.GetVideoList(filename, videopath, videotype)
if filename != 'all':
videotype = filename.split('.')[1]
for vindex, video in enumerate(videos):
clip = VideoFileClip(os.path.join(videopath, video))
print("Extracting ", video)
ny, nx = clip.size # dimensions of frame (width, height)
if cropping == True:
# Select ROI of interest by adjusting values in myconfig.py
clip = clip.crop(y1=y1, y2=y2, x1=x1, x2=x2)
image = clip.get_frame(
time * clip.duration
) #frame is accessed by index *1./clip.fps (fps cancels)
io.imsave("IsCroppingOK" + video.split('.')[0] + ".png", image)
if vindex == len(videos) - 1:
print(
"--> Open the CroppingOK-videofilename-.png file(s) to set the output range! <---"
)
print("--> Adjust shiftx, shifty, fx and fy accordingly! <---")
return image
x2,y2 is the lower right corner of the croped region.
All coordinates are in pixels. Float numbers are accepted.
'''
image = clip.get_frame(1.2)
io.imsave("IsCroppingOK.png", image)
print("--> Open CroppingOK.png file to set the output range! <---")
print("--> Adjust shiftx, shifty, fx and fy accordingly! <---")
####################################################
# Creating folder with name of experiment and extract random frames
####################################################
print("Videoname: ", filename)
folder = filename.split('.')[0]
auxiliaryfunctions.attempttomakefolder(basefolder + folder)
frames = np.random.randint(math.floor(clip.duration * clip.fps * portion),
size=numframes2pick - 1)
width = int(np.ceil(np.log10(clip.duration * clip.fps)))
for index in frames:
try:
image = img_as_ubyte(clip.get_frame(index * 1. / clip.fps))
io.imsave(
basefolder + folder + "/img" + str(index).zfill(width) + ".png",
image)
except:
print("Frame # ", index, " does not exist.")
basefolder = './' + 'data-' + Task
numbodyparts = len(bodyparts)
# Data frame to hold data of all data sets for different scorers, bodyparts and images
DataCombined = None
os.chdir(basefolder)
DataCombined = pd.read_hdf(
'CollectedData_' + cfg_scorer + '.h5', 'df_with_missing')
# Make list of different video data sets:
folders = [
videodatasets for videodatasets in os.listdir(os.curdir)
if os.path.isdir(videodatasets) and
filename.split('.')[0] in videodatasets and 'labeled' not in videodatasets
]
print(folders)
# videos=np.sort([fn for fn in os.listdir(os.curdir) if ("avi" in fn)])
scale = 1 # for plotting
msize=25 #size of labels
for folder in folders:
tmpfolder = folder + 'labeled'
try:
os.mkdir(tmpfolder)
except:
pass
os.chdir(folder)
# sort image file names according to how they were stacked (when labeled in Fiji)
basefolder = './' + 'data-' + Task
numbodyparts = len(bodyparts)
# Data frame to hold data of all data sets for different scorers, bodyparts and images
DataCombined = None
os.chdir(basefolder)
DataCombined = pd.read_hdf('CollectedData_' + cfg_scorer + '.h5',
'df_with_missing')
# Make list of different video data sets:
folders = [
videodatasets for videodatasets in os.listdir(os.curdir)
if os.path.isdir(videodatasets) and filename.split('.')[0] in videodatasets
and 'labeled' not in videodatasets
]
print(folders)
# videos=np.sort([fn for fn in os.listdir(os.curdir) if ("avi" in fn)])
scale = 1 # for plotting
msize = 25 #size of labels
for folder in folders:
tmpfolder = folder + 'labeled'
try:
os.mkdir(tmpfolder)
except:
pass
os.chdir(folder)