def SelectFrames(videopath, filename, x1, x2, y1, y2, cropping, videotype,
start, stop, Task, selectionalgorithm):
''' Selecting frames from videos for labeling.'''
if start > 1.0 or stop > 1.0 or start < 0 or stop < 0 or start >= stop:
print(
"Please change start & stop, they should form a normalized interval with 0<= start < stop<=1."
)
else:
basefolder = 'data-' + Task + '/'
auxiliaryfunctions.attempttomakefolder(basefolder)
videos = auxiliaryfunctions.GetVideoList(filename, videopath,
videotype)
for vindex, video in enumerate(videos):
print("Loading ", video)
clip = VideoFileClip(os.path.join(videopath, video))
print("Duration of video [s], ", clip.duration, "fps, ", clip.fps,
"Cropped frame dimensions: ", clip.size)
####################################################
# Creating folder with name of experiment and extract random frames
####################################################
folder = video.split('.')[0]
auxiliaryfunctions.attempttomakefolder(
os.path.join(basefolder, folder))
indexlength = int(np.ceil(np.log10(clip.duration * clip.fps)))
# Extract the first frame (not cropped!) - useful for data augmentation
index = 0
image = img_as_ubyte(clip.get_frame(index * 1. / clip.fps))
io.imsave(
os.path.join(basefolder, folder,
"img" + str(index).zfill(indexlength) + ".png"),
image)
if cropping == True:
# Select ROI of interest by adjusting values in myconfig.py
clip = clip.crop(y1=y1, y2=y2, x1=x1, x2=x2)
print("Extracting frames ...")
if selectionalgorithm == 'uniform':
frames2pick = frameselectiontools.UniformFrames(
clip, numframes2pick, start, stop)
elif selectionalgorithm == 'kmeans':
frames2pick = frameselectiontools.KmeansbasedFrameselection(
clip, numframes2pick, start, stop)
else:
print(
"Please implement this method yourself and send us a pull request!"
)
frames2pick = []
indexlength = int(np.ceil(np.log10(clip.duration * clip.fps)))
for index in frames2pick:
try:
image = img_as_ubyte(clip.get_frame(index * 1. / clip.fps))
io.imsave(
os.path.join(
basefolder, folder,
"img" + str(index).zfill(indexlength) + ".png"),
image)
except FileNotFoundError:
print("Frame # ", index, " does not exist.")
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