use center frame of clip for sequence

This commit is contained in:
j 2013-08-03 13:11:34 +00:00
parent eb5e102512
commit 8c12ebcf99

View file

@ -81,63 +81,45 @@ def get_sequences(path, position=0):
sequences[mode][-1]['out'] = position
return sequences, position
class DataTimeline():
fps = 25
def __init__(self, path):
file_names = filter(lambda x: 'timelinedata8p' in x, os.listdir(path))
file_names = sorted(file_names, key=lambda x: int(x[14:-4]))
file_names = map(lambda x: path + x, file_names)
self.file_names = file_names
self.timeline_image = Image.open(file_names[0])
self.timeline_width = self.timeline_image.size[0]
self.current_tile = 0
def get_frame(self, pos):
frame = int(pos * self.fps)
tile = int(frame * 8 / self.timeline_width)
if self.current_tile != tile:
self.timeline_image = Image.open(self.file_names[tile])
self.current_tile = tile
x = frame * 8 - tile * self.timeline_width
return self.timeline_image.crop((x, 0, x + 8, 8))
def get_cut_sequences(stream, position=0):
path = stream.timeline_prefix
timeline = DataTimeline(stream.timeline_prefix)
cuts = list(stream.cuts) + [stream.duration]
modes = ['color', 'shape']
sequences = {}
for mode in modes:
sequences[mode] = []
position_start = position
fps = 25
file_names = filter(lambda x: 'timelinedata8p' in x, os.listdir(path))
file_names = sorted(file_names, key=lambda x: int(x[14:-4]))
file_names = map(lambda x: path + x, file_names)
def add_hash(cut, cut_data):
if sequences['color']:
start = sequences['color'][-1]['out']
else:
start = 0
end = position
frames = int(math.ceil((end - start) * fps))
#print 'add', start, end, frames
if frames:
cut_data /= frames
frame_image = Image.new('RGB', (8,8))
frame_image.putdata(list(tuple(pixel) for pixel in cut_data))
for mode in modes:
frame_hash = get_hash(frame_image, mode)
if sequences[mode] and sequences[mode][-1]['hash'] == frame_hash:
sequences[mode][-1]['out'] = end
else:
sequences[mode].append({
'hash': frame_hash,
'in': start,
'out': end,
})
else:
print 'fixme', cut_data
def next_cut():
if cuts:
cut = cuts.pop(0)
else:
cut = 0
return numpy.array(Image.new('RGB', (8,8)).getdata(), numpy.int64), cut
cut_data, cut = next_cut()
for file_name in file_names:
timeline_image = Image.open(file_name)
timeline_width = timeline_image.size[0]
for x in range(0, timeline_width, 8):
frame_image = timeline_image.crop((x, 0, x + 8, 8))
cut_data += numpy.array(frame_image.getdata(), numpy.int64)
position += 1 / fps
if cut and position > cut:
add_hash(cut, cut_data)
cut_data, cut = next_cut()
position += 1 / fps
add_hash(cut, cut_data)
return sequences, position
position = 0
for cut in cuts:
center = position + (cut - position) / 2
center -= center % 0.04
frame_image = timeline.get_frame(center)
for mode in modes:
frame_hash = get_hash(frame_image, mode)
sequences[mode].append({
'hash': frame_hash,
'in': position,
'out': cut,
})
position = cut
return sequences