287 lines
12 KiB
Python
287 lines
12 KiB
Python
# -*- coding: utf-8 -*-
|
|
from __future__ import division, with_statement, print_function
|
|
|
|
import math
|
|
import os
|
|
import re
|
|
|
|
from PIL import Image
|
|
from ox.utils import json
|
|
|
|
__all__ = ['join_tiles', 'split_tiles']
|
|
|
|
def divide(num, by):
|
|
# divide(100, 3) -> [33, 33, 34]
|
|
arr = []
|
|
div = int(num / by)
|
|
mod = num % by
|
|
for i in range(int(by)):
|
|
arr.append(div + (i > by - 1 - mod))
|
|
return arr
|
|
|
|
def join_tiles(source_paths, durations, target_path):
|
|
'''
|
|
This is an implementation of a join_tiles function for new-style timelines.
|
|
Timelines of files will be read from source_paths, the timeline of the item will
|
|
be written to target_path.
|
|
'''
|
|
|
|
def get_file_info(file_name):
|
|
for mode in modes:
|
|
if re.match('^timeline' + mode + '64p\d+\.jpg', file_name):
|
|
return {
|
|
'file': file_name,
|
|
'mode': mode,
|
|
'index': int(file_name[11 + len(mode):-4])
|
|
}
|
|
return None
|
|
|
|
def save_and_open(data):
|
|
# whenever a large tile is done or needed,
|
|
# this function saves the previous large tile
|
|
# (if any) and opens the next one (if any).
|
|
# in between, whenever required, small tiles
|
|
# are opened, rendered and saved, and the
|
|
# large full tile is being generated.
|
|
# 'keyframes' are only rendered in large size,
|
|
# 'keyframeswide' only resized to small size.
|
|
image_mode = 'L' if mode == 'audio' else 'RGB'
|
|
small_mode = 'keyframes' if mode == 'keyframeswide' else mode
|
|
large_tile_i = int(target_w / large_tile_w)
|
|
# save previous large tile
|
|
if large_tile_i > 0:
|
|
large_tile_i -= 1
|
|
if mode != 'keyframeswide':
|
|
image_file = '%stimeline%s%dp%d.jpg' % (
|
|
target_path, mode, large_tile_h, large_tile_i
|
|
)
|
|
data['target_images']['large'].save(image_file)
|
|
#print(image_file)
|
|
if mode != 'keyframes':
|
|
# open small tile
|
|
small_tile_i = int(large_tile_i / 60)
|
|
small_tile_x = (large_tile_i % 60) * 60
|
|
if small_tile_x == 0:
|
|
if small_tile_i < small_tile_n - 1:
|
|
w = small_tile_w
|
|
else:
|
|
w = small_tile_last_w
|
|
data['target_images']['small'] = Image.new(image_mode, (w, small_tile_h))
|
|
# paste large tile into small tile
|
|
w = small_tile_last_w % 60
|
|
if not w or large_tile_i < large_tile_n - 1:
|
|
w = 60
|
|
data['target_images']['large'] = data['target_images']['large'].resize(
|
|
(w, small_tile_h), Image.ANTIALIAS
|
|
)
|
|
if data['target_images']['small']:
|
|
data['target_images']['small'].paste(
|
|
data['target_images']['large'], (small_tile_x, 0)
|
|
)
|
|
# save small tile
|
|
if small_tile_x == small_tile_w - 60 or large_tile_i == large_tile_n - 1:
|
|
image_file = '%stimeline%s%dp%d.jpg' % (
|
|
target_path, small_mode, small_tile_h, small_tile_i
|
|
)
|
|
data['target_images']['small'].save(image_file)
|
|
#print(image_file)
|
|
if mode == full_tile_mode:
|
|
# render full tile
|
|
if data['full_tile_widths']:
|
|
if data['full_tile_widths'][0]:
|
|
resized = data['target_images']['large'].resize((
|
|
data['full_tile_widths'][0], large_tile_h
|
|
), Image.ANTIALIAS)
|
|
data['target_images']['full'].paste(resized, (data['full_tile_offset'], 0))
|
|
data['full_tile_offset'] += data['full_tile_widths'][0]
|
|
data['full_tile_widths'] = data['full_tile_widths'][1:]
|
|
large_tile_i += 1
|
|
# open next large tile
|
|
if large_tile_i < large_tile_n:
|
|
w = large_tile_w if large_tile_i < large_tile_n - 1 else large_tile_last_w
|
|
data['target_images']['large'] = Image.new(image_mode, (w, large_tile_h))
|
|
|
|
data = {}
|
|
fps = 25
|
|
large_tile_w, large_tile_h = 1500, 64
|
|
small_tile_w, small_tile_h = 3600, 16
|
|
full_tile_w = 1920
|
|
modes = ['antialias', 'slitscan', 'keyframes', 'keyframeswide', 'audio']
|
|
source_files = {}
|
|
for mode in modes:
|
|
source_files[mode] = {}
|
|
|
|
# read files
|
|
frame_n = 0
|
|
offset = 0
|
|
offsets = set()
|
|
for i, path in enumerate(source_paths):
|
|
file_info = map(get_file_info, os.listdir(path))
|
|
file_info = list(filter(lambda x: x is not None, file_info))
|
|
files = {}
|
|
for info in sorted(file_info, key=lambda x: x['index']):
|
|
mode = info['mode']
|
|
if mode not in files:
|
|
files[mode] = []
|
|
files[mode].append(path + info['file'])
|
|
if i:
|
|
offset = int(sum(durations[:i]) * 25)
|
|
for mode in files:
|
|
source_files[mode][offset] = files[mode]
|
|
offsets.add(offset)
|
|
|
|
modes = [m for m in modes if source_files[m]]
|
|
for offset in sorted(offsets):
|
|
for mode in modes:
|
|
if offset not in source_files[mode]:
|
|
source_files[mode][offset] = []
|
|
last_offset = max(offsets)
|
|
frame_n = last_offset
|
|
for f in source_files[modes[0]][last_offset]:
|
|
width = Image.open(f).size[0]
|
|
frame_n += width
|
|
large_tile_n = int(math.ceil(frame_n / large_tile_w))
|
|
large_tile_last_w = frame_n % large_tile_w or 60
|
|
small_tile_n = int(math.ceil(frame_n / fps / small_tile_w))
|
|
small_tile_last_w = int(math.ceil(frame_n / fps)) % small_tile_w or small_tile_w
|
|
full_tile_mode = modes[0]
|
|
|
|
# open full timeline
|
|
if large_tile_n == 1:
|
|
data['full_tile_widths'] = [large_tile_last_w]
|
|
else:
|
|
w = full_tile_w
|
|
n = large_tile_n
|
|
if large_tile_last_w < large_tile_w:
|
|
factor = full_tile_w / frame_n
|
|
last_w = int(round(large_tile_last_w * factor))
|
|
w -= last_w
|
|
n -= 1
|
|
data['full_tile_widths'] = divide(w, n)
|
|
if large_tile_last_w < large_tile_w:
|
|
data['full_tile_widths'].append(last_w)
|
|
data['full_tile_offset'] = 0
|
|
full_tile_image = Image.new('RGB', (full_tile_w, large_tile_h))
|
|
|
|
# main loop
|
|
data['target_images'] = {'large': None, 'small': None, 'full': full_tile_image}
|
|
for mode in modes:
|
|
target_w = 0
|
|
for offset in sorted(source_files[mode]):
|
|
target_w = offset
|
|
for source_file in source_files[mode][offset]:
|
|
source_image = Image.open(source_file)
|
|
source_w = source_image.size[0]
|
|
target_x = target_w % large_tile_w
|
|
if target_x == 0:
|
|
save_and_open(data)
|
|
data['target_images']['large'].paste(source_image, (target_x, 0))
|
|
target_w += source_w
|
|
if target_x + source_w > large_tile_w:
|
|
# target tile overflows into next source tile
|
|
save_and_open(data)
|
|
target_x -= large_tile_w
|
|
data['target_images']['large'].paste(source_image, (target_x, 0))
|
|
if not source_files[mode][offset]:
|
|
save_and_open(data)
|
|
# save_and_open saves previous tile and opens tile at target_w
|
|
# increase target_w to be in next tile
|
|
target_w += large_tile_w
|
|
save_and_open(data)
|
|
|
|
if data['full_tile_offset'] < full_tile_w:
|
|
data['target_images']['full'] = data['target_images']['full'].crop((0,0, data['full_tile_offset'], large_tile_h))
|
|
# save full timelines
|
|
image_file = '%stimeline%s%dp.jpg' % (target_path, full_tile_mode, large_tile_h)
|
|
data['target_images']['full'].save(image_file)
|
|
#print(image_file)
|
|
image_file = '%stimeline%s%dp.jpg' % (target_path, full_tile_mode, small_tile_h)
|
|
data['target_images']['full'].resize(
|
|
(full_tile_w, small_tile_h), Image.ANTIALIAS
|
|
).save(image_file)
|
|
#print(image_file)
|
|
|
|
# join cuts
|
|
cuts = []
|
|
offset = 0
|
|
for i, path in enumerate(source_paths):
|
|
p = os.path.join(path, 'cuts.json')
|
|
if os.path.exists(p):
|
|
with open(p, 'r') as f:
|
|
path_cuts = json.load(f)
|
|
else:
|
|
path_cuts = []
|
|
if i > 0:
|
|
cuts.append(offset)
|
|
for cut in path_cuts:
|
|
cuts.append(offset + cut)
|
|
offset += durations[i]
|
|
with open(os.path.join(target_path, 'cuts.json'), 'w') as f:
|
|
# avoid float rounding artefacts
|
|
f.write('[' + ', '.join(map(lambda x: '%.2f' % x, cuts)) + ']')
|
|
|
|
def split_tiles(path, paths, durations):
|
|
|
|
def is_timeline_file(file_name):
|
|
return file_name.startswith('timeline') and file_name.endswith('.png')
|
|
|
|
file_names = list(filter(is_timeline_file, os.listdir(path)))
|
|
tiles = {}
|
|
for file_name in file_names:
|
|
mode = re.split('\d+', file_name[8:])[0]
|
|
split = re.split('[a-z]+', file_name[8 + len(mode):-4])
|
|
height, index = map(lambda x: int(x) if len(x) else -1, split)
|
|
if mode not in tiles:
|
|
tiles[mode] = {}
|
|
if height not in tiles[mode]:
|
|
tiles[mode][height] = 0
|
|
if index + 1 > tiles[mode][height]:
|
|
tiles[mode][height] = index + 1
|
|
|
|
# for each mode
|
|
for mode in tiles:
|
|
image_mode = 'L' if mode == 'audio' else 'RGB'
|
|
# and for each size of that mode
|
|
for i, height in enumerate(tiles[mode]):
|
|
tile_width = 1500 if i == 0 else 3600
|
|
px_per_sec = 25 if i == 0 else 1
|
|
target_images = []
|
|
target_data = []
|
|
# and for each split item
|
|
for item_index, duration in enumerate(durations):
|
|
tile_index = 0
|
|
px = int(math.ceil(duration * px_per_sec))
|
|
# create a flat list of all target images
|
|
# (and store the split item and tile index)
|
|
while px:
|
|
width = tile_width if px > tile_width else px
|
|
target_images.append(
|
|
Image.new(image_mode, (width, height))
|
|
)
|
|
target_data.append(
|
|
{'item': item_index, 'tile': tile_index}
|
|
)
|
|
tile_index += 1
|
|
px -= width
|
|
target_index = 0
|
|
offset = 0
|
|
# for each source tile
|
|
for source_index in range(tiles[mode][height]):
|
|
source_image = Image.open('%stimeline%s%dp%d.png' % (
|
|
path, mode, height, source_index
|
|
))
|
|
source_width = source_image.size[0]
|
|
target_width = target_images[target_index].size[0]
|
|
target_images[target_index].paste(source_image, (offset, 0))
|
|
# paste it into as many target tiles as needed
|
|
while source_width + offset > target_width:
|
|
offset -= target_width
|
|
target_index += 1
|
|
target_width = target_images[target_index].size[0]
|
|
target_images[target_index].paste(source_image, (offset, 0))
|
|
for i, target_image in enumerate(target_images):
|
|
file_name = '%stimeline%s%dp%d' % (
|
|
paths[target_data[i]['item']], mode, height, target_data[i]['tile']
|
|
)
|
|
# target_image.save(file_name)
|
|
|