def load(scale, settings):
arrow_frames = []
for x in range(120, 100, -4):
img = YImage(reversearrow, settings, scale * x / 100, rotate=1)
arrow_frames.append(img.img)
sliderb_frames = YImages(sliderb, settings, scale).frames
sliderfollow_frames = YImages(sliderfollowcircle, settings, scale).frames
slider_tick = YImage(sliderscorepoint, settings, scale).img
return arrow_frames, sliderb_frames, sliderfollow_frames, slider_tick
def prepare_hitresults(scale, diff, settings):
cs = (54.4 - 4.48 * diff["CircleSize"]) * scale
scale = cs * 2 * hitresult_size / default_size
particles_frames = prepare_particles(scale, settings)
scores_frames = {}
singleframemiss = False
for x in [0, 50, 100, 300]:
yimg = YImages(hitprefix + str(x),
settings,
scale,
delimiter="-",
rotate=x == 0)
f = []
f1 = yimg.frames
if yimg.unanimate or len(yimg.frames) == 1:
img = yimg.frames[0]
f = []
if x != 0:
f = size.grow(img, 0.7, 1.1, 0.05)
if x == 0:
if yimg.unanimate or len(yimg.frames) == 1:
f1 = f1[0]
f1 = size.shrink(f1, 1.45, 0.9, 0.05)
f = []
singleframemiss = len(yimg.frames) == 1
if x in particles_frames:
f = []
f1 = particles_frames[x]
scores_frames[x] = f + f1
return scores_frames, singleframemiss
def prepare_fpmanager(scale, settings):
"""
:param settings:
:param path: string
:param scale: float
:return: [PIL.Image]
"""
fp = YImages(followpoints, settings, scale * 0.5, delimiter="-", rotate=1)
return fp.frames
def load(settings):
circle = YImage(hitcircle, settings).img
c_overlay = YImages(hitcircleoverlay, settings, delimiter="-").frames[0]
yslider = YImage(sliderstartcircle, settings, fallback=hitcircle)
slider = yslider.img
slideroverlay = sliderstartcircleoverlay
if yslider.imgfrom == ImageFrom.FALLBACK_X or yslider.imgfrom == ImageFrom.FALLBACK_X2:
slideroverlay = hitcircleoverlay
s_overlay = YImage(slideroverlay, settings, fallback=hitcircleoverlay).img
return circle, c_overlay, slider, s_overlay
def prepare_scorebar(scale, settings):
"""
:param settings:
:param scale: float
:return: [PIL.Image]
"""
yimg = YImages(scorebar, settings, scale, delimiter="-")
img = yimg.frames
defaultpath = yimg.imgfrom == ImageFrom.DEFAULT_X or yimg.imgfrom == ImageFrom.DEFAULT_X2
yimgmarker = YImage(scorebarmarker,
settings,
scale,
defaultpath=defaultpath,
fallback="reeee")
marker = yimgmarker.img
hasmarker = yimgmarker.imgfrom != ImageFrom.BLANK
return img, marker, hasmarker
def prepare_rankinghitresults(scale, settings):
scores_frames = {}
scale *= 0.5
bonus = {100: "k", 300: "g"}
for x in [0, 50, 100, 300]:
yimg = YImage(hitprefix + str(x), settings, scale)
scores_frames[x] = yimg.img
if x > 50:
yimg = YImage(hitprefix + str(x) + bonus[x],
settings,
scale,
fallback="reeee")
img = yimg.img
if yimg.imgfrom == ImageFrom.BLANK:
yimg = YImages(hitprefix + str(x) + bonus[x],
settings,
scale,
delimiter="-")
img = yimg.frames[0]
scores_frames[x + 5] = img
return scores_frames
def prepare_rankingcombo(scale, settings):
img = YImages(rankingcombo, settings, scale, "-").frames
return img
def prepare_menuback(scale, settings):
img = YImages(menuback, settings, scale, delimiter="-").frames
return img
def prepare_rankinggraph(scale, settings):
img = YImage(rankinggraph, settings, scale).img
perfectimg = YImages(rankingperfect, settings, scale,
delimiter="-").frames[0]
return [img, perfectimg]
def prepare_rankingaccuracy(scale, settings):
img = YImages(rankingaccuracy, settings, scale, delimiter="-").frames
return img