ai-content-maker/.venv/Lib/site-packages/moviepy/video/fx/resize.py

166 lines
4.8 KiB
Python

resize_possible = True
try:
# TRY USING OpenCV AS RESIZER
#raise ImportError #debugging
import cv2
import numpy as np
def resizer (pic, newsize):
lx, ly = int(newsize[0]), int(newsize[1])
if lx > pic.shape[1] or ly > pic.shape[0]:
# For upsizing use linear for good quality & decent speed
interpolation = cv2.INTER_LINEAR
else:
# For dowsizing use area to prevent aliasing
interpolation = cv2.INTER_AREA
return cv2.resize(+pic.astype('uint8'), (lx, ly),
interpolation=interpolation)
resizer.origin = "cv2"
except ImportError:
try:
# TRY USING PIL/PILLOW AS RESIZER
from PIL import Image
import numpy as np
def resizer(pic, newsize):
newsize = list(map(int, newsize))[::-1]
shape = pic.shape
if len(shape)==3:
newshape = (newsize[0],newsize[1], shape[2] )
else:
newshape = (newsize[0],newsize[1])
pilim = Image.fromarray(pic)
resized_pil = pilim.resize(newsize[::-1], Image.ANTIALIAS)
#arr = np.fromstring(resized_pil.tostring(), dtype='uint8')
#arr.reshape(newshape)
return np.array(resized_pil)
resizer.origin = "PIL"
except ImportError:
# TRY USING SCIPY AS RESIZER
try:
from scipy.misc import imresize
resizer = lambda pic, newsize : imresize(pic,
map(int, newsize[::-1]))
resizer.origin = "Scipy"
except ImportError:
resize_possible = False
from moviepy.decorators import apply_to_mask
def resize(clip, newsize=None, height=None, width=None, apply_to_mask=True):
"""
Returns a video clip that is a resized version of the clip.
Parameters
------------
newsize:
Can be either
- ``(width,height)`` in pixels or a float representing
- A scaling factor, like 0.5
- A function of time returning one of these.
width:
width of the new clip in pixel. The height is then computed so
that the width/height ratio is conserved.
height:
height of the new clip in pixel. The width is then computed so
that the width/height ratio is conserved.
Examples
----------
>>> myClip.resize( (460,720) ) # New resolution: (460,720)
>>> myClip.resize(0.6) # width and heigth multiplied by 0.6
>>> myClip.resize(width=800) # height computed automatically.
>>> myClip.resize(lambda t : 1+0.02*t) # slow swelling of the clip
"""
w, h = clip.size
if newsize is not None:
def trans_newsize(ns):
if isinstance(ns, (int, float)):
return [ns * w, ns * h]
else:
return ns
if hasattr(newsize, "__call__"):
newsize2 = lambda t : trans_newsize(newsize(t))
if clip.ismask:
fun = lambda gf,t: (1.0*resizer((255 * gf(t)).astype('uint8'),
newsize2(t))/255)
else:
fun = lambda gf,t: resizer(gf(t).astype('uint8'),
newsize2(t))
return clip.fl(fun, keep_duration=True,
apply_to= (["mask"] if apply_to_mask else []))
else:
newsize = trans_newsize(newsize)
elif height is not None:
if hasattr(height, "__call__"):
fun = lambda t : 1.0*int(height(t))/h
return resize(clip, fun)
else:
newsize = [w * height / h, height]
elif width is not None:
if hasattr(width, "__call__"):
fun = lambda t : 1.0*width(t)/w
return resize(clip, fun)
newsize = [width, h * width / w]
# From here, the resizing is constant (not a function of time), size=newsize
if clip.ismask:
fl = lambda pic: 1.0*resizer((255 * pic).astype('uint8'), newsize)/255.0
else:
fl = lambda pic: resizer(pic.astype('uint8'), newsize)
newclip = clip.fl_image(fl)
if apply_to_mask and clip.mask is not None:
newclip.mask = resize(clip.mask, newsize, apply_to_mask=False)
return newclip
if not resize_possible:
doc = resize.__doc__
def resize(clip, newsize=None, height=None, width=None):
raise ImportError("fx resize needs OpenCV or Scipy or PIL")
resize.__doc__ = doc