Source code for

import numpy as np

from import CompositeAudioClip
from import ColorClip, VideoClip

#  CompositeVideoClip

[docs]class CompositeVideoClip(VideoClip): """ A VideoClip made of other videoclips displayed together. This is the base class for most compositions. Parameters ---------- size The size (height x width) of the final clip. clips A list of videoclips. Each clip of the list will be displayed below the clips appearing after it in the list. For each clip: - The attribute ``pos`` determines where the clip is placed. See ``VideoClip.set_pos`` - The mask of the clip determines which parts are visible. Finally, if all the clips in the list have their ``duration`` attribute set, then the duration of the composite video clip is computed automatically bg_color Color for the unmasked and unfilled regions. Set to None for these regions to be transparent (will be slower). use_bgclip Set to True if the first clip in the list should be used as the 'background' on which all other clips are blitted. That first clip must have the same size as the final clip. If it has no transparency, the final clip will have no mask. The clip with the highest FPS will be the FPS of the composite clip. """ def __init__(self, clips, size=None, bg_color=None, use_bgclip=False, ismask=False): if size is None: size = clips[0].size if use_bgclip and (clips[0].mask is None): transparent = False else: transparent = (bg_color is None) if bg_color is None: bg_color = 0.0 if ismask else (0, 0, 0) fpss = [c.fps for c in clips if getattr(c, 'fps', None)] self.fps = max(fpss) if fpss else None VideoClip.__init__(self) self.size = size self.ismask = ismask self.clips = clips self.bg_color = bg_color if use_bgclip: = clips[0] self.clips = clips[1:] self.created_bg = False else: self.clips = clips = ColorClip(size, color=self.bg_color) self.created_bg = True # compute duration ends = [c.end for c in self.clips] if None not in ends: duration = max(ends) self.duration = duration self.end = duration # compute audio audioclips = [ for v in self.clips if is not None] if audioclips: = CompositeAudioClip(audioclips) # compute mask if necessary if transparent: maskclips = [(c.mask if (c.mask is not None) else c.add_mask().mask).set_position(c.pos) .set_end(c.end).set_start(c.start, change_end=False) for c in self.clips] self.mask = CompositeVideoClip(maskclips,self.size, ismask=True, bg_color=0.0) def make_frame(t): """ The clips playing at time `t` are blitted over one another. """ f = for c in self.playing_clips(t): f = c.blit_on(f, t) return f self.make_frame = make_frame
[docs] def playing_clips(self, t=0): """ Returns a list of the clips in the composite clips that are actually playing at the given time `t`. """ return [c for c in self.clips if c.is_playing(t)]
[docs] def close(self): if self.created_bg and # Only close the background clip if it was locally created. # Otherwise, it remains the job of whoever created it. = None if hasattr(self, "audio") and = None
def clips_array(array, rows_widths=None, cols_widths=None, bg_color = None): """ rows_widths widths of the different rows in pixels. If None, is set automatically. cols_widths widths of the different colums in pixels. If None, is set automatically. cols_widths bg_color Fill color for the masked and unfilled regions. Set to None for these regions to be transparent (will be slower). """ array = np.array(array) sizes_array = np.array([[c.size for c in line] for line in array]) # find row width and col_widths automatically if not provided if rows_widths is None: rows_widths = sizes_array[:,:,1].max(axis=1) if cols_widths is None: cols_widths = sizes_array[:,:,0].max(axis=0) xx = np.cumsum([0]+list(cols_widths)) yy = np.cumsum([0]+list(rows_widths)) for j, (x, cw) in enumerate(zip(xx[:-1], cols_widths)): for i, (y, rw) in enumerate(zip(yy[:-1], rows_widths)): clip = array[i, j] w, h = clip.size if (w < cw) or (h < rw): clip = (CompositeVideoClip([clip.set_position('center')], size = (cw,rw), bg_color = bg_color). set_duration(clip.duration)) array[i, j] = clip.set_position((x, y)) return CompositeVideoClip(array.flatten(), size=(xx[-1], yy[-1]), bg_color=bg_color)