99 lines
3.1 KiB
Python
99 lines
3.1 KiB
Python
import sys
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from math import sqrt
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import numpy
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from numpy.linalg import norm
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class FrameInterval:
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def __init__(self, start_frame, end_frame):
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self.start_frame = int(start_frame)
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self.end_frame = int(end_frame)
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def overlaps(self, other : 'FrameInterval') -> bool:
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return self.start_frame <= other.start_frame <= self.end_frame or \
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other.start_frame <= self.start_frame <= other.end_frame
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def compute_relative_vector(camera: bpy.types.Camera, target: bpy.types.Object):
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"""
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Return a vector from `camera` to `target` in the camera's coordinate space.
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The camera's lens is assumed to be norm to the ZX plane.
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"""
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cam_loc, cam_rot, _ = camera.matrix_world.decompose()
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target_loc, _, _ = target.matrix_world.decompose()
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relative_vector = target_loc - cam_loc
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rotation = cam_rot.to_matrix().transposed()
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relative_vector.rotate(rotation)
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# The camera's worldvector is norm to the horizon, we want a vector
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# down the barrel.
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camera_correction = Quaternion( ( sqrt(2.) / 2. , sqrt(2.) / 2. , 0. , 0.) )
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relative_vector.rotate(camera_correction)
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return relative_vector
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def room_norm_vector(vec, room_size=1.) -> Vector:
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"""
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The Room is tearing me apart, Lisa.
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The room is a cube with the camera at its center. We use a chebyshev normalization
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to convert a vector in world or camera space into a vector the represents the projection
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of that vector onto the room's walls.
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The Pro Tools/Dolby Atmos workflow I am targeting uses "Room Centric" panner coordinates
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("cartesian allocentric coordinates" in ADM speak) and this process seems to yield good
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results.
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"""
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chebyshev = norm(vec, ord=numpy.inf)
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if chebyshev < room_size:
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return vec / room_size
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else:
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return vec / chebyshev
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def closest_approach_to_camera(scene, speaker_object) -> (float, int):
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max_dist = sys.float_info.max
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at_time = scene.frame_start
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for frame in range(scene.frame_start, scene.frame_end + 1):
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scene.frame_set(frame)
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rel = speaker_object.matrix_world.to_translation() - scene.camera.matrix_world.to_translation()
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dist = norm(rel)
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if dist < max_dist:
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max_dist = dist
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at_time = frame
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return (max_dist, at_time)
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def speaker_active_time_range(speaker) -> FrameInterval:
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"""
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The time range this speaker must control in order to sound right.
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At this time this is assuming the str
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"""
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start, end = 0xffffffff, -0xffffffff
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for track in speaker.animation_data.nla_tracks:
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for strip in track.strips:
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if strip.frame_start < start:
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start = strip.frame_start
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if strip.frame_end > end:
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end = strip.frame_end
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return FrameInterval(start_frame=start, end_frame=end)
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def speakers_by_min_distance(scene, speakers):
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def min_distance(speaker):
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return closest_approach_to_camera(scene, speaker)[0]
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return sorted(speakers, key=(lambda spk: min_distance(spk)))
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def speakers_by_start_time(speaker_objs):
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return sorted(speaker_objs, key=(lambda spk: speaker_active_time_range(spk).start_frame)) |