FBX IO: Speed up animation import using NumPy #104856
@ -524,6 +524,593 @@ def blen_read_object_transform_preprocess(fbx_props, fbx_obj, rot_alt_mat, use_p
|
|||||||
|
|
||||||
# ---------
|
# ---------
|
||||||
# Animation
|
# Animation
|
||||||
|
def _transformation_curves_gen(item, values_arrays, channel_keys):
|
||||||
|
from operator import setitem
|
||||||
|
from functools import partial
|
||||||
|
if item.is_bone:
|
||||||
|
bl_obj = item.bl_obj.pose.bones[item.bl_bone]
|
||||||
|
else:
|
||||||
|
bl_obj = item.bl_obj
|
||||||
|
|
||||||
|
rot_mode = bl_obj.rotation_mode
|
||||||
|
transform_data = item.fbx_transform_data
|
||||||
|
rot_eul_prev = bl_obj.rotation_euler.copy()
|
||||||
|
rot_quat_prev = bl_obj.rotation_quaternion.copy()
|
||||||
|
|
||||||
|
# Pre-compute inverted local rest matrix of the bone, if relevant.
|
||||||
|
restmat_inv = item.get_bind_matrix().inverted_safe() if item.is_bone else None
|
||||||
|
|
||||||
|
transform_prop_to_attr = {
|
||||||
|
b'Lcl Translation': transform_data.loc,
|
||||||
|
b'Lcl Rotation': transform_data.rot,
|
||||||
|
b'Lcl Scaling': transform_data.sca,
|
||||||
|
}
|
||||||
|
|
||||||
|
# Pre-get/calculate these to reduce the work done inside the hot loop.
|
||||||
|
anim_compensation_matrix = item.anim_compensation_matrix
|
||||||
|
do_anim_compensation_matrix = bool(anim_compensation_matrix)
|
||||||
|
|
||||||
|
pre_matrix = item.pre_matrix
|
||||||
|
do_pre_matrix = bool(pre_matrix)
|
||||||
|
|
||||||
|
post_matrix = item.post_matrix
|
||||||
|
do_post_matrix = bool(post_matrix)
|
||||||
|
|
||||||
|
do_restmat_inv = bool(restmat_inv)
|
||||||
|
|
||||||
|
|||||||
|
# Create a setter into transform_data for each values array. e.g. a values array for 'Lcl Scaling' with channel == 2
|
||||||
|
# would set transform_data.sca[2].
|
||||||
|
# TODO: Might be faster to create a list of each transform_prop_to_attr[fbx_prop] and a list of channels, then zip
|
||||||
|
# both and in the main loop, do transform_data_attr[channel] = value
|
||||||
|
setters = [partial(setitem, transform_prop_to_attr[fbx_prop], channel) for fbx_prop, channel in channel_keys]
|
||||||
|
zipped_values_iterators = zip(*(iter(arr.data) for arr in values_arrays))
|
||||||
|
|
||||||
|
# todo: Rather than having to get the Matrix/Quaternion methods upon each call within the loop, we can instead get
|
||||||
|
# them in advance.
|
||||||
|
# Before the loop:
|
||||||
|
# `mat_decompose = Matrix.decompose`
|
||||||
|
# then within the loop:
|
||||||
|
# `mat_decompose(mat)`
|
||||||
|
|
||||||
|
for values in zipped_values_iterators:
|
||||||
|
for setter, value in zip(setters, values):
|
||||||
|
setter(value)
|
||||||
|
|
||||||
|
mat, _, _ = blen_read_object_transform_do(transform_data)
|
||||||
|
|
||||||
|
# compensate for changes in the local matrix during processing
|
||||||
|
if do_anim_compensation_matrix:
|
||||||
|
mat = mat @ anim_compensation_matrix
|
||||||
|
|
||||||
|
# apply pre- and post matrix
|
||||||
|
# post-matrix will contain any correction for lights, camera and bone orientation
|
||||||
|
# pre-matrix will contain any correction for a parent's correction matrix or the global matrix
|
||||||
|
if do_pre_matrix:
|
||||||
|
mat = pre_matrix @ mat
|
||||||
|
if do_post_matrix:
|
||||||
|
mat = mat @ post_matrix
|
||||||
|
|
||||||
|
# And now, remove that rest pose matrix from current mat (also in parent space).
|
||||||
|
if do_restmat_inv:
|
||||||
|
mat = restmat_inv @ mat
|
||||||
|
|
||||||
|
# Now we have a virtual matrix of transform from AnimCurves, we can insert keyframes!
|
||||||
|
loc, rot, sca = mat.decompose()
|
||||||
|
if rot_mode == 'QUATERNION':
|
||||||
|
if rot_quat_prev.dot(rot) < 0.0:
|
||||||
|
rot = -rot
|
||||||
|
rot_quat_prev = rot
|
||||||
|
elif rot_mode == 'AXIS_ANGLE':
|
||||||
|
vec, ang = rot.to_axis_angle()
|
||||||
|
rot = ang, vec.x, vec.y, vec.z
|
||||||
|
else: # Euler
|
||||||
|
rot = rot.to_euler(rot_mode, rot_eul_prev)
|
||||||
|
rot_eul_prev = rot
|
||||||
|
|
||||||
|
# Yield order matches the order that the location/rotation/scale FCurves are created in.
|
||||||
|
yield from loc
|
||||||
|
yield from rot
|
||||||
|
yield from sca
|
||||||
|
|
||||||
|
|
||||||
|
def _combine_same_property_curves(times_and_values_tuples):
|
||||||
|
"""Combine multiple sorted animation curves, that affect the same property, into a single sorted animation curve."""
|
||||||
|
if len(times_and_values_tuples) > 1:
|
||||||
|
# TODO: Print a warning to the console that more than one curve was found
|
||||||
|
# The FBX animation system's default implementation only uses the first curve assigned to a channel.
|
||||||
|
# Additional curves per channel are allowed by the FBX specification, but the handling of these curves is
|
||||||
|
# considered the responsibility of the application that created them. Note that each curve node is expected to
|
||||||
|
# have a unique set of channels, so these additional curves with the same channel would have to belong to
|
||||||
|
# separate curve nodes. See the FBX SDK documentation for FbxAnimCurveNode.
|
||||||
|
|
||||||
|
# Concatenate all the times into one array and all the values into one array.
|
||||||
|
all_times = np.concatenate([t[0] for t in times_and_values_tuples])
|
||||||
|
all_values = np.concatenate([t[1] for t in times_and_values_tuples])
|
||||||
|
# Get the unique, sorted times and the index in all_times of the first occurrence of each unique value.
|
||||||
|
sorted_unique_times, unique_indices_in_all_times = np.unique(all_times, return_index=True)
|
||||||
|
|
||||||
|
values_of_sorted_unique_times = all_values[unique_indices_in_all_times]
|
||||||
|
return sorted_unique_times, values_of_sorted_unique_times
|
||||||
|
|
||||||
|
# # Get the indices that would sort all_times.
|
||||||
|
# # Use a stable algorithm so that if there are any duplicate times, they maintain their original order.
|
||||||
|
# perm = np.argsort(kind='stable')
|
||||||
|
# # Use the indices to sort both all_times and all_values.
|
||||||
|
# all_times = all_times[perm]
|
||||||
|
# all_values = all_values[perm]
|
||||||
|
else:
|
||||||
|
return times_and_values_tuples[0]
|
||||||
|
|
||||||
|
|
||||||
|
def _combine_curve_keyframes(times_and_values_tuples, initial_values):
|
||||||
|
"""Combine multiple sorted animation curves, that affect different properties, such that every animation curve
|
||||||
|
contains the keyframes from every other curve, interpolating the values for the newly inserted keyframes in each
|
||||||
|
curve.
|
||||||
|
|
||||||
|
Currently, linear interpolation is assumed, but FBX does store how keyframes should be interpolated, so correctly
|
||||||
|
interpolating the keyframe values is a TODO."""
|
||||||
|
# all_times = []
|
||||||
|
# #all_values = []
|
||||||
|
# #all_curve_idx = []
|
||||||
|
# for i, (times, values) in enumerate(times_and_values_tuples):
|
||||||
|
# all_times.append(times)
|
||||||
|
# #all_values.append(values)
|
||||||
|
# #all_curve_idx.append(np.full_like(times, i))
|
||||||
|
# all_times = np.concatenate(all_times)
|
||||||
|
# #all_curve_idx = np.concatenate(all_curve_idx)
|
||||||
|
# perm = np.argsort(all_times, kind='stable')
|
||||||
|
#
|
||||||
|
# sorted_all_times = all_times[perm]
|
||||||
|
#
|
||||||
|
# # Get the index in sorted_all_times of each time in all_times
|
||||||
|
# all_times_indices = np.empty(len(perm), dtype=np.intp)
|
||||||
|
# all_times_indices[perm] = np.arange(len(perm))
|
||||||
|
|
||||||
|
all_times = [t[0] for t in times_and_values_tuples]
|
||||||
|
|
||||||
|
# Get sorted unique times and the index in sorted_all_times of each time in all_times
|
||||||
|
sorted_all_times, all_times_indices = np.unique(np.concatenate(all_times), return_inverse=True)
|
||||||
|
|
||||||
|
#sorted_all_values = all_values[perm]
|
||||||
|
#sorted_curve_idx = all_curve_idx[perm]
|
||||||
|
# An alternative would be to concatenated filled arrays with the index of each array and then index that by perm,
|
||||||
|
# then a mask for each array can be found by checking for values that equal the index of that array.
|
||||||
|
values_arrays = []
|
||||||
|
times_start = 0
|
||||||
|
for (times, values), initial_value in zip(times_and_values_tuples, initial_values):
|
||||||
|
times_end = times_start + len(times)
|
||||||
|
# The index in sorted_all_times of each value in times
|
||||||
|
times_indices = all_times_indices[times_start:times_end]
|
||||||
|
# Update times_start for the next array
|
||||||
|
times_start = times_end
|
||||||
|
|
||||||
|
# todo: Not sure the best way to mask out the values here, will need investigating
|
||||||
|
|
||||||
|
#times_extended = sorted_all_times.copy()
|
||||||
|
|
||||||
|
needs_interpolation_mask = np.full(len(sorted_all_times), True)
|
||||||
|
needs_interpolation_mask[times_indices] = False
|
||||||
|
#imported_times_mask = ~needs_interpolation_mask
|
||||||
|
|
||||||
|
# # Need to find the before and after times for each time that needs interpolation
|
||||||
|
# # Times are sorted, so the smallest and largest are simply the first and last values.
|
||||||
|
# min_time_value = values[0]
|
||||||
|
# max_time_value = values[-1]
|
||||||
|
|
||||||
|
# todo: It's possible we can get the same result faster by doing the interpolation manually, since we can figure
|
||||||
|
# out the before and after values for each time that needs interpolating (this would also likely make it easier
|
||||||
|
# to update the function to support other interpolation than just linear).
|
||||||
|
interp_values = np.interp(sorted_all_times[needs_interpolation_mask], times, values, left=initial_value)
|
||||||
|
|
||||||
|
# Alt, though we typically expect there to be few times that need interpolation:
|
||||||
|
# extended_values = np.interp(sorted_all_times, times, values, left=initial_value)
|
||||||
|
|
||||||
|
extended_values = np.empty_like(values, shape=len(sorted_all_times))
|
||||||
|
extended_values[needs_interpolation_mask] = interp_values
|
||||||
|
extended_values[times_indices] = values
|
||||||
|
|
||||||
|
values_arrays.append(extended_values)
|
||||||
|
|
||||||
|
# FIXME: If we have two curves with the same times, aren't they going to break because they're going to try and
|
||||||
|
# interpolate the same times?
|
||||||
|
# times1 = [1,2,3,4]
|
||||||
|
# times2 = [1,2,3,4]
|
||||||
|
# sorted_all_times = [1,1,2,2,3,3,4,4]... not good
|
||||||
|
|
||||||
|
# # Manual linear interpolation (it may be easier to extend for other interpolation):
|
||||||
|
# # Get the index of the previous and next elements that are not interpolated
|
||||||
|
# prev_value_indices = np.arange(len(sorted_all_times), dtype=np.intp)
|
||||||
|
# next_value_indices = prev_value_indices.copy()
|
||||||
|
# prev_value_indices[needs_interpolation_mask] = times_indices[0]
|
||||||
|
# next_value_indices[needs_interpolation_mask] = times_indices[-1]
|
||||||
|
# prev_value_indices = np.maximum.accumulate(prev_value_indices)
|
||||||
|
# next_value_indices = np.flip(np.minimum.accumulate(np.flip(next_value_indices)))
|
||||||
|
#
|
||||||
|
# # TODO: May be faster to simply not index by needs_interpolation_mask every time and then only index by
|
||||||
|
# # needs_interpolation_mask at the end.
|
||||||
|
# prev_times = sorted_all_times[prev_value_indices][needs_interpolation_mask]
|
||||||
|
# prev_values = sorted_all_values[prev_value_indices][needs_interpolation_mask]
|
||||||
|
# next_times = sorted_all_times[next_value_indices][needs_interpolation_mask]
|
||||||
|
# next_values = sorted_all_values[next_value_indices][needs_interpolation_mask]
|
||||||
|
#
|
||||||
|
# interp_times = sorted_all_times[needs_interpolation_mask]
|
||||||
|
# ifac = (interp_times - prev_times) / (next_times - prev_times)
|
||||||
|
# interp_values = ifac * (next_values - prev_values) + prev_values
|
||||||
|
|
||||||
|
# ifac = (sorted_all_times[needs_interpolation_mask] - prev_times) / ()
|
||||||
|
#
|
||||||
|
# values_extended =
|
||||||
|
#
|
||||||
|
# min_before = np.full_like(sorted_all_times, times[0])
|
||||||
|
# max_after = np.full_like(sorted_all_times, times[-1])
|
||||||
|
#
|
||||||
|
# # FIXME: But we need the indices so we can get the before and after values and interpolate between those...
|
||||||
|
# before_times = times_extended.copy()
|
||||||
|
# before_times[needs_interpolation_mask] = min_time
|
||||||
|
# before_times = np.maximum.accumulate(before_times)
|
||||||
|
#
|
||||||
|
# after_times = times_extended.copy()
|
||||||
|
# after_times[needs_interpolation_mask] = max_time
|
||||||
|
# after_times = np.flip(np.minimum.accumulate(np.flip(after_times)))
|
||||||
|
#
|
||||||
|
# before_times[needs_interpolation_mask]
|
||||||
|
#
|
||||||
|
#
|
||||||
|
#
|
||||||
|
#
|
||||||
|
# times_full = sorted_all_times.copy()
|
||||||
|
# values_full = np.full_like(sorted_all_times, np.nan)
|
||||||
|
# values_full[sorted_curve_idx == i] = values
|
||||||
|
return sorted_all_times, values_arrays
|
||||||
|
|
||||||
|
|
||||||
|
def blen_read_invalid_animation_curve(key_times, key_values):
|
||||||
|
"""FBX will parse animation curves even when their keyframe times are invalid (not strictly increasing). It's
|
||||||
|
unclear exactly how FBX handles invalid curves, but this matches in some cases and is how the FBX IO addon has been
|
||||||
|
handling invalid keyframe times for a long time.
|
||||||
|
|
||||||
|
Notably, this function will also correctly parse valid animation curves, though is much slower than the trivial,
|
||||||
|
regular way.
|
||||||
|
|
||||||
|
The returned keyframe times are guaranteed to be strictly increasing."""
|
||||||
|
sorted_unique_times = np.unique(key_times)
|
||||||
|
|
||||||
|
# Unsure if this can be vectorized with numpy, so using iteration for now.
|
||||||
|
def index_gen():
|
||||||
|
idx = 0
|
||||||
|
key_times_len = len(key_times)
|
||||||
|
# Iterating .data, the memoryview of the array, is faster than iterating the array directly.
|
||||||
|
for curr_fbxktime in sorted_unique_times.data:
|
||||||
|
if key_times[idx] < curr_fbxktime:
|
||||||
|
if idx >= 0:
|
||||||
|
idx += 1
|
||||||
|
if idx >= key_times_len:
|
||||||
|
idx = -1
|
||||||
|
yield idx
|
||||||
|
|
||||||
|
indices = np.fromiter(index_gen(), dtype=np.int64, count=len(sorted_unique_times))
|
||||||
|
indexed_times = key_times[indices]
|
||||||
|
indexed_values = key_values[indices]
|
||||||
|
|
||||||
|
# Interpolate the value for each time in sorted_unique_times according to the times and values at each index and
|
||||||
|
# the previous index.
|
||||||
|
interpolated_values = np.empty_like(indexed_values)
|
||||||
|
|
||||||
|
# Where the index is 0, there's no previous value to interpolate from, so we set the value without
|
||||||
|
# interpolating.
|
||||||
|
# Because the indices are in increasing order, all zeroes must be at the start, so we can find the index of the
|
||||||
|
# last zero and use that to index with a slice instead of a boolean array for performance.
|
||||||
|
# Equivalent to, but as a slice:
|
||||||
|
# idx_zero_mask = indices == 0
|
||||||
|
# idx_nonzero_mask = ~idx_zero_mask
|
||||||
|
first_nonzero_idx = np.searchsorted(indices, 0, side='right')
|
||||||
|
idx_zero_slice = slice(0, first_nonzero_idx) # [:first_nonzero_idx]
|
||||||
|
idx_nonzero_slice = slice(first_nonzero_idx, None) # [first_nonzero_idx:]
|
||||||
|
|
||||||
|
interpolated_values[idx_zero_slice] = indexed_values[idx_zero_slice]
|
||||||
|
|
||||||
|
indexed_times_nonzero_idx = indexed_times[idx_nonzero_slice]
|
||||||
|
indexed_values_nonzero_idx = indexed_values[idx_nonzero_slice]
|
||||||
|
indices_nonzero = indices[idx_nonzero_slice]
|
||||||
|
|
||||||
|
prev_indices_nonzero = indices_nonzero - 1
|
||||||
|
prev_indexed_times_nonzero_idx = key_times[prev_indices_nonzero]
|
||||||
|
prev_indexed_values_nonzero_idx = key_values[prev_indices_nonzero]
|
||||||
|
|
||||||
|
ifac_a = sorted_unique_times[idx_nonzero_slice] - prev_indexed_times_nonzero_idx
|
||||||
|
ifac_b = indexed_times_nonzero_idx - prev_indexed_times_nonzero_idx
|
||||||
|
# If key_times contains two (or more) duplicate times in a row, then values in `ifac_b` can be zero which would
|
||||||
|
# result in division by zero.
|
||||||
|
# Use the `np.errstate` context manager to suppress printing the RuntimeWarning to the system console.
|
||||||
|
with np.errstate(divide='ignore'):
|
||||||
|
ifac = ifac_a / ifac_b
|
||||||
|
interpolated_values[idx_nonzero_slice] = ((indexed_values_nonzero_idx - prev_indexed_values_nonzero_idx) * ifac
|
||||||
|
+ prev_indexed_values_nonzero_idx)
|
||||||
|
|
||||||
|
# If the time to interpolate at is larger than the time in indexed_times, then the value has been extrapolated.
|
||||||
|
# Extrapolated values are excluded.
|
||||||
|
valid_mask = indexed_times >= sorted_unique_times
|
||||||
|
|
||||||
|
key_times = sorted_unique_times[valid_mask]
|
||||||
|
key_values = interpolated_values[valid_mask]
|
||||||
|
|
||||||
|
return key_times, key_values
|
||||||
|
|
||||||
|
|
||||||
|
def _convert_fbx_time_to_blender_time(key_times, blen_start_offset, fbx_start_offset, fps):
|
||||||
|
# todo: Could move this into blen_store_keyframes since it probably doesn't need to be used anywhere else
|
||||||
|
from .fbx_utils import FBX_KTIME
|
||||||
|
timefac = fps / FBX_KTIME
|
||||||
|
|
||||||
|
# Convert from FBX timing to Blender timing.
|
||||||
|
# Cannot subtract in-place because key_times could be read directly from FBX and could be used by multiple Actions.
|
||||||
|
key_times = key_times - fbx_start_offset
|
||||||
|
# timefac is a Python float, so the new array will be a np.float64 array.
|
||||||
|
key_times = key_times * timefac
|
||||||
|
|
||||||
|
key_times += blen_start_offset
|
||||||
|
|
||||||
|
return key_times
|
||||||
|
|
||||||
|
|
||||||
|
def blen_read_single_animation_curve(fbx_curve):
|
||||||
|
"""Read a single animation curve from FBX data.
|
||||||
|
|
||||||
|
The parsed keyframe times are guaranteed to be strictly increasing."""
|
||||||
|
# TODO: Remove these, we can do all time conversion at the very end, just before combining times and values into a
|
||||||
|
# single array
|
||||||
|
# from .fbx_utils import FBX_KTIME
|
||||||
|
# timefac = fps / FBX_KTIME
|
||||||
|
|
||||||
|
key_times = parray_as_ndarray(elem_prop_first(elem_find_first(fbx_curve, b'KeyTime')))
|
||||||
|
key_values = parray_as_ndarray(elem_prop_first(elem_find_first(fbx_curve, b'KeyValueFloat')))
|
||||||
|
|
||||||
|
assert(len(key_values) == len(key_times))
|
||||||
|
|
||||||
|
# The FBX SDK specifies that only one key per time is allowed and that the keys are sorted in time order.
|
||||||
|
# https://help.autodesk.com/view/FBX/2020/ENU/?guid=FBX_Developer_Help_cpp_ref_class_fbx_anim_curve_html
|
||||||
|
all_times_strictly_increasing = (key_times[1:] > key_times[:-1]).all()
|
||||||
|
|
||||||
|
if all_times_strictly_increasing:
|
||||||
|
return key_times, key_values
|
||||||
|
else:
|
||||||
|
# todo: Print something to the console warning that the animation curve was invalid.
|
||||||
|
|
||||||
|
# FBX will still read animation curves even if they are invalid.
|
||||||
|
return blen_read_invalid_animation_curve(key_times, key_values)
|
||||||
|
|
||||||
|
# todo When we have transformation curves (or more than one curve per channel (optional support)) separately combine
|
||||||
|
# singular parsed curves and fill in the gaps with linear interpolation. .concatenate and .unique the key_times
|
||||||
|
# arrays with return_inverse=True. Use the lengths of each key_times array and their order in the concatenation to
|
||||||
|
# get the index of each of their elements in the sorted, unique concatenation.
|
||||||
|
# For each key_times array, create an all True array and use those indices to set values to False.
|
||||||
|
# Copy the sorted, unique concatenation and use this new mask to effectively delete all times that didn't come from
|
||||||
|
# this key_times array. Use .maximum.accumulate and a reversed .minimum.accumulate to get the first time before and
|
||||||
|
# first time after each time that needs its value to be interpolated. These two arrays get the start and end times
|
||||||
|
# to interpolate from. For each time that needs its value to be interpolated, get the values for the start and end
|
||||||
|
# times and then use those and the times that needs their values interpolated to calculate the interpolated values.
|
||||||
|
# Care will need to be taken for times where there is no first value before or where there is no first value after,
|
||||||
|
# in which case interpolation can't take place and we'll either need to start set values at the very start and end
|
||||||
|
# or otherwise fill the values that can't be interpolated with a default value or the first/last value in
|
||||||
|
# key_times.
|
||||||
|
|
||||||
|
if not all_times_strictly_increasing:
|
||||||
|
# We try to match how FBX behaves when it encounters an invalid KeyTime array. This doesn't quite match when the
|
||||||
|
# maximum value is not the last value (FBX discards some keyframes whereas we don't), but it's close enough.
|
||||||
|
|
||||||
|
# Start the curve from the index of the smallest KeyTime value.
|
||||||
|
min_idx = np.amin(key_times) if key_times.size else 0
|
||||||
|
key_times = key_times[min_idx:]
|
||||||
|
key_values = key_values[min_idx:]
|
||||||
|
|
||||||
|
max_idx = np.amax(key_times) if key_times.size else 0
|
||||||
|
# If the largest KeyTime value is at the last index then it's simple.
|
||||||
|
if max_idx == key_times.size - 1:
|
||||||
|
# Set each element to the maximum of itself and all elements before it
|
||||||
|
key_times = np.maximum.accumulate(key_times)
|
||||||
|
else:
|
||||||
|
# This works the same as Blender's original animation curve parser, without the conversion from FBX time to
|
||||||
|
# Blender time and modified to operate on a single curve rather than multiple
|
||||||
|
|
||||||
|
# todo: Maybe these should be sorted instead?
|
||||||
|
# todo: Maybe these should be np.maximum.accumulate-d instead?
|
||||||
|
# Sorted unique key times
|
||||||
|
sorted_unique_times = np.unique(key_times)
|
||||||
|
|
||||||
|
# TODO: How is this different from np.searchsorted on np.maximum.acccumulate-d times? Can we use it to find
|
||||||
|
# the points at which idx will increase and then np.cumsum those increases?
|
||||||
|
def parse_invalid_curve_times_to_indices():
|
||||||
|
idx = 0
|
||||||
|
times = key_times.data
|
||||||
|
num_times = len(times)
|
||||||
|
|
||||||
|
for curr_fbxktime in sorted_unique_times.data:
|
||||||
|
curr_time = times[idx]
|
||||||
|
if curr_time < curr_fbxktime:
|
||||||
|
if idx >= 0:
|
||||||
|
idx += 1
|
||||||
|
if idx >= num_times:
|
||||||
|
# We have reached our last element for this curve, stay on it from now on...
|
||||||
|
idx = -1
|
||||||
|
yield idx
|
||||||
|
|
||||||
|
key_time_indices = np.fromiter(parse_invalid_curve_times_to_indices(), dtype=np.int64)
|
||||||
|
key_times = key_times[key_time_indices]
|
||||||
|
key_values = key_values[key_values]
|
||||||
|
|
||||||
|
# Filter out invalid times
|
||||||
|
valid_mask = key_times >= sorted_unique_times
|
||||||
|
key_times = key_times[valid_mask]
|
||||||
|
key_values = key_values[valid_mask]
|
||||||
|
|
||||||
|
interpolated_values = np.empty_like(key_values)
|
||||||
|
interpolated_values[:1] = key_values[:1]
|
||||||
|
ifac = (sorted_unique_times[1:] - key_times[:-1]) / (key_values[1:] - key_times[:-1])
|
||||||
|
interpolated_values[1:] = (key_values[1:] - key_values[:-1]) * ifac + key_values[:-1]
|
||||||
|
key_values = interpolated_values
|
||||||
|
|
||||||
|
# def parse_curve_fallback_gen():
|
||||||
|
# idx = 0
|
||||||
|
# times = key_times.data
|
||||||
|
# num_times = len(times)
|
||||||
|
# values = key_values.data
|
||||||
|
# # Sorted unique times
|
||||||
|
# sorted_unique_times = np.unique(key_times)
|
||||||
|
# for curr_fbxktime in sorted_unique_times.data:
|
||||||
|
# curr_time = times[idx]
|
||||||
|
# if curr_time < curr_fbxktime:
|
||||||
|
# if idx >= 0:
|
||||||
|
# idx += 1
|
||||||
|
# if idx >= num_times:
|
||||||
|
# # We have reached our last element for this curve, stay on it from now on...
|
||||||
|
# idx = -1
|
||||||
|
# curr_time = times[idx]
|
||||||
|
# if curr_time >= curr_fbxktime:
|
||||||
|
# if idx == 0:
|
||||||
|
# curr_value = values[idx]
|
||||||
|
# else:
|
||||||
|
# # Interpolate between this key and the previous one
|
||||||
|
# prev_time = times[idx - 1]
|
||||||
|
# ifac = (curr_fbxktime - prev_time) / (curr_time - prev_time)
|
||||||
|
# prev_value =
|
||||||
|
# curr_value = (values[idx] - values[idx - 1]) * ifac + values[idx - 1]
|
||||||
|
# yield curr_fbxktime, curr_value
|
||||||
|
# structured_dtype = np.dtype([("time", key_times.dtype), ("value", key_values.dtype)])
|
||||||
|
# times_and_values = np.fromiter(parse_curve_fallback_gen(), dtype=structured_dtype)
|
||||||
|
# key_times = times_and_values["time"]
|
||||||
|
# key_values = times_and_values["values"]
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
# # todo: Get some printable attribute from fbx_curve, don't print the entire fbx_curve
|
||||||
|
# print("WARNING: Invalid animation keyframe times for %s. The key frame times that are not strictly increasing"
|
||||||
|
# " and the keyframes before the first keyframe chronologically have been discarded." % str(fbx_curve))
|
||||||
|
# # We could sort the key times, but starting from the minimum value and then taking an accumulative maximum
|
||||||
|
# # better matches FBX and older Blender behaviour when the times are not in order.
|
||||||
|
# # FIXME: min_idx thing doesn't work, things get weird when the start and end aren't the min and max times...
|
||||||
|
# min_idx = np.amin(key_times) if key_times.size else 0
|
||||||
|
# """
|
||||||
|
# Ok, so moving the max_idx to not be last has odd effects...
|
||||||
|
# Given frames [0, 10, ..., 90, 100] and values [0, ..., 100]. Moving the last time into the:
|
||||||
|
# second-last position: Frames -> [0, ..., 90], values -> [0, ..., 80, 85] (not 90??)
|
||||||
|
# [..., 80, _90_, (100)]
|
||||||
|
# Perhaps [..., 80, ????, (90)]
|
||||||
|
# Interp [..., 80, 85, (90)]
|
||||||
|
# Frames [..., 80, 90, (100)]
|
||||||
|
# Blender appears to agree with Unity in this case, but Blender doesn't exclude the (<value>) element
|
||||||
|
# whereas Unity does.
|
||||||
|
# Interp [..., 80, 85, 90]
|
||||||
|
# Frames [..., 80, 90, 100]
|
||||||
|
# third-last position: Frames -> [0, ..., 70, 90], values -> [0, ..., 70, 76.6666] (not 80??)
|
||||||
|
# [..., 70, _80_, (90), (100)]
|
||||||
|
# Perhaps [..., 70, ????, ????, (90)]
|
||||||
|
# Interp [..., 70, 76.6, 83.3, (90)]
|
||||||
|
# Frames [..., 70, (80), 90, (100)]
|
||||||
|
#
|
||||||
|
# Blender sets frame 100 to 80 instead, which would have been the next value after 70, but Blender
|
||||||
|
# doesn't exclude the (<value>) elements whereas Unity does.
|
||||||
|
# Perhaps [..., 70, (??), ????, (80)]
|
||||||
|
# Interp [..., 70,(73.3),76.6, (80)]
|
||||||
|
# Frames [..., 70, 80, 90, 100]
|
||||||
|
# fourth-last position: Frames -> [0, ..., 60, 90], values -> [0, ..., 60, 67.5]
|
||||||
|
# [..., 60, _70_, (80), (90), (100)]
|
||||||
|
# Perhaps [..., 60, ????, ????, ????, (90)]
|
||||||
|
# Interp [..., 60, 67.5, 75, 82.5, (90)]
|
||||||
|
# Frames [..., 60, (70), (80), 90, (100)]
|
||||||
|
#
|
||||||
|
# Blender sets frame 100 to 70 instead, which would have been the next value after 60, but Blender
|
||||||
|
# doesn't exclude the (<value>) elements whereas Unity does.
|
||||||
|
# Perhaps [..., 60, (??), (??), ????, (70)]
|
||||||
|
# Interp [..., 60,(62.5),(65), 67.5, (70)]
|
||||||
|
# Frames [..., 60, 70, 80, 90, 100]
|
||||||
|
# TODO: Try changing the 90 value to something else and see if the interpolations still hold.
|
||||||
|
# """
|
||||||
|
# max_idx = np.amax(key_times) if key_times.size else 0 # max idx might also get reduced by min_idx?
|
||||||
|
# last_idx = len(key_times) - 1
|
||||||
|
# if max_idx != last_idx:
|
||||||
|
# max_idx = last_idx - 2 # Seems to exclude the last two keyframes for some reason...
|
||||||
|
# key_times = key_times[min_idx:max_idx]
|
||||||
|
# key_values = key_values[min_idx:max_idx]
|
||||||
|
# key_times = np.maximum.accumulate(key_times)
|
||||||
|
# # TODO: As an alternative to finding the duplicates ourselves, we could just return key_times and key_values
|
||||||
|
# # as they are from here, letting Blender remove the duplicates when calling .update().
|
||||||
|
# # Yes, we should leave it to Blender, imagine a transform channel with values [10, 2, 5, 20] at times
|
||||||
|
# # [1, 12, 12, 40], and then another transform channel with times at [6, 30]. The first channel will need to
|
||||||
|
# # interpolate for the missing times of 6 and 30.
|
||||||
|
# unique_mask = np.empty_like(key_times, dtype=bool)
|
||||||
|
# # Remove keyframes at duplicate times. Blender would do this when calling .update() on the FCurve. Where there
|
||||||
|
# # are duplicate times, Blender only keeps the last duplicate.
|
||||||
|
# # Note that this may produce different results to software that uses the FBX SDK, because it does not remove
|
||||||
|
# # duplicates.
|
||||||
|
# # Because key_times is now in ascending order, unique elements are the last element and elements that are
|
||||||
|
# # pairwise not equal.
|
||||||
|
# # 1,1,1,2,3,3,4,5,5
|
||||||
|
# # F,F,T,T,F,T,T,F
|
||||||
|
# np.not_equal(key_times[:-1], key_times[1:], out=unique_mask[:-1])
|
||||||
|
# # The last element is always kept:
|
||||||
|
# # F,F,T,T,F,T,T,F,T
|
||||||
|
# unique_mask[-1:] = True
|
||||||
|
#
|
||||||
|
# # # FIXME: This currently gets the first unique time, but if we were to import even duplicate times, when we
|
||||||
|
# # # .update() the FCurve, Blender keeps only the *last* unique time.
|
||||||
|
# # # Remove duplicates. Because key_times is now in ascending order, unique elements are the first element and
|
||||||
|
# # # elements that are pairwise not equal.
|
||||||
|
# # # 1,1,1,2,3,3,4,5
|
||||||
|
# # # F,F,T,T,F,T,T
|
||||||
|
# # # The first element is always unique:
|
||||||
|
# # # T,F,F,T,T,F,T,T
|
||||||
|
# # unique_mask[:1] = True
|
||||||
|
# # np.not_equal(key_times[:-1], key_times[1:], out=unique_mask[1:])
|
||||||
|
# #
|
||||||
|
# # #indices = np.where(unique_mask, np.arange(len(unique_mask), 0))
|
||||||
|
# # #indices = np.maximum.accumulate(indices)
|
||||||
|
# #
|
||||||
|
# # Use the mask to get only the times (and their values) that are strictly increasing.
|
||||||
|
# key_times = key_times[unique_mask]
|
||||||
|
# key_values = key_values[unique_mask]
|
||||||
|
|
||||||
|
# Convert from FBX timing to Blender timing.
|
||||||
|
# Cannot subtract in-place because this curve could be used in multiple Actions.
|
||||||
|
key_times = key_times - fbx_start_offset
|
||||||
|
# timefac is a Python float, so the new array will be a np.float64 array.
|
||||||
|
key_times = key_times * timefac
|
||||||
|
key_times += blen_start_offset
|
||||||
|
|
||||||
|
return key_times, key_values
|
||||||
|
|
||||||
|
|
||||||
|
def blen_store_keyframes(blen_fcurve, key_times, key_values):
|
||||||
|
"""Set all keyframe times and values for a newly created FCurve.
|
||||||
|
Linear interpolation is currently assumed."""
|
||||||
|
# The fcurve must be newly created and thus have no keyframe_points.
|
||||||
|
assert(len(blen_fcurve.keyframe_points) == 0)
|
||||||
|
num_keys = len(key_times)
|
||||||
|
|
||||||
|
# Compatible with C float type
|
||||||
|
bl_keyframe_dtype = np.single
|
||||||
|
# Compatible with C char type
|
||||||
|
bl_enum_dtype = np.byte
|
||||||
|
|
||||||
|
# TODO: get this value once and store it as a global variable
|
||||||
|
linear_enum_value = bpy.types.Keyframe.bl_rna.properties['interpolation'].enum_items['LINEAR'].value
|
||||||
|
|
||||||
|
# Stack the arrays into a flattened array of flattened (frame, value) pairs
|
||||||
|
# Same as `np.column_stack(key_times, key_values).ravel()`, but allows specifying the dtype.
|
||||||
|
full_key_frame_array = np.concatenate((key_times.reshape(-1, 1), key_values.reshape(-1, 1)),
|
||||||
|
dtype=bl_keyframe_dtype, casting='unsafe', axis=1).ravel()
|
||||||
|
|
||||||
|
# Add the keyframe points to the FCurve and then set the 'co' and 'interpolation' of each point.
|
||||||
|
blen_fcurve.keyframe_points.add(num_keys)
|
||||||
|
blen_fcurve.keyframe_points.foreach_set('co', full_key_frame_array.ravel())
|
||||||
|
blen_fcurve.keyframe_points.foreach_set('interpolation', np.full(num_keys, linear_enum_value, dtype=bl_enum_dtype))
|
||||||
|
|
||||||
|
# Since we inserted our keyframes in 'ultra-fast' mode, we have to update the fcurves now.
|
||||||
|
blen_fcurve.update()
|
||||||
|
|
||||||
|
|
||||||
|
# TODO: Remove this function
|
||||||
def blen_read_animations_curves_iter(fbx_curves, blen_start_offset, fbx_start_offset, fps):
|
def blen_read_animations_curves_iter(fbx_curves, blen_start_offset, fbx_start_offset, fps):
|
||||||
"""
|
"""
|
||||||
Get raw FBX AnimCurve list, and yield values for all curves at each singular curves' keyframes,
|
Get raw FBX AnimCurve list, and yield values for all curves at each singular curves' keyframes,
|
||||||
@ -572,42 +1159,54 @@ def blen_read_animations_action_item(action, item, cnodes, fps, anim_offset, glo
|
|||||||
taking any pre_ and post_ matrix into account to transform from fbx into blender space.
|
taking any pre_ and post_ matrix into account to transform from fbx into blender space.
|
||||||
"""
|
"""
|
||||||
from bpy.types import Object, PoseBone, ShapeKey, Material, Camera
|
from bpy.types import Object, PoseBone, ShapeKey, Material, Camera
|
||||||
|
# todo: Remove this import
|
||||||
from itertools import chain
|
from itertools import chain
|
||||||
|
|
||||||
fbx_curves = []
|
fbx_curves: dict[bytes, dict[int, list[FBXElem]]] = {}
|
||||||
used_channels = set()
|
|
||||||
warn_multiple_curves_per_channel = False
|
|
||||||
for curves, fbxprop in cnodes.values():
|
for curves, fbxprop in cnodes.values():
|
||||||
|
channels_dict = fbx_curves.setdefault(fbxprop, {})
|
||||||
for (fbx_acdata, _blen_data), channel in curves.values():
|
for (fbx_acdata, _blen_data), channel in curves.values():
|
||||||
channel_id = (fbxprop, channel)
|
channels_dict.setdefault(channel, []).append(fbx_acdata)
|
||||||
if channel_id in used_channels:
|
|
||||||
# The FBX animation system's default implementation only uses the first curve assigned to a channel.
|
# fbx_curves = []
|
||||||
# Additional curves per channel are allowed by the FBX specification, but the handling of these curves
|
# used_channels = set()
|
||||||
# is considered the responsibility of the application that created them. Note that each curve node is
|
# warn_multiple_curves_per_channel = False
|
||||||
# expected to have a unique set of channels, so these additional curves with the same channel would have
|
# for curves, fbxprop in cnodes.values():
|
||||||
# to belong to separate curve nodes. See the FBX SDK documentation for FbxAnimCurveNode.
|
# channels_dict = fbx_curves_props_channels.setdefault(fbxprop, {})
|
||||||
warn_multiple_curves_per_channel = True
|
# for (fbx_acdata, _blen_data), channel in curves.values():
|
||||||
else:
|
# channels_dict.setdefault(channel, []).append(fbx_acdata)
|
||||||
used_channels.add(channel_id)
|
#
|
||||||
fbx_curves.append((fbxprop, channel, fbx_acdata))
|
# for (fbx_acdata, _blen_data), channel in curves.values():
|
||||||
if warn_multiple_curves_per_channel:
|
# channel_id = (fbxprop, channel)
|
||||||
print("WARNING: Multiple animation curves per animated property channel were found for %s. All but the first"
|
# if channel_id in used_channels:
|
||||||
"curve for each property channel has been discarded." % action.name)
|
# # The FBX animation system's default implementation only uses the first curve assigned to a channel.
|
||||||
|
# # Additional curves per channel are allowed by the FBX specification, but the handling of these curves
|
||||||
|
# # is considered the responsibility of the application that created them. Note that each curve node is
|
||||||
|
# # expected to have a unique set of channels, so these additional curves with the same channel would have
|
||||||
|
# # to belong to separate curve nodes. See the FBX SDK documentation for FbxAnimCurveNode.
|
||||||
|
# warn_multiple_curves_per_channel = True
|
||||||
|
# else:
|
||||||
|
# used_channels.add(channel_id)
|
||||||
|
# fbx_curves.append((fbxprop, channel, fbx_acdata))
|
||||||
|
# if warn_multiple_curves_per_channel:
|
||||||
|
# print("WARNING: Multiple animation curves per animated property channel were found for %s. All but the first"
|
||||||
|
# "curve for each property channel has been discarded." % action.name)
|
||||||
|
|
||||||
# Leave if no curves are attached (if a blender curve is attached to scale but without keys it defaults to 0).
|
# Leave if no curves are attached (if a blender curve is attached to scale but without keys it defaults to 0).
|
||||||
if len(fbx_curves) == 0:
|
if len(fbx_curves) == 0:
|
||||||
return
|
return
|
||||||
|
|
||||||
blen_curves = []
|
# todo: Remove these
|
||||||
props = []
|
# blen_curves = []
|
||||||
keyframes = {}
|
# props = []
|
||||||
|
# keyframes = {}
|
||||||
|
|
||||||
# Add each keyframe to the keyframe dict
|
# # Add each keyframe to the keyframe dict
|
||||||
def store_keyframe(fc, frame, value):
|
# def store_keyframe(fc, frame, value):
|
||||||
fc_key = (fc.data_path, fc.array_index)
|
# fc_key = (fc.data_path, fc.array_index)
|
||||||
if not keyframes.get(fc_key):
|
# if not keyframes.get(fc_key):
|
||||||
keyframes[fc_key] = []
|
# keyframes[fc_key] = []
|
||||||
keyframes[fc_key].extend((frame, value))
|
# keyframes[fc_key].extend((frame, value))
|
||||||
|
|
||||||
if isinstance(item, Material):
|
if isinstance(item, Material):
|
||||||
grpname = item.name
|
grpname = item.name
|
||||||
@ -642,115 +1241,105 @@ def blen_read_animations_action_item(action, item, cnodes, fps, anim_offset, glo
|
|||||||
for prop, nbr_channels, grpname in props for channel in range(nbr_channels)]
|
for prop, nbr_channels, grpname in props for channel in range(nbr_channels)]
|
||||||
|
|
||||||
if isinstance(item, Material):
|
if isinstance(item, Material):
|
||||||
for frame, values in blen_read_animations_curves_iter(fbx_curves, anim_offset, 0, fps):
|
for fbxprop, channel_to_curves in fbx_curves.items():
|
||||||
value = [0,0,0]
|
|
||||||
for v, (fbxprop, channel, _fbx_acdata) in values:
|
|
||||||
assert(fbxprop == b'DiffuseColor')
|
assert(fbxprop == b'DiffuseColor')
|
||||||
|
for channel, curves in channel_to_curves.items():
|
||||||
assert(channel in {0, 1, 2})
|
assert(channel in {0, 1, 2})
|
||||||
value[channel] = v
|
blen_curve = blen_curves[channel]
|
||||||
|
parsed_curves = tuple(map(blen_read_single_animation_curve, curves))
|
||||||
for fc, v in zip(blen_curves, value):
|
fbx_key_times, values = _combine_same_property_curves(parsed_curves)
|
||||||
store_keyframe(fc, frame, v)
|
bl_key_times = _convert_fbx_time_to_blender_time(fbx_key_times, anim_offset, 0, fps)
|
||||||
|
blen_store_keyframes(blen_curve, bl_key_times, values)
|
||||||
|
|
||||||
elif isinstance(item, ShapeKey):
|
elif isinstance(item, ShapeKey):
|
||||||
deform_values = shape_key_deforms.setdefault(item, [])
|
deform_values = shape_key_deforms.setdefault(item, [])
|
||||||
for frame, values in blen_read_animations_curves_iter(fbx_curves, anim_offset, 0, fps):
|
for fbxprop, channel_to_curves in fbx_curves.items():
|
||||||
value = 0.0
|
|
||||||
for v, (fbxprop, channel, _fbx_acdata) in values:
|
|
||||||
assert(fbxprop == b'DeformPercent')
|
assert(fbxprop == b'DeformPercent')
|
||||||
|
for channel, curves in channel_to_curves.items():
|
||||||
assert(channel == 0)
|
assert(channel == 0)
|
||||||
value = v / 100.0
|
blen_curve = blen_curves[channel]
|
||||||
deform_values.append(value)
|
parsed_curves = tuple(map(blen_read_single_animation_curve, curves))
|
||||||
|
fbx_key_times, values = _combine_same_property_curves(parsed_curves)
|
||||||
for fc, v in zip(blen_curves, (value,)):
|
bl_key_times = _convert_fbx_time_to_blender_time(fbx_key_times, anim_offset, 0, fps)
|
||||||
store_keyframe(fc, frame, v)
|
# A fully activated shape key in FBX DeformPercent is 100.0 whereas it is 1.0 in Blender.
|
||||||
|
values = values / 100.0
|
||||||
|
blen_store_keyframes(blen_curve, bl_key_times, values)
|
||||||
|
# Store the minimum and maximum shape key values, so that the shape key's slider range can be expanded if
|
||||||
|
# necessary after reading all animations.
|
||||||
|
deform_values.append(values.min())
|
||||||
|
deform_values.append(values.max())
|
||||||
|
|
||||||
elif isinstance(item, Camera):
|
elif isinstance(item, Camera):
|
||||||
for frame, values in blen_read_animations_curves_iter(fbx_curves, anim_offset, 0, fps):
|
for fbxprop, channel_to_curves in fbx_curves.items():
|
||||||
focal_length = 0.0
|
is_focus_distance = fbxprop == b'FocusDistance'
|
||||||
focus_distance = 0.0
|
assert(fbxprop == b'FocalLength' or is_focus_distance)
|
||||||
for v, (fbxprop, channel, _fbx_acdata) in values:
|
for channel, curves in channel_to_curves.items():
|
||||||
assert(fbxprop == b'FocalLength' or fbxprop == b'FocusDistance' )
|
|
||||||
assert(channel == 0)
|
assert(channel == 0)
|
||||||
if (fbxprop == b'FocalLength' ):
|
# The indices are determined by the creation of the `props` list above.
|
||||||
focal_length = v
|
blen_curve = blen_curves[1 if is_focus_distance else 0]
|
||||||
elif(fbxprop == b'FocusDistance'):
|
parsed_curves = tuple(map(blen_read_single_animation_curve, curves))
|
||||||
focus_distance = v / 1000 * global_scale
|
fbx_key_times, values = _combine_same_property_curves(parsed_curves)
|
||||||
|
bl_key_times = _convert_fbx_time_to_blender_time(fbx_key_times, anim_offset, 0, fps)
|
||||||
for fc, v in zip(blen_curves, (focal_length, focus_distance)):
|
if is_focus_distance:
|
||||||
store_keyframe(fc, frame, v)
|
# Remap the imported values from FBX to Blender.
|
||||||
|
values = values / 1000.0
|
||||||
|
values *= global_scale
|
||||||
|
blen_store_keyframes(blen_curve, bl_key_times, values)
|
||||||
|
|
||||||
else: # Object or PoseBone:
|
else: # Object or PoseBone:
|
||||||
if item.is_bone:
|
|
||||||
bl_obj = item.bl_obj.pose.bones[item.bl_bone]
|
|
||||||
else:
|
|
||||||
bl_obj = item.bl_obj
|
|
||||||
|
|
||||||
transform_data = item.fbx_transform_data
|
transform_data = item.fbx_transform_data
|
||||||
rot_eul_prev = bl_obj.rotation_euler.copy()
|
|
||||||
rot_quat_prev = bl_obj.rotation_quaternion.copy()
|
|
||||||
|
|
||||||
# Pre-compute inverted local rest matrix of the bone, if relevant.
|
# Each transformation curve needs to have keyframes at the times of every other transformation curve
|
||||||
restmat_inv = item.get_bind_matrix().inverted_safe() if item.is_bone else None
|
# (interpolating missing values), so that we can construct a matrix at every keyframe.
|
||||||
|
transform_prop_to_attr = {
|
||||||
|
b'Lcl Translation': transform_data.loc,
|
||||||
|
b'Lcl Rotation': transform_data.rot,
|
||||||
|
b'Lcl Scaling': transform_data.sca,
|
||||||
|
}
|
||||||
|
|
||||||
for frame, values in blen_read_animations_curves_iter(fbx_curves, anim_offset, 0, fps):
|
times_and_values_tuples = []
|
||||||
for v, (fbxprop, channel, _fbx_acdata) in values:
|
initial_values = []
|
||||||
if fbxprop == b'Lcl Translation':
|
channel_keys = []
|
||||||
transform_data.loc[channel] = v
|
for fbxprop, channel_to_curves in fbx_curves.items():
|
||||||
elif fbxprop == b'Lcl Rotation':
|
if fbxprop not in transform_prop_to_attr:
|
||||||
transform_data.rot[channel] = v
|
# Currently, we only care about transformation curves.
|
||||||
elif fbxprop == b'Lcl Scaling':
|
continue
|
||||||
transform_data.sca[channel] = v
|
for channel, curves in channel_to_curves.items():
|
||||||
mat, _, _ = blen_read_object_transform_do(transform_data)
|
assert(channel in {0, 1, 2})
|
||||||
|
parsed_curves = tuple(map(blen_read_single_animation_curve, curves))
|
||||||
|
fbx_key_times, values = _combine_same_property_curves(parsed_curves)
|
||||||
|
|
||||||
# compensate for changes in the local matrix during processing
|
channel_keys.append((fbxprop, channel))
|
||||||
if item.anim_compensation_matrix:
|
|
||||||
mat = mat @ item.anim_compensation_matrix
|
|
||||||
|
|
||||||
# apply pre- and post matrix
|
initial_values.append(transform_prop_to_attr[fbxprop][channel])
|
||||||
# post-matrix will contain any correction for lights, camera and bone orientation
|
|
||||||
# pre-matrix will contain any correction for a parent's correction matrix or the global matrix
|
|
||||||
if item.pre_matrix:
|
|
||||||
mat = item.pre_matrix @ mat
|
|
||||||
if item.post_matrix:
|
|
||||||
mat = mat @ item.post_matrix
|
|
||||||
|
|
||||||
# And now, remove that rest pose matrix from current mat (also in parent space).
|
times_and_values_tuples.append((fbx_key_times, values))
|
||||||
if restmat_inv:
|
|
||||||
mat = restmat_inv @ mat
|
|
||||||
|
|
||||||
# Now we have a virtual matrix of transform from AnimCurves, we can insert keyframes!
|
combined_fbx_times, values_arrays = _combine_curve_keyframes(times_and_values_tuples, initial_values)
|
||||||
loc, rot, sca = mat.decompose()
|
|
||||||
if rot_mode == 'QUATERNION':
|
|
||||||
if rot_quat_prev.dot(rot) < 0.0:
|
|
||||||
rot = -rot
|
|
||||||
rot_quat_prev = rot
|
|
||||||
elif rot_mode == 'AXIS_ANGLE':
|
|
||||||
vec, ang = rot.to_axis_angle()
|
|
||||||
rot = ang, vec.x, vec.y, vec.z
|
|
||||||
else: # Euler
|
|
||||||
rot = rot.to_euler(rot_mode, rot_eul_prev)
|
|
||||||
rot_eul_prev = rot
|
|
||||||
|
|
||||||
# Add each keyframe and its value to the keyframe dict
|
bl_key_times = _convert_fbx_time_to_blender_time(combined_fbx_times, anim_offset, 0, fps)
|
||||||
for fc, value in zip(blen_curves, chain(loc, rot, sca)):
|
|
||||||
store_keyframe(fc, frame, value)
|
|
||||||
|
|
||||||
# Add all keyframe points to the fcurves at once and modify them after
|
flattened_channel_values_gen = _transformation_curves_gen(item, values_arrays, channel_keys)
|
||||||
for fc_key, key_values in keyframes.items():
|
|
||||||
data_path, index = fc_key
|
|
||||||
|
|
||||||
# Add all keyframe points at once
|
num_loc_channels = 3
|
||||||
fcurve = action.fcurves.find(data_path=data_path, index=index)
|
num_rot_channels = 4 if rot_mode in {'QUATERNION', 'AXIS_ANGLE'} else 3 # Variations of EULER are all 3
|
||||||
num_keys = len(key_values) // 2
|
num_sca_channels = 3
|
||||||
fcurve.keyframe_points.add(num_keys)
|
num_channels = num_loc_channels + num_rot_channels + num_sca_channels
|
||||||
fcurve.keyframe_points.foreach_set('co', key_values)
|
num_frames = len(combined_fbx_times)
|
||||||
linear_enum_value = bpy.types.Keyframe.bl_rna.properties['interpolation'].enum_items['LINEAR'].value
|
full_length = num_channels * num_frames
|
||||||
fcurve.keyframe_points.foreach_set('interpolation', (linear_enum_value,) * num_keys)
|
|
||||||
|
|
||||||
# Since we inserted our keyframes in 'ultra-fast' mode, we have to update the fcurves now.
|
# TODO: It may be beneficial to iterate into np.float64 since the generator yields Python floats
|
||||||
for fc in blen_curves:
|
flattened_channel_values = np.fromiter(flattened_channel_values_gen, dtype=np.single, count=full_length)
|
||||||
fc.update()
|
# Reshape to one row per frame and then view the transpose so that each row corresponds to a single channel.
|
||||||
|
# e.g.
|
||||||
|
# loc_channels = channel_values[:num_loc_channels]
|
||||||
|
# rot_channels = channel_values[num_loc_channels:num_loc_channels + num_rot_channels]
|
||||||
|
# sca_channels = channel_values[num_loc_channels + num_rot_channels:]
|
||||||
|
channel_values = flattened_channel_values.reshape(num_frames, num_channels).T
|
||||||
|
|
||||||
|
for blen_curve, values in zip(blen_curves, channel_values):
|
||||||
|
# TODO: The bl_key_times is used more than once, meaning we duplicate some of the work
|
||||||
|
blen_store_keyframes(blen_curve, bl_key_times, values)
|
||||||
|
|
||||||
|
|
||||||
def blen_read_animations(fbx_tmpl_astack, fbx_tmpl_alayer, stacks, scene, anim_offset, global_scale):
|
def blen_read_animations(fbx_tmpl_astack, fbx_tmpl_alayer, stacks, scene, anim_offset, global_scale):
|
||||||
|
Loading…
Reference in New Issue
Block a user
transform_data.scale[2]
I believe?In this case
.sca
is correct, theFBXTransformData
namedtuple uses rather short attribute names.