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feat: Update release workflow and manifest for improved dependency management and layer handling

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马南
2026-05-25 14:09:44 +08:00
parent e06cadc67e
commit cd00c2bfef
5 changed files with 282 additions and 65 deletions
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280
src/bioxelnodes/operators/io.py
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@@ -12,20 +12,37 @@ import transforms3d
from ..props import BIOXEL_Series
from ..utils import get_layer_obj, wrapped_label
from ..bioxel import (
DICOM_EXTS,
SUPPORT_EXTS,
read,
read_meta,
calc_layer_shape,
calc_layer_size,
get_ext,
)
from ..bioxel.layer import Layer
from ..bioxel.parse import DICOM_EXTS, SUPPORT_EXTS, get_ext, parse_volumetric_data
from ..utils import get_cache_dir, progress_update, progress_bar
from ..layer import get_layer_caches, save_layers_to_json
def get_layer_shape(bioxel_size: float, orig_shape: tuple, orig_spacing: tuple):
shape = (
int(orig_shape[0] / bioxel_size * orig_spacing[0]),
int(orig_shape[1] / bioxel_size * orig_spacing[1]),
int(orig_shape[2] / bioxel_size * orig_spacing[2]),
)
return (
shape[0] if shape[0] > 0 else 1,
shape[1] if shape[1] > 0 else 1,
shape[2] if shape[2] > 0 else 1,
)
def get_layer_size(shape: tuple, bioxel_size: float, scale: float = 1.0):
size = (
float(shape[0] * bioxel_size * scale),
float(shape[1] * bioxel_size * scale),
float(shape[2] * bioxel_size * scale),
)
return size
"""
ImportData -> ParseVolumetricData -> ImportDataDialog
start import parse data execute import
@@ -194,7 +211,11 @@ class ParseVolumetricData(bpy.types.Operator):
try:
series_id = self.series_id if self.series_id != "empty" else ""
data = read_meta(self.filepath, series_id=series_id)
data, meta = parse_volumetric_data(
data_file=self.filepath,
series_id=series_id,
progress_callback=progress_callback,
)
except KeyboardInterrupt:
return
except Exception as e:
@@ -204,8 +225,8 @@ class ParseVolumetricData(bpy.types.Operator):
if cancel():
return
self.meta = data.meta
self.label_count = int(np.max(data.data))
self.meta = meta
self.label_count = int(np.max(data))
self.dtype = data.dtype
# Init cancel flag
@@ -313,8 +334,8 @@ class ParseVolumetricData(bpy.types.Operator):
bioxel_size = max(min(*orig_spacing), 1.0)
layer_shape = calc_layer_shape(bioxel_size, orig_shape, orig_spacing)
layer_size = calc_layer_size(layer_shape, bioxel_size, 0.01)
layer_shape = get_layer_shape(bioxel_size, orig_shape, orig_spacing)
layer_size = get_layer_size(layer_shape, bioxel_size, 0.01)
min_log10 = math.floor(math.log10(min(*layer_size)))
max_log10 = math.floor(math.log10(max(*layer_size)))
@@ -526,23 +547,33 @@ class ImportDataDialog(bpy.types.Operator):
def execute(self, context):
def import_volumetric_data_func(self, context, cancel):
progress_update(context, 0.0, "Parsing Volumetirc Data...")
def progress_callback(factor, text):
if cancel():
raise KeyboardInterrupt("Cancelled by user")
progress_update(context, factor * 0.2, text)
try:
data = read(self.filepath, self.series_id, progress_callback)
def progress_callback_factory(layer_name, progress, progress_step):
def progress_callback(frame, total):
if cancel():
raise KeyboardInterrupt("Cancelled by user")
sub_progress_step = progress_step / total
sub_progress = progress + frame * sub_progress_step
progress_update(
context,
sub_progress,
f"Processing {layer_name} Frame {frame+1}...",
)
print(f"Processing {layer_name} Frame {frame+1}...")
self.layers = data.to_layers(
kind=self.read_as.lower(),
layer_name=self.layer_name,
bioxel_size=self.bioxel_size,
smooth=self.smooth,
remap=self.remap,
split_channel=self.split_channel,
frame_source=self.frame_source,
progress_callback=lambda f, t: progress_callback(0.2 + f * 0.7, t),
return progress_callback
try:
data, meta = parse_volumetric_data(
data_file=self.filepath,
series_id=self.series_id,
progress_callback=progress_callback,
)
except KeyboardInterrupt:
@@ -554,6 +585,203 @@ class ImportDataDialog(bpy.types.Operator):
if cancel():
return
shape = get_layer_shape(
self.bioxel_size, self.orig_shape, self.orig_spacing
)
mat_scale = transforms3d.zooms.zfdir2aff(self.bioxel_size)
affine = np.dot(meta["affine"], mat_scale)
kind = self.read_as.lower()
if cancel():
return
# change shape as sequence or not
if self.frame_source == "-1":
data = data[0:1, :, :, :, :]
elif self.frame_source == "0":
# frame as frame
pass
elif self.frame_source == "1":
# X as frame
data = data.transpose(1, 0, 2, 3, 4)
shape = (1, shape[1], shape[2])
elif self.frame_source == "2":
# Y as frame
data = data.transpose(2, 1, 0, 3, 4)
shape = (shape[0], 1, shape[2])
elif self.frame_source == "3":
# Z as frame
data = data.transpose(3, 1, 2, 0, 4)
shape = (shape[0], shape[1], 1)
else:
# channel as frame
data = data.transpose(4, 1, 2, 3, 0)
layers = []
if kind == "label":
name = self.layer_name or "Label"
data = data.astype(int)
label_count = int(np.max(data))
progress_step = 0.7 / label_count
for i in range(label_count):
if cancel():
return
name_i = f"{name}_{i+1}"
progress = 0.2 + i * progress_step
progress_update(context, progress, f"Processing {name_i}...")
progress_callback = progress_callback_factory(
name_i, progress, progress_step
)
label_data = data == np.full_like(data, i + 1)
# label_data = label_data.astype(np.float32)
try:
layer = Layer(data=label_data, name=name_i, kind=kind)
layer.resize(
shape=shape,
smooth=self.smooth,
progress_callback=progress_callback,
)
layer.affine = affine
layers.append(layer)
except KeyboardInterrupt:
return
except Exception as e:
self.has_error = e
return
if kind == "color":
if np.issubdtype(np.uint8, data.dtype):
data = np.multiply(data, 1.0 / 256, dtype=np.float32)
elif data.dtype.kind in ["u", "i"]:
# Convert the normalized array to float dtype
data = data.astype(np.float32)
min_val = data.min()
max_val = data.max()
# Avoid division by zero if all values are the same
if max_val != min_val:
# Normalize the array to the range (0,1)
data = (data - min_val) / (max_val - min_val)
else:
# If all values are the same, the normalized array will be all zeros
data = np.zeros_like(data, dtype=np.float32)
else:
data = data.astype(np.float32)
# Gamma Correct
# data = data ** 2.2
name = self.layer_name or "Color"
if data.shape[4] == 1:
data = np.repeat(data, repeats=3, axis=4)
elif data.shape[4] == 2:
d_shape = list(data.shape)
d_shape = d_shape[:4] + [1]
zore = np.zeros(tuple(d_shape), dtype=np.float32)
data = np.concatenate((data, zore), axis=-1)
elif data.shape[4] > 3:
data = data[:, :, :, :, :3]
if cancel():
return
progress_update(context, 0.2, f"Processing {name}...")
progress_callback = progress_callback_factory(name, 0.2, 0.7)
try:
layer = Layer(data=data, name=name, kind=kind)
layer.resize(shape=shape, progress_callback=progress_callback)
layer.affine = affine
layers.append(layer)
except KeyboardInterrupt:
return
except Exception as e:
self.has_error = e
return
elif kind == "scalar":
name = self.layer_name or "Scalar"
if self.remap:
# Convert the normalized array to float dtype
data = data.astype(np.float32)
min_val = data.min()
max_val = data.max()
# Avoid division by zero if all values are the same
if max_val != min_val:
# Normalize the array to the range (0,1)
data = (data - min_val) / (max_val - min_val)
else:
# If all values are the same, the normalized array will be all zeros
data = np.zeros_like(data, dtype=np.float32)
if self.split_channel:
progress_step = 0.7 / self.channel_count
for i in range(self.channel_count):
if cancel():
return
name_i = f"{name}_{i+1}"
progress = 0.2 + i * progress_step
progress_update(context, progress, f"Processing {name_i}...")
progress_callback = progress_callback_factory(
name_i, progress, progress_step
)
try:
layer = Layer(
data=data[:, :, :, :, i : i + 1], name=name_i, kind=kind
)
layer.resize(
shape=shape, progress_callback=progress_callback
)
layer.affine = affine
layers.append(layer)
except KeyboardInterrupt:
return
except Exception as e:
self.has_error = e
return
else:
if cancel():
return
progress_update(context, 0.2, f"Processing {name}...")
progress_callback = progress_callback_factory(name, 0.2, 0.7)
try:
layer = Layer(data=data, name=name, kind=kind)
layer.resize(shape=shape, progress_callback=progress_callback)
layer.affine = affine
layers.append(layer)
except KeyboardInterrupt:
return
except Exception as e:
self.has_error = e
return
if cancel():
return
self.layers = layers
progress_update(context, 0.9, "Creating Layers...")
self.is_cancelled = False
@@ -623,7 +851,7 @@ class ImportDataDialog(bpy.types.Operator):
return {"RUNNING_MODAL"}
def draw(self, context):
layer_shape = calc_layer_shape(
layer_shape = get_layer_shape(
self.bioxel_size, self.orig_shape, self.orig_spacing
)