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feat: Update version to 2.0.1, refactor asset library handling, and enhance layer import process

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马南
2026-07-07 12:38:49 +08:00
parent 720233b14c
commit 7b9151046d
9 changed files with 567 additions and 372 deletions
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259
src/bioxelnodes/operators/io_worker.py Normal file
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import json
import sys
import traceback
from pathlib import Path
PACKAGE_PARENT = Path(__file__).resolve().parents[2]
if str(PACKAGE_PARENT) not in sys.path:
sys.path.insert(0, str(PACKAGE_PARENT))
import numpy as np
import transforms3d
from bioxelnodes.bioxel.layer import Layer
from bioxelnodes.bioxel.parse import parse_volumetric_data
from bioxelnodes.layer import save_layers_to_cache
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 write_json(path: Path, data):
temp_path = path.with_suffix(path.suffix + ".tmp")
temp_path.write_text(json.dumps(data), encoding="utf-8")
temp_path.replace(path)
def check_cancel(cancel_path: Path):
if cancel_path.exists():
raise KeyboardInterrupt("Cancelled by user")
def make_progress_writer(progress_path: Path, cancel_path: Path, scale=1.0, offset=0.0):
def progress_callback(factor, text):
check_cancel(cancel_path)
write_json(
progress_path,
{
"factor": offset + factor * scale,
"text": text,
},
)
return progress_callback
def progress_callback_factory(progress_path: Path, cancel_path: Path, layer_name, progress, progress_step):
def progress_callback(frame, total):
check_cancel(cancel_path)
sub_progress_step = progress_step / total
sub_progress = progress + frame * sub_progress_step
text = f"Processing {layer_name} Frame {frame+1}..."
write_json(progress_path, {"factor": sub_progress, "text": text})
print(text)
return progress_callback
def read_meta(config, progress_path: Path, cancel_path: Path):
progress_callback = make_progress_writer(progress_path, cancel_path)
series_id = config["series_id"] if config["series_id"] != "empty" else ""
data, meta = parse_volumetric_data(
data_file=config["filepath"],
series_id=series_id,
progress_callback=progress_callback,
)
check_cancel(cancel_path)
return {
"meta": {
**meta,
"spacing": list(meta["spacing"]),
"affine": meta["affine"].tolist(),
"xyz_shape": list(meta["xyz_shape"]),
},
"label_count": int(np.max(data)),
"dtype": data.dtype.str,
"dtype_kind": data.dtype.kind,
}
def build_layers(config, progress_path: Path, cancel_path: Path):
write_json(progress_path, {"factor": 0.0, "text": "Parsing Volumetirc Data..."})
progress_callback = make_progress_writer(progress_path, cancel_path, scale=0.2)
data, meta = parse_volumetric_data(
data_file=config["filepath"],
series_id=config["series_id"],
progress_callback=progress_callback,
)
check_cancel(cancel_path)
orig_shape = tuple(config["orig_shape"])
orig_spacing = tuple(config["orig_spacing"])
shape = get_layer_shape(config["bioxel_size"], orig_shape, orig_spacing)
mat_scale = transforms3d.zooms.zfdir2aff(config["bioxel_size"])
affine = np.dot(meta["affine"], mat_scale)
kind = config["read_as"].lower()
check_cancel(cancel_path)
frame_source = config["frame_source"]
if frame_source == "-1":
data = data[0:1, :, :, :, :]
elif frame_source == "0":
pass
elif frame_source == "1":
data = data.transpose(1, 0, 2, 3, 4)
shape = (1, shape[1], shape[2])
elif frame_source == "2":
data = data.transpose(2, 1, 0, 3, 4)
shape = (shape[0], 1, shape[2])
elif frame_source == "3":
data = data.transpose(3, 1, 2, 0, 4)
shape = (shape[0], shape[1], 1)
else:
data = data.transpose(4, 1, 2, 3, 0)
layers = []
if kind == "label":
name = config["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):
check_cancel(cancel_path)
name_i = f"{name}_{i+1}"
progress = 0.2 + i * progress_step
write_json(progress_path, {"factor": progress, "text": f"Processing {name_i}..."})
progress_callback = progress_callback_factory(
progress_path, cancel_path, name_i, progress, progress_step
)
label_data = data == np.full_like(data, i + 1)
layer = Layer(data=label_data, name=name_i, kind=kind)
layer.resize(
shape=shape,
smooth=config["smooth"],
progress_callback=progress_callback,
)
layer.affine = affine
layers.append(layer)
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"]:
data = data.astype(np.float32)
min_val = data.min()
max_val = data.max()
if max_val != min_val:
data = (data - min_val) / (max_val - min_val)
else:
data = np.zeros_like(data, dtype=np.float32)
else:
data = data.astype(np.float32)
name = config["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]
check_cancel(cancel_path)
write_json(progress_path, {"factor": 0.2, "text": f"Processing {name}..."})
progress_callback = progress_callback_factory(progress_path, cancel_path, name, 0.2, 0.7)
layer = Layer(data=data, name=name, kind=kind)
layer.resize(shape=shape, progress_callback=progress_callback)
layer.affine = affine
layers.append(layer)
elif kind == "scalar":
name = config["layer_name"] or "Scalar"
if config["remap"]:
data = data.astype(np.float32)
min_val = data.min()
max_val = data.max()
if max_val != min_val:
data = (data - min_val) / (max_val - min_val)
else:
data = np.zeros_like(data, dtype=np.float32)
if config["split_channel"]:
progress_step = 0.7 / config["channel_count"]
for i in range(config["channel_count"]):
check_cancel(cancel_path)
name_i = f"{name}_{i+1}"
progress = 0.2 + i * progress_step
write_json(progress_path, {"factor": progress, "text": f"Processing {name_i}..."})
progress_callback = progress_callback_factory(
progress_path, cancel_path, name_i, progress, progress_step
)
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)
else:
check_cancel(cancel_path)
write_json(progress_path, {"factor": 0.2, "text": f"Processing {name}..."})
progress_callback = progress_callback_factory(progress_path, cancel_path, name, 0.2, 0.7)
layer = Layer(data=data, name=name, kind=kind)
layer.resize(shape=shape, progress_callback=progress_callback)
layer.affine = affine
layers.append(layer)
check_cancel(cancel_path)
write_json(progress_path, {"factor": 0.9, "text": "Creating Layers..."})
cache_infos = save_layers_to_cache(layers, config["cache_dir"])
return {"cache_infos": cache_infos, "added_ids": [item["id"] for item in cache_infos]}
def main():
config_path = Path(sys.argv[-1])
config = json.loads(config_path.read_text(encoding="utf-8"))
progress_path = Path(config["progress_path"])
result_path = Path(config["result_path"])
cancel_path = Path(config["cancel_path"])
try:
if config["command"] == "read_meta":
result = read_meta(config, progress_path, cancel_path)
elif config["command"] == "import_layers":
result = build_layers(config, progress_path, cancel_path)
else:
raise ValueError(f"Unknown command: {config['command']}")
write_json(result_path, {"ok": True, **result})
write_json(progress_path, {"factor": 1.0, "text": ""})
except KeyboardInterrupt:
write_json(result_path, {"ok": False, "cancelled": True})
except Exception as e:
write_json(
result_path,
{
"ok": False,
"error": str(e),
"traceback": traceback.format_exc(),
},
)
if __name__ == "__main__":
main()