From 58c2f5018e66d394cc6607d88b1fbabf276884df Mon Sep 17 00:00:00 2001
From: s214735 <s214735@dtu.dk>
Date: Thu, 26 Dec 2024 10:44:58 +0100
Subject: [PATCH] Checked rest of files
---
qim3d/ml/_augmentations.py | 2 +-
qim3d/ml/_data.py | 20 +++++++---
qim3d/ml/_ml_utils.py | 26 ++++++-------
qim3d/ml/models/_unet.py | 37 ++++++++++--------
.../operations/_common_operations_methods.py | 2 +-
qim3d/processing/_layers.py | 9 ++++-
qim3d/processing/_local_thickness.py | 2 +-
qim3d/processing/_structure_tensor.py | 2 +-
qim3d/segmentation/_connected_components.py | 2 +-
qim3d/utils/_doi.py | 18 ++++-----
qim3d/utils/_misc.py | 20 +++++-----
qim3d/utils/_ome_zarr.py | 4 +-
qim3d/utils/_progress_bar.py | 8 ++--
qim3d/utils/_server.py | 4 +-
qim3d/utils/_system.py | 4 +-
qim3d/viz/_cc.py | 12 +++---
qim3d/viz/_data_exploration.py | 20 +++++-----
qim3d/viz/_detection.py | 2 +-
qim3d/viz/_k3d.py | 38 +++++++++----------
qim3d/viz/_layers2d.py | 2 +-
qim3d/viz/_metrics.py | 37 ++++++++++--------
21 files changed, 150 insertions(+), 121 deletions(-)
diff --git a/qim3d/ml/_augmentations.py b/qim3d/ml/_augmentations.py
index ea81e53a..8cb0b472 100644
--- a/qim3d/ml/_augmentations.py
+++ b/qim3d/ml/_augmentations.py
@@ -38,7 +38,7 @@ class Augmentation:
self.transform_validation = transform_validation
self.transform_test = transform_test
- def augment(self, im_h, im_w, level=None):
+ def augment(self, im_h: int, im_w: int, level: bool = None):
"""
Returns an albumentations.core.composition.Compose class depending on the augmentation level.
A baseline augmentation is implemented regardless of the level, and a set of augmentations are added depending of the level.
diff --git a/qim3d/ml/_data.py b/qim3d/ml/_data.py
index 38fbdac7..17f9a281 100644
--- a/qim3d/ml/_data.py
+++ b/qim3d/ml/_data.py
@@ -4,7 +4,9 @@ from PIL import Image
from qim3d.utils._logger import log
import torch
import numpy as np
-
+from typing import Optional, Callable
+import torch.nn as nn
+from ._data import Augmentation
class Dataset(torch.utils.data.Dataset):
"""
@@ -36,7 +38,7 @@ class Dataset(torch.utils.data.Dataset):
transform=albumentations.Compose([ToTensorV2()]))
image, target = dataset[idx]
"""
- def __init__(self, root_path: str, split="train", transform=None):
+ def __init__(self, root_path: str, split: str = "train", transform: Optional[Callable] = None):
super().__init__()
# Check if split is valid
@@ -58,7 +60,7 @@ class Dataset(torch.utils.data.Dataset):
def __len__(self):
return len(self.sample_images)
- def __getitem__(self, idx):
+ def __getitem__(self, idx: int):
image_path = self.sample_images[idx]
target_path = self.sample_targets[idx]
@@ -76,7 +78,7 @@ class Dataset(torch.utils.data.Dataset):
# TODO: working with images of different sizes
- def check_shape_consistency(self,sample_images):
+ def check_shape_consistency(self,sample_images: tuple[str]):
image_shapes= []
for image_path in sample_images:
image_shape = self._get_shape(image_path)
@@ -131,7 +133,7 @@ def check_resize(im_height: int, im_width: int, resize: str, n_channels: int):
return h_adjust, w_adjust
-def prepare_datasets(path: str, val_fraction: float, model, augmentation):
+def prepare_datasets(path: str, val_fraction: float, model: nn.Module, augmentation: Augmentation):
"""
Splits and augments the train/validation/test datasets.
@@ -172,7 +174,13 @@ def prepare_datasets(path: str, val_fraction: float, model, augmentation):
return train_set, val_set, test_set
-def prepare_dataloaders(train_set, val_set, test_set, batch_size, shuffle_train = True, num_workers = 8, pin_memory = False):
+def prepare_dataloaders(train_set: torch.utils.data,
+ val_set: torch.utils.data,
+ test_set: torch.utils.data,
+ batch_size: int,
+ shuffle_train: bool = True,
+ num_workers: int = 8,
+ pin_memory: bool = False):
"""
Prepares the dataloaders for model training.
diff --git a/qim3d/ml/_ml_utils.py b/qim3d/ml/_ml_utils.py
index 7c8a3b86..1c442791 100644
--- a/qim3d/ml/_ml_utils.py
+++ b/qim3d/ml/_ml_utils.py
@@ -9,18 +9,18 @@ from qim3d.viz._metrics import plot_metrics
from tqdm.auto import tqdm
from tqdm.contrib.logging import logging_redirect_tqdm
-
+from models._unet import Hyperparameters
def train_model(
- model,
- hyperparameters,
- train_loader,
- val_loader,
- eval_every=1,
- print_every=5,
- plot=True,
- return_loss=False,
-):
+ model: torch.nn.Module,
+ hyperparameters: Hyperparameters,
+ train_loader: torch.utils.data.DataLoader,
+ val_loader: torch.utils.data.DataLoader,
+ eval_every: int = 1,
+ print_every: int = 5,
+ plot: bool = True,
+ return_loss: bool = False,
+) -> tuple[tuple[float], tuple[float]]:
"""Function for training Neural Network models.
Args:
@@ -137,7 +137,7 @@ def train_model(
return train_loss, val_loss
-def model_summary(dataloader, model):
+def model_summary(dataloader: torch.utils.data.DataLoader, model: torch.nn.Module):
"""Prints the summary of a PyTorch model.
Args:
@@ -160,7 +160,7 @@ def model_summary(dataloader, model):
return model_s
-def inference(data, model):
+def inference(data: torch.utils.data.Dataset, model: torch.nn.Module) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
"""Performs inference on input data using the specified model.
Performs inference on the input data using the provided model. The input data should be in the form of a list,
@@ -242,7 +242,7 @@ def inference(data, model):
return inputs, targets, preds
-def volume_inference(volume, model, threshold=0.5):
+def volume_inference(volume: np.ndarray, model: torch.nn.Module, threshold:float = 0.5) -> np.ndarray:
"""
Compute on the entire volume
Args:
diff --git a/qim3d/ml/models/_unet.py b/qim3d/ml/models/_unet.py
index 353d10bd..27ee78a4 100644
--- a/qim3d/ml/models/_unet.py
+++ b/qim3d/ml/models/_unet.py
@@ -119,13 +119,13 @@ class Hyperparameters:
def __init__(
self,
- model,
- n_epochs=10,
- learning_rate=1e-3,
- optimizer="Adam",
- momentum=0,
- weight_decay=0,
- loss_function="Focal",
+ model: nn.Module,
+ n_epochs: int = 10,
+ learning_rate: float = 1e-3,
+ optimizer: str = "Adam",
+ momentum: float = 0,
+ weight_decay: float = 0,
+ loss_function: str = "Focal",
):
# TODO: implement custom loss_functions? then add a check to see if loss works for segmentation.
@@ -168,13 +168,13 @@ class Hyperparameters:
def model_params(
self,
- model,
- n_epochs,
- optimizer,
- learning_rate,
- weight_decay,
- momentum,
- loss_function,
+ model: nn.Module,
+ n_epochs: int,
+ optimizer: str,
+ learning_rate: float,
+ weight_decay: float,
+ momentum: float,
+ loss_function: str,
):
optim = self._optimizer(model, optimizer, learning_rate, weight_decay, momentum)
@@ -188,7 +188,12 @@ class Hyperparameters:
return hyper_dict
# selecting the optimizer
- def _optimizer(self, model, optimizer, learning_rate, weight_decay, momentum):
+ def _optimizer(self,
+ model: nn.Module,
+ optimizer: str,
+ learning_rate: float,
+ weight_decay: float,
+ momentum: float):
from torch.optim import Adam, SGD, RMSprop
if optimizer == "Adam":
@@ -212,7 +217,7 @@ class Hyperparameters:
return optim
# selecting the loss function
- def _loss_functions(self, loss_function):
+ def _loss_functions(self, loss_function: str):
from monai.losses import FocalLoss, DiceLoss, DiceCELoss
from torch.nn import BCEWithLogitsLoss
diff --git a/qim3d/operations/_common_operations_methods.py b/qim3d/operations/_common_operations_methods.py
index 1c14e163..5975c30e 100644
--- a/qim3d/operations/_common_operations_methods.py
+++ b/qim3d/operations/_common_operations_methods.py
@@ -153,7 +153,7 @@ def fade_mask(
def overlay_rgb_images(
- background: np.ndarray, foreground: np.ndarray, alpha: float = 0.5, hide_black:bool = True,
+ background: np.ndarray, foreground: np.ndarray, alpha: float = 0.5, hide_black: bool = True,
) -> np.ndarray:
"""
Overlay an RGB foreground onto an RGB background using alpha blending.
diff --git a/qim3d/processing/_layers.py b/qim3d/processing/_layers.py
index d91ef0a4..ed90133f 100644
--- a/qim3d/processing/_layers.py
+++ b/qim3d/processing/_layers.py
@@ -2,7 +2,14 @@ import numpy as np
from slgbuilder import GraphObject
from slgbuilder import MaxflowBuilder
-def segment_layers(data:np.ndarray, inverted:bool = False, n_layers:int = 1, delta:float = 1, min_margin:int = 10, max_margin:int = None, wrap:bool = False):
+def segment_layers(data: np.ndarray,
+ inverted: bool = False,
+ n_layers: int = 1,
+ delta: float = 1,
+ min_margin: int = 10,
+ max_margin: int = None,
+ wrap: bool = False
+ ) -> list:
"""
Works on 2D and 3D data.
Light one function wrapper around slgbuilder https://github.com/Skielex/slgbuilder to do layer segmentation
diff --git a/qim3d/processing/_local_thickness.py b/qim3d/processing/_local_thickness.py
index a7e877d6..947f8865 100644
--- a/qim3d/processing/_local_thickness.py
+++ b/qim3d/processing/_local_thickness.py
@@ -10,7 +10,7 @@ def local_thickness(
image: np.ndarray,
scale: float = 1,
mask: Optional[np.ndarray] = None,
- visualize=False,
+ visualize: bool = False,
**viz_kwargs
) -> np.ndarray:
"""Wrapper for the local thickness function from the [local thickness package](https://github.com/vedranaa/local-thickness)
diff --git a/qim3d/processing/_structure_tensor.py b/qim3d/processing/_structure_tensor.py
index 10eba890..f6dc98cd 100644
--- a/qim3d/processing/_structure_tensor.py
+++ b/qim3d/processing/_structure_tensor.py
@@ -12,7 +12,7 @@ def structure_tensor(
rho: float = 6.0,
base_noise: bool = True,
full: bool = False,
- visualize=False,
+ visualize: bool = False,
**viz_kwargs
) -> Tuple[np.ndarray, np.ndarray]:
"""Wrapper for the 3D structure tensor implementation from the [structure_tensor package](https://github.com/Skielex/structure-tensor/).
diff --git a/qim3d/segmentation/_connected_components.py b/qim3d/segmentation/_connected_components.py
index f43f0dc2..1f29b235 100644
--- a/qim3d/segmentation/_connected_components.py
+++ b/qim3d/segmentation/_connected_components.py
@@ -4,7 +4,7 @@ from qim3d.utils._logger import log
class CC:
- def __init__(self, connected_components, num_connected_components):
+ def __init__(self, connected_components: np.ndarray, num_connected_components: int):
"""
Initializes a ConnectedComponents object.
diff --git a/qim3d/utils/_doi.py b/qim3d/utils/_doi.py
index b3ece663..6c4ae626 100644
--- a/qim3d/utils/_doi.py
+++ b/qim3d/utils/_doi.py
@@ -4,7 +4,7 @@ import requests
from qim3d.utils._logger import log
-def _validate_response(response):
+def _validate_response(response: requests.Response) -> bool:
# Check if we got a good response
if not response.ok:
log.error(f"Could not read the provided DOI ({response.reason})")
@@ -13,7 +13,7 @@ def _validate_response(response):
return True
-def _doi_to_url(doi):
+def _doi_to_url(doi: str) -> str:
if doi[:3] != "http":
url = "https://doi.org/" + doi
else:
@@ -22,7 +22,7 @@ def _doi_to_url(doi):
return url
-def _make_request(doi, header):
+def _make_request(doi: str, header: str) -> requests.Response:
# Get url from doi
url = _doi_to_url(doi)
@@ -35,7 +35,7 @@ def _make_request(doi, header):
return response
-def _log_and_get_text(doi, header):
+def _log_and_get_text(doi, header) -> str:
response = _make_request(doi, header)
if response and response.encoding:
@@ -50,13 +50,13 @@ def _log_and_get_text(doi, header):
return text
-def get_bibtex(doi):
+def get_bibtex(doi: str):
"""Generates bibtex from doi"""
header = {"Accept": "application/x-bibtex"}
return _log_and_get_text(doi, header)
-def cusom_header(doi, header):
+def cusom_header(doi: str, header: str) -> str:
"""Allows a custom header to be passed
For example:
@@ -67,7 +67,7 @@ def cusom_header(doi, header):
"""
return _log_and_get_text(doi, header)
-def get_metadata(doi):
+def get_metadata(doi: str) -> dict:
"""Generates a metadata dictionary from doi"""
header = {"Accept": "application/vnd.citationstyles.csl+json"}
response = _make_request(doi, header)
@@ -76,7 +76,7 @@ def get_metadata(doi):
return metadata
-def get_reference(doi):
+def get_reference(doi: str) -> str:
"""Generates a metadata dictionary from doi and use it to build a reference string"""
metadata = get_metadata(doi)
@@ -84,7 +84,7 @@ def get_reference(doi):
return reference_string
-def build_reference_string(metadata):
+def build_reference_string(metadata: dict) -> str:
"""Generates a reference string from metadata"""
authors = ", ".join([f"{author['family']} {author['given']}" for author in metadata['author']])
year = metadata['issued']['date-parts'][0][0]
diff --git a/qim3d/utils/_misc.py b/qim3d/utils/_misc.py
index a754ecb8..3d8660b4 100644
--- a/qim3d/utils/_misc.py
+++ b/qim3d/utils/_misc.py
@@ -12,7 +12,7 @@ import difflib
import qim3d
-def get_local_ip():
+def get_local_ip() -> str:
"""Retrieves the local IP address of the current machine.
The function uses a socket to determine the local IP address.
@@ -42,7 +42,7 @@ def get_local_ip():
return ip_address
-def port_from_str(s):
+def port_from_str(s: str) -> int:
"""
Generates a port number from a given string.
@@ -65,7 +65,7 @@ def port_from_str(s):
return int(hashlib.sha1(s.encode("utf-8")).hexdigest(), 16) % (10**4)
-def gradio_header(title, port):
+def gradio_header(title: str, port: int) -> None:
"""Display the header for a Gradio server.
Displays a formatted header containing the provided title,
@@ -99,7 +99,7 @@ def gradio_header(title, port):
ouf.showlist(details, style="box", title="Starting gradio server")
-def sizeof(num, suffix="B"):
+def sizeof(num: float, suffix: str = "B") -> str:
"""Converts a number to a human-readable string representing its size.
Converts the given number to a human-readable string representing its size in
@@ -131,7 +131,7 @@ def sizeof(num, suffix="B"):
return f"{num:.1f} Y{suffix}"
-def find_similar_paths(path):
+def find_similar_paths(path: str) -> list[str]:
parent_dir = os.path.dirname(path) or "."
parent_files = os.listdir(parent_dir) if os.path.isdir(parent_dir) else ""
valid_paths = [os.path.join(parent_dir, file) for file in parent_files]
@@ -165,14 +165,14 @@ def get_file_size(file_path: str) -> int:
return file_size
-def stringify_path(path):
+def stringify_path(path: os.PathLike) -> str:
"""Converts an os.PathLike object to a string"""
if isinstance(path, os.PathLike):
path = path.__fspath__()
return path
-def get_port_dict():
+def get_port_dict() -> dict:
# Gets user and port
username = getpass.getuser()
url = f"https://platform.qim.dk/qim-api/get-port/{username}"
@@ -189,7 +189,7 @@ def get_port_dict():
return port_dict
-def get_css():
+def get_css() -> str:
current_directory = os.path.dirname(os.path.abspath(__file__))
parent_directory = os.path.abspath(os.path.join(current_directory, os.pardir))
@@ -201,7 +201,7 @@ def get_css():
return css_content
-def downscale_img(img, max_voxels=512**3):
+def downscale_img(img: np.ndarray, max_voxels: int = 512**3) -> np.ndarray:
"""Downscale image if total number of voxels exceeds 512³.
Args:
@@ -226,7 +226,7 @@ def downscale_img(img, max_voxels=512**3):
return zoom(img, zoom_factor, order=0)
-def scale_to_float16(arr: np.ndarray):
+def scale_to_float16(arr: np.ndarray) -> np.ndarray:
"""
Scale the input array to the float16 data type.
diff --git a/qim3d/utils/_ome_zarr.py b/qim3d/utils/_ome_zarr.py
index 452997f1..db7ad145 100644
--- a/qim3d/utils/_ome_zarr.py
+++ b/qim3d/utils/_ome_zarr.py
@@ -1,7 +1,7 @@
from zarr.util import normalize_chunks, normalize_dtype, normalize_shape
import numpy as np
-def get_chunk_size(shape:tuple, dtype):
+def get_chunk_size(shape:tuple, dtype: tuple) -> tuple[int, ...]:
"""
How the chunk size is computed in zarr.storage.init_array_metadata which is ran in the chain of functions we use
in qim3d.io.export_ome_zarr function
@@ -20,7 +20,7 @@ def get_chunk_size(shape:tuple, dtype):
return chunks
-def get_n_chunks(shapes:tuple, dtypes:tuple):
+def get_n_chunks(shapes: tuple, dtypes: tuple) -> int:
"""
Estimates how many chunks we will use in advence so we can pass this number to a progress bar and track how many
have been already written to disk
diff --git a/qim3d/utils/_progress_bar.py b/qim3d/utils/_progress_bar.py
index 629026f4..57f33738 100644
--- a/qim3d/utils/_progress_bar.py
+++ b/qim3d/utils/_progress_bar.py
@@ -24,7 +24,7 @@ class RepeatTimer(Timer):
self.function(*self.args, **self.kwargs)
class ProgressBar(ABC):
- def __init__(self,tqdm_kwargs:dict, repeat_time: float, *args, **kwargs):
+ def __init__(self, tqdm_kwargs: dict, repeat_time: float, *args, **kwargs):
"""
Context manager for ('with' statement) to track progress during a long progress over
which we don't have control (like loading a file) and thus can not insert the tqdm
@@ -98,7 +98,7 @@ class FileLoadingProgressBar(ProgressBar):
super().__init__( tqdm_kwargs, repeat_time)
self.process = psutil.Process()
- def get_new_update(self):
+ def get_new_update(self) -> int:
counters = self.process.io_counters()
try:
memory = counters.read_chars
@@ -107,7 +107,7 @@ class FileLoadingProgressBar(ProgressBar):
return memory
class OmeZarrExportProgressBar(ProgressBar):
- def __init__(self,path:str, n_chunks:int, reapeat_time="auto"):
+ def __init__(self,path: str, n_chunks: int, reapeat_time: str = "auto"):
"""
Context manager to track the exporting of OmeZarr files.
@@ -152,7 +152,7 @@ class OmeZarrExportProgressBar(ProgressBar):
self.last_update = 0
def get_new_update(self):
- def file_count(folder_path:str):
+ def file_count(folder_path: str) -> int:
"""
Goes recursively through the folders and counts how many files are there,
Doesn't count metadata json files
diff --git a/qim3d/utils/_server.py b/qim3d/utils/_server.py
index 9d20fccd..e4a46673 100644
--- a/qim3d/utils/_server.py
+++ b/qim3d/utils/_server.py
@@ -14,7 +14,7 @@ class CustomHTTPRequestHandler(SimpleHTTPRequestHandler):
self.send_header("Access-Control-Allow-Headers", "X-Requested-With, Content-Type")
super().end_headers()
- def list_directory(self, path):
+ def list_directory(self, path: str):
"""Helper to produce a directory listing, includes hidden files."""
try:
file_list = os.listdir(path)
@@ -49,7 +49,7 @@ class CustomHTTPRequestHandler(SimpleHTTPRequestHandler):
# Write the encoded HTML directly to the response
self.wfile.write(encoded)
-def start_http_server(directory, port=8000):
+def start_http_server(directory: str, port: int = 8000) -> HTTPServer:
"""
Starts an HTTP server serving the specified directory on the given port with CORS enabled.
diff --git a/qim3d/utils/_system.py b/qim3d/utils/_system.py
index 19792627..ccccb672 100644
--- a/qim3d/utils/_system.py
+++ b/qim3d/utils/_system.py
@@ -36,7 +36,7 @@ class Memory:
round(self.free_pct, 1),
)
-def _test_disk_speed(file_size_bytes=1024, ntimes=10):
+def _test_disk_speed(file_size_bytes: int = 1024, ntimes: int =10) -> tuple[float, float, float, float]:
'''
Test the write and read speed of the disk by writing a file of a given size
and then reading it back.
@@ -95,7 +95,7 @@ def _test_disk_speed(file_size_bytes=1024, ntimes=10):
return avg_write_speed, write_speed_std, avg_read_speed, read_speed_std
-def disk_report(file_size=1024 * 1024 * 100, ntimes=10):
+def disk_report(file_size: int = 1024 * 1024 * 100, ntimes: int = 10) -> None:
'''
Report the average write and read speed of the disk.
diff --git a/qim3d/viz/_cc.py b/qim3d/viz/_cc.py
index 1c0ed560..14ecf1f4 100644
--- a/qim3d/viz/_cc.py
+++ b/qim3d/viz/_cc.py
@@ -2,15 +2,15 @@ import matplotlib.pyplot as plt
import numpy as np
import qim3d
from qim3d.utils._logger import log
-
+from segmentation._connected_components import CC
def plot_cc(
- connected_components,
+ connected_components: CC,
component_indexs: list | tuple = None,
- max_cc_to_plot=32,
- overlay=None,
- crop=False,
- show=True,
+ max_cc_to_plot: int = 32,
+ overlay: np.ndarray = None,
+ crop: bool = False,
+ show: bool = True,
cmap: str = "viridis",
vmin: float = None,
vmax: float = None,
diff --git a/qim3d/viz/_data_exploration.py b/qim3d/viz/_data_exploration.py
index 2198cd94..766aae15 100644
--- a/qim3d/viz/_data_exploration.py
+++ b/qim3d/viz/_data_exploration.py
@@ -9,7 +9,9 @@ from typing import List, Optional, Union
import dask.array as da
import ipywidgets as widgets
+import matplotlib.figure
import matplotlib.pyplot as plt
+import matplotlib
from IPython.display import SVG, display
import matplotlib
import numpy as np
@@ -29,7 +31,7 @@ def slices_grid(
color_map: str = "magma",
value_min: float = None,
value_max: float = None,
- image_size=None,
+ image_size: int = None,
image_height: int = 2,
image_width: int = 2,
display_figure: bool = False,
@@ -38,7 +40,7 @@ def slices_grid(
color_bar: bool = False,
color_bar_style: str = "small",
**matplotlib_imshow_kwargs,
-) -> plt.Figure:
+) -> matplotlib.figure.Figure:
"""Displays one or several slices from a 3d volume.
By default if `slice_positions` is None, slices_grid plots `num_slices` linearly spaced slices.
@@ -296,7 +298,7 @@ def slices_grid(
return fig
-def _get_slice_range(position: int, num_slices: int, n_total):
+def _get_slice_range(position: int, num_slices: int, n_total) -> np.ndarray:
"""Helper function for `slices`. Returns the range of slices to be displayed around the given position."""
start_idx = position - num_slices // 2
end_idx = (
@@ -324,7 +326,7 @@ def slicer(
image_width: int = 3,
display_positions: bool = False,
interpolation: Optional[str] = None,
- image_size=None,
+ image_size: int = None,
color_bar: bool = False,
**matplotlib_imshow_kwargs,
) -> widgets.interactive:
@@ -401,8 +403,8 @@ def slicer_orthogonal(
image_width: int = 3,
display_positions: bool = False,
interpolation: Optional[str] = None,
- image_size=None,
-):
+ image_size: int = None,
+)-> widgets.interactive:
"""Interactive widget for visualizing orthogonal slices of a 3D volume.
Args:
@@ -461,7 +463,7 @@ def fade_mask(
color_map: str = "magma",
value_min: float = None,
value_max: float = None,
-):
+)-> widgets.interactive:
"""Interactive widget for visualizing the effect of edge fading on a 3D volume.
This can be used to select the best parameters before applying the mask.
@@ -596,7 +598,7 @@ def fade_mask(
return slicer_obj
-def chunks(zarr_path: str, **kwargs):
+def chunks(zarr_path: str, **kwargs)-> widgets.interactive:
"""
Function to visualize chunks of a Zarr dataset using the specified visualization method.
@@ -861,7 +863,7 @@ def histogram(
return_fig=False,
show=True,
**sns_kwargs,
-):
+) -> Optional[matplotlib.figure.Figure]:
"""
Plots a histogram of voxel intensities from a 3D volume, with options to show a specific slice or the entire volume.
diff --git a/qim3d/viz/_detection.py b/qim3d/viz/_detection.py
index a0926105..b4ab9098 100644
--- a/qim3d/viz/_detection.py
+++ b/qim3d/viz/_detection.py
@@ -6,7 +6,7 @@ from IPython.display import clear_output, display
import qim3d
-def circles(blobs, vol, alpha=0.5, color="#ff9900", **kwargs):
+def circles(blobs: np.ndarray, vol: np.ndarray, alpha: float = 0.5, color: str = "#ff9900", **kwargs)-> widgets.interactive:
"""
Plots the blobs found on a slice of the volume.
diff --git a/qim3d/viz/_k3d.py b/qim3d/viz/_k3d.py
index b80e9556..8b2c23ac 100644
--- a/qim3d/viz/_k3d.py
+++ b/qim3d/viz/_k3d.py
@@ -15,18 +15,18 @@ from qim3d.utils._misc import downscale_img, scale_to_float16
def volumetric(
- img,
- aspectmode="data",
- show=True,
- save=False,
- grid_visible=False,
- color_map='magma',
- constant_opacity=False,
- vmin=None,
- vmax=None,
- samples="auto",
- max_voxels=512**3,
- data_type="scaled_float16",
+ img: np.ndarray,
+ aspectmode: str = "data",
+ show: bool = True,
+ save: bool = False,
+ grid_visible: bool = False,
+ color_map: str = 'magma',
+ constant_opacity: bool = False,
+ vmin: float = None,
+ vmax: float = None,
+ samples: int|str = "auto",
+ max_voxels: int = 512**3,
+ data_type: str = "scaled_float16",
**kwargs,
):
"""
@@ -175,13 +175,13 @@ def volumetric(
def mesh(
- verts,
- faces,
- wireframe=True,
- flat_shading=True,
- grid_visible=False,
- show=True,
- save=False,
+ verts: np.ndarray,
+ faces: np.ndarray,
+ wireframe: bool = True,
+ flat_shading: bool = True,
+ grid_visible: bool = False,
+ show: bool = True,
+ save: bool = False,
**kwargs,
):
"""
diff --git a/qim3d/viz/_layers2d.py b/qim3d/viz/_layers2d.py
index 1e284461..676845a5 100644
--- a/qim3d/viz/_layers2d.py
+++ b/qim3d/viz/_layers2d.py
@@ -8,7 +8,7 @@ import numpy as np
from PIL import Image
-def image_with_lines(image:np.ndarray, lines: list, line_thickness:float|int) -> Image:
+def image_with_lines(image: np.ndarray, lines: list, line_thickness: float) -> Image:
"""
Plots the image and plots the lines on top of it. Then extracts it as PIL.Image and in the same size as the input image was.
Paramters:
diff --git a/qim3d/viz/_metrics.py b/qim3d/viz/_metrics.py
index 53a7f3a6..ded37d24 100644
--- a/qim3d/viz/_metrics.py
+++ b/qim3d/viz/_metrics.py
@@ -1,19 +1,21 @@
"""Visualization tools"""
+import matplotlib.figure
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
from matplotlib import colormaps
from qim3d.utils._logger import log
-
+import torch
+import matplotlib
def plot_metrics(
- *metrics,
- linestyle="-",
- batch_linestyle="dotted",
+ *metrics: tuple[dict[str, float]],
+ linestyle: str = "-",
+ batch_linestyle: str = "dotted",
labels: list = None,
figsize: tuple = (16, 6),
- show=False
+ show: bool = False
):
"""
Plots the metrics over epochs and batches.
@@ -79,8 +81,13 @@ def plot_metrics(
def grid_overview(
- data, num_images=7, cmap_im="gray", cmap_segm="viridis", alpha=0.5, show=False
-):
+ data: list|torch.utils.data.Dataset,
+ num_images: int = 7,
+ cmap_im: str = "gray",
+ cmap_segm: str = "viridis",
+ alpha: float = 0.5,
+ show: bool = False
+)-> matplotlib.figure.Figure:
"""Displays an overview grid of images, labels, and masks (if they exist).
Labels are the annotated target segmentations
@@ -174,13 +181,13 @@ def grid_overview(
def grid_pred(
- in_targ_preds,
- num_images=7,
- cmap_im="gray",
- cmap_segm="viridis",
- alpha=0.5,
- show=False,
-):
+ in_targ_preds: tuple[np.ndarray, np.ndarray, np.ndarray],
+ num_images: int = 7,
+ cmap_im: str = "gray",
+ cmap_segm: str = "viridis",
+ alpha: float = 0.5,
+ show: bool = False,
+)-> matplotlib.figure.Figure:
"""Displays a grid of input images, predicted segmentations, ground truth segmentations, and their comparison.
Displays a grid of subplots representing different aspects of the input images and segmentations.
@@ -282,7 +289,7 @@ def grid_pred(
return fig
-def vol_masked(vol, vol_mask, viz_delta=128):
+def vol_masked(vol: np.ndarray, vol_mask: np.ndarray, viz_delta: int=128) -> np.ndarray:
"""
Applies masking to a volume based on a binary volume mask.
--
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