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Merged
alanocallaghan merged 3 commits into from
Oct 20, 2025
Merged

Refactor classification code to handle multiple classifications #44

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bc78725
Refactor classification code to handle multiple classifications
alanocallaghan Oct 20, 2025
f880565
Apply suggestion from @alanocallaghan
alanocallaghan Oct 20, 2025
7a34137
Merge branch 'main' into handle-classifications
alanocallaghan Oct 20, 2025
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42 changes: 29 additions & 13 deletions qubalab/objects/classification.py
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Original file line number Diff line number Diff line change
@@ -1,21 +1,27 @@
from __future__ import annotations
import random
from typing import Optional
from typing import Optional, Union


class Classification(object):
"""
Simple class to store the name and color of a classification.
Simple class to store the names and color of a classification.
"""

_cached_classifications = {}

def __init__(self, name: str, color: Optional[tuple[int, int, int]] = None):
def __init__(
self,
names: Union[str, tuple[str]],
color: Optional[tuple[int, int, int]] = None,
):
"""
:param name: the name of the classification
:param names: the names of the classification
:param color: the RGB color (each component between 0 and 255) of the classification. Can be None to use a random color
"""
self._name = name
if isinstance(names, str):
names = (names,)
self._names = names
self._color = (
tuple(random.randint(0, 255) for _ in range(3)) if color is None else color
)
Expand All @@ -25,7 +31,14 @@ def name(self) -> str:
"""
The name of the classification.
"""
return self._name
return ": ".join(self._names)

@property
def names(self) -> tuple[str]:
"""
The name of the classification.
"""
return self._names

@property
def color(self) -> tuple[int, int, int]:
Expand All @@ -36,8 +49,9 @@ def color(self) -> tuple[int, int, int]:

@staticmethod
def get_cached_classification(
name: str, color: Optional[tuple[int, int, int]] = None
) -> Classification:
name: Optional[Union[str, tuple[str]]],
color: Optional[tuple[int, int, int]] = None,
) -> Optional[Classification]:
"""
Return a classification by looking at an internal cache.

Expand All @@ -57,23 +71,25 @@ def get_cached_classification(
"""
if name is None:
return None

if isinstance(name, str):
name = (name,)
name = ": ".join(name)
classification = Classification._cached_classifications.get(name)
if classification is None:
classification = Classification(name, color)
Classification._cached_classifications[classification.name] = classification
return classification

def __str__(self):
return f"Classification {self._name} of color {self._color}"
return f"Classification {self.name} of color {self.color}"

def __repr__(self):
return f"Classification('{self._name}', {self._color})"
return f"Classification('{self.name}', {self.color})"

def __eq__(self, other):
if isinstance(other, Classification):
return self._name == other._name and self._color == other._color
return self.name == other.name and self.color == other.color
return False

def __hash__(self):
return hash(self._name)
return hash(self.name)
12 changes: 8 additions & 4 deletions qubalab/objects/image_feature.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,12 +72,14 @@ def __init__(
if classification is not None:
if isinstance(classification, Classification):
props["classification"] = {
"name": classification.name,
"names": classification.names,
"color": classification.color,
}
else:
props["classification"] = {
"name": classification.get("name"),
"names": classification.get("names")
if "names" in classification.keys()
else (classification.get("name"),),
"color": classification.get("color"),
}
if name is not None:
Expand Down Expand Up @@ -169,7 +171,7 @@ def create_from_label_image(
connectivity: int = 4,
scale: float = 1.0,
include_labels=False,
classification_names: Union[str, dict[int, str]] = None,
classification_names: Optional[Union[str, dict[int, str]]] = None,
) -> list[ImageFeature]:
"""
Create a list of ImageFeatures from a binary or labeled image.
Expand Down Expand Up @@ -243,7 +245,9 @@ def classification(self) -> Classification:
"""
if "classification" in self.properties:
return Classification(
self.properties["classification"].get("name"),
self.properties["classification"].get("names")
if "names" in self.properties["classification"].keys()
else (self.properties["classification"].get("name"),),
self.properties["classification"].get("color"),
)
else:
Expand Down
35 changes: 32 additions & 3 deletions tests/objects/test_image_feature.py
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Original file line number Diff line number Diff line change
@@ -1,9 +1,12 @@
import geojson
import math
import numpy as np
from qubalab.objects.image_feature import ImageFeature
from qubalab.objects.classification import Classification
from qubalab.objects.object_type import ObjectType
from qubalab.objects import (
ObjectType,
ImageFeature,
Classification,
geojson_features_from_string,
)


def test_geometry():
Expand Down Expand Up @@ -685,3 +688,29 @@ def test_nucleus_geometry_when_set_after_creation():
nucleus_geometry = image_feature.nucleus_geometry

assert nucleus_geometry == expected_nucleus_geometry


def test_imagefeature_handles_classification_names():
string = """
{"type":"Feature","geometry":{"type":"Point","coordinates":[0,0]},"properties":{"objectType":"annotation","classification":{"names":["a","b"]}}}
"""
feature = geojson_features_from_string(string)
ifeature = ImageFeature.create_from_feature(feature)
assert (
ifeature.classification.names
== feature["properties"]["classification"]["names"]
)
assert ifeature.classification.name == ": ".join(
feature["properties"]["classification"]["names"]
)


def test_imagefeature_handles_classification_name():
string = """
{"type":"Feature","geometry":{"type":"Point","coordinates":[0,0]},"properties":{"objectType":"annotation","classification":{"names":["a","b"]}}}
"""
feature = geojson_features_from_string(string)
ifeature = ImageFeature.create_from_feature(feature)
assert ifeature.classification.name == ": ".join(
feature["properties"]["classification"]["names"]
)