manually fixed some ruff issues

v7labs · Oct 17, 2023 · 081f249 · 081f249
1 parent ba78fe1
commit 081f249
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Showing 3 changed files with 6 additions and 7 deletions.
diff --git a/darwin/dataset/local_dataset.py b/darwin/dataset/local_dataset.py
@@ -3,7 +3,6 @@
 from typing import Any, Dict, Iterator, List, Optional, Tuple
 
 import numpy as np
-import orjson as json
 from PIL import Image as PILImage
 
 from darwin.dataset.utils import get_classes, get_release_path, load_pil_image

diff --git a/darwin/dataset/split_manager.py b/darwin/dataset/split_manager.py
@@ -294,8 +294,8 @@ def _stratify_samples(
     # Extract entries whose support set is 1 (it would make sklearn crash) and append the to train later
     unique_labels, count = np.unique(labels, return_counts=True)
     single_files = []
-    for l in unique_labels[count == 1]:
-        index = np.where(labels == l)[0][0]
+    for label in unique_labels[count == 1]:
+        index = np.where(labels == label)[0][0]
         single_files.append(file_indices[index])
         labels = np.delete(labels, index)
         file_indices = np.delete(file_indices, index)

diff --git a/tests/darwin/torch/dataset_test.py b/tests/darwin/torch/dataset_test.py
@@ -49,7 +49,7 @@ def test_should_correctly_create_a_instance_seg_dataset(self, team_slug: str, te
         ds = InstanceSegmentationDataset(dataset_path=root, release_name="latest")
 
         generic_dataset_test(ds, n=20, size=(50, 50))
-        assert type(ds[0][1]) is dict
+        assert isinstance(ds[0][1], dict)
 
 
 class TestSemanticSegmentationDataset:
@@ -58,7 +58,7 @@ def test_should_correctly_create_a_semantic_seg_dataset(self, team_slug: str, te
         ds = SemanticSegmentationDataset(dataset_path=root, release_name="latest")
 
         generic_dataset_test(ds, n=20, size=(50, 50))
-        assert type(ds[0][1]) is dict
+        assert isinstance(ds[0][1], dict)
 
 
 class TestObjectDetectionDataset:
@@ -67,7 +67,7 @@ def test_should_correctly_create_a_object_detection_dataset(self, team_slug: str
         ds = ObjectDetectionDataset(dataset_path=root, release_name="latest")
 
         generic_dataset_test(ds, n=20, size=(50, 50))
-        assert type(ds[0][1]) is dict
+        assert isinstance(ds[0][1], dict)
         img, target = ds[0]
 
         for bbox in target["boxes"]:
@@ -251,7 +251,7 @@ def test_loads_semantic_segmentation_dataset_from_polygon_annotations(
         label = {k: _maybe_tensor_to_list(v) for k, v in label.items()}
 
         assert label["image_id"] == [0]
-        assert type(label["mask"][0]) == list
+        assert isinstance(label["mask"][0], list)
         assert label["height"] == 50
         assert label["width"] == 50