minor format fixes

src/data_gradients/config/detection.yaml

@@ -18,7 +18,7 @@ report_sections:
       - DetectionBoundingBoxArea
       - DetectionBoundingBoxPerImageCount
       - DetectionBoundingBoxSize
-      - DetectionClassesCount
+      - DetectionObjectsPerClass
       - DetectionClassesPerImageCount
       - DetectionBoundingBoxIoU:
           num_bins: 10

src/data_gradients/feature_extractors/__init__.py

@@ -19,7 +19,7 @@
     DetectionBoundingBoxArea,
     DetectionBoundingBoxPerImageCount,
     DetectionBoundingBoxSize,
-    DetectionClassesCount,
+    DetectionObjectsPerClass,
     DetectionClassHeatmap,
     DetectionClassesPerImageCount,
     DetectionSampleVisualization,
@@ -43,7 +43,7 @@
     "DetectionBoundingBoxArea",
     "DetectionBoundingBoxPerImageCount",
     "DetectionBoundingBoxSize",
-    "DetectionClassesCount",
+    "DetectionObjectsPerClass",
     "DetectionClassHeatmap",
     "DetectionClassesPerImageCount",
     "DetectionSampleVisualization",

src/data_gradients/feature_extractors/common/summary.py

@@ -92,7 +92,7 @@ def aggregate(self) -> Feature:
             index_of_med = np.argsort(areas)[len(areas) // 2]
             basic_stats.med_image_resolution = self.format_resolution(basic_stats.images_resolutions[index_of_med][0])
 
-            basic_stats.annotations_per_image = basic_stats.annotation_count / basic_stats.image_count
+            basic_stats.annotations_per_image = f"{basic_stats.annotation_count / basic_stats.image_count:.2f}"
             basic_stats.image_count = f"{basic_stats.image_count:,}"
             basic_stats.annotation_count = f"{basic_stats.annotation_count:,}"
 

src/data_gradients/feature_extractors/object_detection/__init__.py

@@ -1,7 +1,7 @@
 from .bounding_boxes_area import DetectionBoundingBoxArea
 from .bounding_boxes_per_image_count import DetectionBoundingBoxPerImageCount
 from .bounding_boxes_resolution import DetectionBoundingBoxSize
-from .classes_count import DetectionClassesCount
+from .classes_count import DetectionObjectsPerClass
 from .classes_heatmap_per_class import DetectionClassHeatmap
 from .classes_per_image_count import DetectionClassesPerImageCount
 from .sample_visualization import DetectionSampleVisualization
@@ -11,7 +11,7 @@
     "DetectionBoundingBoxArea",
     "DetectionBoundingBoxPerImageCount",
     "DetectionBoundingBoxSize",
-    "DetectionClassesCount",
+    "DetectionObjectsPerClass",
     "DetectionClassHeatmap",
     "DetectionClassesPerImageCount",
     "DetectionSampleVisualization",

src/data_gradients/feature_extractors/object_detection/classes_count.py

@@ -8,7 +8,7 @@
 
 
 @register_feature_extractor()
-class DetectionClassesCount(AbstractFeatureExtractor):
+class DetectionObjectsPerClass(AbstractFeatureExtractor):
     """Feature Extractor to count the number of instance of each class."""
 
     def __init__(self):
@@ -33,7 +33,7 @@ def aggregate(self) -> Feature:
 
         plot_options = BarPlotOptions(
             x_label_key="n_appearance",
-            x_label_name="Number of Appearance",
+            x_label_name="Objects per class",
             y_label_key="class_name",
             y_label_name="Class Names",
             order_key="class_id",
@@ -57,7 +57,7 @@ def aggregate(self) -> Feature:
 
     @property
     def title(self) -> str:
-        return "Number of classes."
+        return "Objects Per Class"
 
     @property
     def description(self) -> str:

src/data_gradients/managers/abstract_manager.py

@@ -6,7 +6,7 @@
 from itertools import zip_longest
 from logging import getLogger
 from datetime import datetime
-import tqdm
+from tqdm import tqdm
 
 from data_gradients.feature_extractors import AbstractFeatureExtractor
 from data_gradients.batch_processors.base import BatchProcessor
@@ -104,7 +104,7 @@ def execute(self):
             f"  - feature extractor list: {self.grouped_feature_extractors}"
         )
 
-        datasets_tqdm = tqdm.tqdm(
+        datasets_tqdm = tqdm(
             zip_longest(self.train_iter, self.val_iter, fillvalue=None),
             desc="Analyzing... ",
             total=self.n_batches,
@@ -149,7 +149,7 @@ def post_process(self, interrupted=False):
         images_created = []
 
         summary = ResultsContainer()
-        for section_name, feature_extractors in self.grouped_feature_extractors.items():
+        for section_name, feature_extractors in tqdm(self.grouped_feature_extractors.items(), desc="Summing... "):
             section = Section(section_name)
             for feature_extractor in feature_extractors:
                 try:
@@ -166,9 +166,9 @@ def post_process(self, interrupted=False):
                     )
 
                 if f is not None:
-                    image_name = feature_extractor.__class__.__name__ + ".svg"
+                    image_name = feature_extractor.__class__.__name__ + ".png"
                     image_path = os.path.join(self.archive_dir, image_name)
-                    f.savefig(image_path, dpi=1200)
+                    f.savefig(image_path, dpi=300)
                     images_created.append(image_path)
                 else:
                     image_path = None

tests/manual_tests/detection_super_gradients_test.py

@@ -7,7 +7,7 @@
 from data_gradients.feature_extractors.common.image_color_distribution import ImageColorDistribution
 from data_gradients.feature_extractors.object_detection.bounding_boxes_area import DetectionBoundingBoxArea
 from data_gradients.feature_extractors.object_detection.bounding_boxes_resolution import DetectionBoundingBoxSize
-from data_gradients.feature_extractors.object_detection.classes_count import DetectionClassesCount
+from data_gradients.feature_extractors.object_detection.classes_count import DetectionObjectsPerClass
 from data_gradients.feature_extractors.object_detection.classes_per_image_count import DetectionClassesPerImageCount
 from data_gradients.feature_extractors.object_detection.bounding_boxes_per_image_count import DetectionBoundingBoxPerImageCount
 
@@ -66,7 +66,7 @@ def __call__(self, sample):
     DetectionBoundingBoxPerImageCount(),
     DetectionBoundingBoxArea(),
     DetectionBoundingBoxSize(),
-    DetectionClassesCount(),
+    DetectionObjectsPerClass(),
     DetectionClassesPerImageCount(),
 ]