ultralytics 8.1.44 add IS_RASPBERRYPI and constants refactor (#9827)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

ultralytics/data/__init__.py

@@ -1,19 +1,14 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
 from .base import BaseDataset
-from .build import (
-    build_dataloader,
-    build_yolo_dataset,
-    build_grounding,
-    load_inference_source,
-)
+from .build import build_dataloader, build_grounding, build_yolo_dataset, load_inference_source
 from .dataset import (
     ClassificationDataset,
+    GroundingDataset,
     SemanticDataset,
+    YOLOConcatDataset,
     YOLODataset,
     YOLOMultiModalDataset,
-    GroundingDataset,
-    YOLOConcatDataset,
 )
 
 __all__ = (

ultralytics/data/augment.py

@@ -20,7 +20,7 @@ from .utils import polygons2masks, polygons2masks_overlap
 
 DEFAULT_MEAN = (0.0, 0.0, 0.0)
 DEFAULT_STD = (1.0, 1.0, 1.0)
-DEFAULT_CROP_FTACTION = 1.0
+DEFAULT_CROP_FRACTION = 1.0
 
 
 # TODO: we might need a BaseTransform to make all these augments be compatible with both classification and semantic
@@ -1134,7 +1134,7 @@ def classify_transforms(
     mean=DEFAULT_MEAN,
     std=DEFAULT_STD,
     interpolation=Image.BILINEAR,
-    crop_fraction: float = DEFAULT_CROP_FTACTION,
+    crop_fraction: float = DEFAULT_CROP_FRACTION,
 ):
     """
     Classification transforms for evaluation/inference. Inspired by timm/data/transforms_factory.py.

ultralytics/data/base.py

@@ -15,7 +15,7 @@ import psutil
 from torch.utils.data import Dataset
 
 from ultralytics.utils import DEFAULT_CFG, LOCAL_RANK, LOGGER, NUM_THREADS, TQDM
-from .utils import HELP_URL, FORMATS_HELP_MSG, IMG_FORMATS
+from .utils import FORMATS_HELP_MSG, HELP_URL, IMG_FORMATS
 
 
 class BaseDataset(Dataset):

ultralytics/data/build.py

@@ -22,7 +22,7 @@ from ultralytics.data.loaders import (
 from ultralytics.data.utils import IMG_FORMATS, VID_FORMATS
 from ultralytics.utils import RANK, colorstr
 from ultralytics.utils.checks import check_file
-from .dataset import YOLODataset, YOLOMultiModalDataset, GroundingDataset
+from .dataset import GroundingDataset, YOLODataset, YOLOMultiModalDataset
 from .utils import PIN_MEMORY
 
 

ultralytics/data/converter.py

@@ -519,12 +519,13 @@ def yolo_bbox2segment(im_dir, save_dir=None, sam_model="sam_b.pt"):
                 ├─ ..
                 └─ NNN.txt
     """
-    from ultralytics.data import YOLODataset
-    from ultralytics.utils.ops import xywh2xyxy
-    from ultralytics.utils import LOGGER
-    from ultralytics import SAM
     from tqdm import tqdm
 
+    from ultralytics import SAM
+    from ultralytics.data import YOLODataset
+    from ultralytics.utils import LOGGER
+    from ultralytics.utils.ops import xywh2xyxy
+
     # NOTE: add placeholder to pass class index check
     dataset = YOLODataset(im_dir, data=dict(names=list(range(1000))))
     if len(dataset.labels[0]["segments"]) > 0:  # if it's segment data

ultralytics/data/dataset.py

@@ -30,10 +30,10 @@ from .utils import (
     LOGGER,
     get_hash,
     img2label_paths,
-    verify_image,
-    verify_image_label,
     load_dataset_cache_file,
     save_dataset_cache_file,
+    verify_image,
+    verify_image_label,
 )
 
 # Ultralytics dataset *.cache version, >= 1.0.0 for YOLOv8

ultralytics/data/explorer/explorer.py

@@ -15,7 +15,7 @@ from ultralytics.data.augment import Format
 from ultralytics.data.dataset import YOLODataset
 from ultralytics.data.utils import check_det_dataset
 from ultralytics.models.yolo.model import YOLO
-from ultralytics.utils import LOGGER, IterableSimpleNamespace, checks, USER_CONFIG_DIR
+from ultralytics.utils import LOGGER, USER_CONFIG_DIR, IterableSimpleNamespace, checks
 from .utils import get_sim_index_schema, get_table_schema, plot_query_result, prompt_sql_query, sanitize_batch
 
 
@@ -203,7 +203,8 @@ class Explorer:
         table = self.table.to_arrow()  # noqa NOTE: Don't comment this. This line is used by DuckDB
         if not query.startswith("SELECT") and not query.startswith("WHERE"):
             raise ValueError(
-                f"Query must start with SELECT or WHERE. You can either pass the entire query or just the WHERE clause. found {query}"
+                f"Query must start with SELECT or WHERE. You can either pass the entire query or just the WHERE "
+                f"clause. found {query}"
             )
         if query.startswith("WHERE"):
             query = f"SELECT * FROM 'table' {query}"
@@ -318,13 +319,13 @@ class Explorer:
 
         Args:
             max_dist (float): maximum L2 distance between the embeddings to consider. Defaults to 0.2.
-            top_k (float): Percentage of the closest data points to consider when counting. Used to apply limit when running
+            top_k (float): Percentage of the closest data points to consider when counting. Used to apply limit.
                            vector search. Defaults: None.
             force (bool): Whether to overwrite the existing similarity index or not. Defaults to True.
 
         Returns:
-            (pandas.DataFrame): A dataframe containing the similarity index. Each row corresponds to an image, and columns
-                                include indices of similar images and their respective distances.
+            (pandas.DataFrame): A dataframe containing the similarity index. Each row corresponds to an image,
+                and columns include indices of similar images and their respective distances.
 
         Example:
             ```python

ultralytics/data/loaders.py

@@ -15,8 +15,8 @@ import requests
 import torch
 from PIL import Image
 
-from ultralytics.data.utils import IMG_FORMATS, VID_FORMATS, FORMATS_HELP_MSG
-from ultralytics.utils import LOGGER, is_colab, is_kaggle, ops
+from ultralytics.data.utils import FORMATS_HELP_MSG, IMG_FORMATS, VID_FORMATS
+from ultralytics.utils import IS_COLAB, IS_KAGGLE, LOGGER, ops
 from ultralytics.utils.checks import check_requirements
 
 
@@ -87,7 +87,7 @@ class LoadStreams:
                 # YouTube format i.e. 'https://www.youtube.com/watch?v=Zgi9g1ksQHc' or 'https://youtu.be/LNwODJXcvt4'
                 s = get_best_youtube_url(s)
             s = eval(s) if s.isnumeric() else s  # i.e. s = '0' local webcam
-            if s == 0 and (is_colab() or is_kaggle()):
+            if s == 0 and (IS_COLAB or IS_KAGGLE):
                 raise NotImplementedError(
                     "'source=0' webcam not supported in Colab and Kaggle notebooks. "
                     "Try running 'source=0' in a local environment."

ultralytics/data/utils.py

@@ -27,9 +27,9 @@ from ultralytics.utils import (
     clean_url,
     colorstr,
     emojis,
+    is_dir_writeable,
     yaml_load,
     yaml_save,
-    is_dir_writeable,
 )
 from ultralytics.utils.checks import check_file, check_font, is_ascii
 from ultralytics.utils.downloads import download, safe_download, unzip_file