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>
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Glenn Jocher 2024-04-07 00:47:12 +02:00 committed by GitHub
parent 3f34a7c3af
commit 7d891a4aa4
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43 changed files with 146 additions and 141 deletions

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@ -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