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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43 changed files with 146 additions and 141 deletions
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@ -15,7 +15,7 @@ from ultralytics.data.augment import Format
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from ultralytics.data.dataset import YOLODataset
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from ultralytics.data.utils import check_det_dataset
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from ultralytics.models.yolo.model import YOLO
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from ultralytics.utils import LOGGER, IterableSimpleNamespace, checks, USER_CONFIG_DIR
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from ultralytics.utils import LOGGER, USER_CONFIG_DIR, IterableSimpleNamespace, checks
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from .utils import get_sim_index_schema, get_table_schema, plot_query_result, prompt_sql_query, sanitize_batch
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@ -203,7 +203,8 @@ class Explorer:
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table = self.table.to_arrow() # noqa NOTE: Don't comment this. This line is used by DuckDB
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if not query.startswith("SELECT") and not query.startswith("WHERE"):
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raise ValueError(
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f"Query must start with SELECT or WHERE. You can either pass the entire query or just the WHERE clause. found {query}"
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f"Query must start with SELECT or WHERE. You can either pass the entire query or just the WHERE "
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f"clause. found {query}"
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)
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if query.startswith("WHERE"):
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query = f"SELECT * FROM 'table' {query}"
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@ -318,13 +319,13 @@ class Explorer:
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Args:
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max_dist (float): maximum L2 distance between the embeddings to consider. Defaults to 0.2.
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top_k (float): Percentage of the closest data points to consider when counting. Used to apply limit when running
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top_k (float): Percentage of the closest data points to consider when counting. Used to apply limit.
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vector search. Defaults: None.
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force (bool): Whether to overwrite the existing similarity index or not. Defaults to True.
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Returns:
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(pandas.DataFrame): A dataframe containing the similarity index. Each row corresponds to an image, and columns
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include indices of similar images and their respective distances.
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(pandas.DataFrame): A dataframe containing the similarity index. Each row corresponds to an image,
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and columns include indices of similar images and their respective distances.
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Example:
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```python
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