refactor: 🛠️ update type hints to use built-in types in VLM and validation functions
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@ -53,3 +53,11 @@ repos:
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- id: codespell
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additional_dependencies:
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- tomli
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- repo: https://github.com/asottile/pyupgrade
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rev: v3.20.0
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hooks:
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- id: pyupgrade
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args: ["--py39-plus"]
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additional_dependencies:
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- tomli
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@ -118,7 +118,7 @@ def from_paligemma(
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Args:
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result: String containing paligemma-formatted locations and labels.
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resolution_wh: Tuple (width, height) to which we scale the box coordinates.
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resolution_wh: tuple (width, height) to which we scale the box coordinates.
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classes: Optional list of valid class names. If provided, boxes and labels not
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in this list are filtered out.
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@ -423,9 +423,9 @@ def from_google_gemini_2_0(
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def from_google_gemini_2_5(
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result: str,
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resolution_wh: Tuple[int, int],
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classes: Optional[List[str]] = None,
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) -> Tuple[
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resolution_wh: tuple[int, int],
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classes: Optional[list[str]] = None,
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) -> tuple[
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np.ndarray,
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Optional[np.ndarray],
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np.ndarray,
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@ -1,4 +1,5 @@
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from typing import Any
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import numpy as np
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@ -139,7 +140,7 @@ def validate_keypoints_fields(
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validate_data(data, n)
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def validate_resolution(resolution: Any) -> Tuple[int, int]:
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def validate_resolution(resolution: Any) -> tuple[int, int]:
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if not (isinstance(resolution, tuple) and len(resolution) == 2):
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raise ValueError(
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f"""
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@ -1080,10 +1080,10 @@ def test_florence_2(
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def test_from_google_gemini_2_5(
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exception,
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result: str,
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resolution_wh: Tuple[int, int],
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classes: Optional[List[str]],
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resolution_wh: tuple[int, int],
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classes: Optional[list[str]],
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expected_results: Optional[
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Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray]
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tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray]
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],
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):
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with exception:
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