Merge remote-tracking branch 'origin/main' into experimental/nalgebra

.github/workflows/codespeed.yml

@@ -40,7 +40,7 @@ jobs:
         run: cd powerboxesrs && cargo codspeed build
 
       - name: Run benchmarks
-        uses: CodSpeedHQ/action@v1
+        uses: CodSpeedHQ/action@v2
         with:
           token: ${{ secrets.CODSPEED_TOKEN }}
           run: pytest bindings/tests/ --codspeed && cd powerboxesrs && cargo codspeed run

bindings/pyproject.toml

@@ -28,7 +28,7 @@ description = "Utility functions to manipulate and compute metrics on boxes"
 homepage = "https://smirkey.github.io/powerboxes/"
 documentation = "https://smirkey.github.io/powerboxes/"
 repository = "https://github.com/Smirkey/powerboxes"
-version = "0.2.2"
+version = "0.2.3"
 dependencies = ["numpy"]
 
 [tool.maturin]

bindings/python/powerboxes/__init__.py

@@ -37,7 +37,7 @@
     "uint32",
     "uint64",
 ]
-__version__ = "0.2.2"
+__version__ = "0.2.3"
 
 T = TypeVar(
     "T",
@@ -136,7 +136,7 @@ def parallel_iou_distance(
         raise TypeError(_BOXES_NOT_NP_ARRAY)
     if boxes1.dtype == boxes2.dtype:
         try:
-            return _dtype_to_func_parallel_iou_distance[boxes1.dtype](boxes1, boxes2)
+            return _dtype_to_func_parallel_iou_distance[boxes1.dtype](boxes1, boxes2) # type: ignore
         except KeyError:
             raise TypeError(
                 f"Box dtype: {boxes1.dtype} not in supported dtypes {supported_dtypes}"
@@ -167,7 +167,7 @@ def parallel_giou_distance(
         raise TypeError(_BOXES_NOT_NP_ARRAY)
     if boxes1.dtype == boxes2.dtype:
         try:
-            return _dtype_to_func_parallel_giou_distance[boxes1.dtype](boxes1, boxes2)
+            return _dtype_to_func_parallel_giou_distance[boxes1.dtype](boxes1, boxes2) # type: ignore
         except KeyError:
             raise TypeError(
                 f"Box dtype: {boxes1.dtype} not in supported dtypes {supported_dtypes}"
@@ -198,7 +198,7 @@ def giou_distance(
         raise TypeError(_BOXES_NOT_NP_ARRAY)
     if boxes1.dtype == boxes2.dtype:
         try:
-            return _dtype_to_func_giou_distance[boxes1.dtype](boxes1, boxes2)
+            return _dtype_to_func_giou_distance[boxes1.dtype](boxes1, boxes2) # type: ignore
         except KeyError:
             raise TypeError(
                 f"Box dtype: {boxes1.dtype} not in supported dtypes {supported_dtypes}"
@@ -229,7 +229,7 @@ def tiou_distance(
         raise TypeError(_BOXES_NOT_NP_ARRAY)
     if boxes1.dtype == boxes2.dtype:
         try:
-            return _dtype_to_func_tiou_distance[boxes1.dtype](boxes1, boxes2)
+            return _dtype_to_func_tiou_distance[boxes1.dtype](boxes1, boxes2) # type: ignore
         except KeyError:
             raise TypeError(
                 f"Box dtype: {boxes1.dtype} not in supported dtypes {supported_dtypes}"
@@ -346,7 +346,7 @@ def remove_small_boxes(boxes: npt.NDArray[T], min_size: float) -> npt.NDArray[T]
     if not isinstance(boxes, np.ndarray):
         raise TypeError(_BOXES_NOT_NP_ARRAY)
     try:
-        return _dtype_to_func_remove_small_boxes[boxes.dtype](boxes, min_size)
+        return _dtype_to_func_remove_small_boxes[boxes.dtype](boxes, min_size) # type: ignore
     except KeyError:
         raise TypeError(
             f"Box dtype: {boxes.dtype} not in supported dtypes {supported_dtypes}"
@@ -365,7 +365,7 @@ def boxes_areas(boxes: npt.NDArray[T]) -> npt.NDArray[np.float64]:
     if not isinstance(boxes, np.ndarray):
         raise TypeError(_BOXES_NOT_NP_ARRAY)
     try:
-        return _dtype_to_func_box_areas[boxes.dtype](boxes)
+        return _dtype_to_func_box_areas[boxes.dtype](boxes) # type: ignore
     except KeyError:
         raise TypeError(
             f"Box dtype: {boxes.dtype} not in supported dtypes {supported_dtypes}"
@@ -391,7 +391,7 @@ def box_convert(boxes: npt.NDArray[T], in_fmt: str, out_fmt: str) -> npt.NDArray
     if not isinstance(boxes, np.ndarray):
         raise TypeError(_BOXES_NOT_NP_ARRAY)
     try:
-        return _dtype_to_func_box_convert[boxes.dtype](boxes, in_fmt, out_fmt)
+        return _dtype_to_func_box_convert[boxes.dtype](boxes, in_fmt, out_fmt) # type: ignore
     except KeyError:
         raise TypeError(
             f"Box dtype: {boxes.dtype} not in supported dtypes {supported_dtypes}"
@@ -438,7 +438,7 @@ def nms(
     if not isinstance(boxes, np.ndarray) or not isinstance(scores, np.ndarray):
         raise TypeError("Boxes and scores must be numpy arrays")
     try:
-        return _dtype_to_func_nms[boxes.dtype](
+        return _dtype_to_func_nms[boxes.dtype]( # type: ignore
             boxes, scores, iou_threshold, score_threshold
         )
     except KeyError:
@@ -473,7 +473,7 @@ def rtree_nms(
     if not isinstance(boxes, np.ndarray) or not isinstance(scores, np.ndarray):
         raise TypeError("Boxes and scores must be numpy arrays")
     try:
-        return _dtype_to_func_rtree_nms[boxes.dtype](
+        return _dtype_to_func_rtree_nms[boxes.dtype]( # type: ignore
             boxes, scores, iou_threshold, score_threshold
         )
     except KeyError:

bindings/tests/test_boxes.py

@@ -1,7 +1,8 @@
-from powerboxes import masks_to_boxes
-import numpy as np
 import os
+
+import numpy as np
 from PIL import Image
+from powerboxes import masks_to_boxes
 
 
 def test_masks_box():

powerboxesrs/src/lib.rs

@@ -11,7 +11,7 @@
 //!
 //! ```toml
 //! [dependencies]
-//! powerboxesrs = "0.2.2"
+//! powerboxesrs = "0.2.3"
 //! ```
 //!
 //! ## Usage
@@ -46,10 +46,10 @@
 //! - `rtree_nms`: Non-maximum suppression, returns the indices of the boxes to keep, uses a r-tree internally to avoid quadratic complexity, useful when having many boxes.
 //!
 pub mod boxes;
+pub mod diou;
 pub mod giou;
 pub mod iou;
 pub mod nms;
 pub mod rotation;
 pub mod tiou;
 mod utils;
-pub mod diou;

powerboxesrs/src/utils.rs

@@ -1,7 +1,6 @@
 use num_traits::{Num, ToPrimitive};
 use rstar::{RStarInsertionStrategy, RTreeNum, RTreeObject, RTreeParams, AABB};
 
-pub const EPS: f64 = 1e-16;
 pub const ONE: f64 = 1.0;
 pub const ZERO: f64 = 0.0;