feat: pre commit for the repo

.github/workflows/doc.yml

@@ -1,8 +1,8 @@
-name: doc 
+name: doc
 on:
   push:
     branches:
-      - master 
+      - master
       - main
 permissions:
   contents: write
@@ -18,12 +18,12 @@ jobs:
       - uses: actions/setup-python@v4
         with:
           python-version: 3.12
-      - run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV 
+      - run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV
       - uses: actions/cache@v3
         with:
           key: mkdocs-material-${{ env.cache_id }}
           path: .cache
           restore-keys: |
             mkdocs-material-
       - run: pip install -r bindings/docs/requirements-doc.txt && pip install bindings/.
-      - run: cd bindings && mkdocs gh-deploy --force
+      - run: cd bindings && mkdocs gh-deploy --force

.pre-commit-config.yaml

@@ -0,0 +1,19 @@
+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+- repo: https://github.com/pre-commit/pre-commit-hooks
+  rev: v4.5.0
+  hooks:
+  - id: trailing-whitespace
+  - id: end-of-file-fixer
+  - id: check-json
+  - id: detect-private-key
+  - id: debug-statements
+
+- repo: https://github.com/charliermarsh/ruff-pre-commit
+  # Ruff version.
+  rev: 'v0.2.2'
+  hooks:
+    - id: ruff
+      args: [--fix, --exit-non-zero-on-fix]
+    - id: ruff-format

README.md

@@ -13,7 +13,7 @@ It shows a significant speedup over the equivalent numpy implementations in Pyth
 **🦀 Rust [documentation](https://docs.rs/powerboxesrs)**
 
 
-**🐍 Python [documentation]("https://smirkey.github.io/powerboxes/")**
+**🐍 Python [documentation](https://smirkey.github.io/powerboxes/)**
 
 ## Installation
 

bindings/README.md

@@ -7,6 +7,9 @@
 Powerboxes is a package containing utility functions for transforming bounding boxes and computing metrics. It is implemented in both Python and Rust.
 It shows a significant speedup over the equivalent numpy implementations in Python, or other libraries such as [shapely](https://github.com/shapely/shapely) or [torchvision](https://pytorch.org/vision/main/ops.html).
 
+# Checkout out the documentation !
+**🐍 Python [documentation]("https://smirkey.github.io/powerboxes/")**
+
 ## Installation
 
 ```bash
@@ -28,54 +31,3 @@ area = pb.box_areas(box)
 # Compute the intersection of the box with itself
 intersection = pb.iou_distance(box, box)
 ```
-### Functions available
-#### Box Transformations and utilities
-- `box_areas`: Compute the area of list of boxes
-- `box_convert`: Convert a box from one format to another. Supported formats are `xyxy`, `xywh`, `cxcywh`.
-- `remove_small_boxes`: Remove boxes with area smaller than a threshold
-- `mask_to_boxes`: Convert a mask to a list of boxes
-
-#### Box Metrics
-- `iou_distance`: Compute the intersection over union matrix of two sets of boxes
-- `parallel_iou_distance`: Compute the intersection over union matrix of two sets of boxes in parallel
-- `giou_distance`: Compute the generalized intersection over union matrix of two sets of boxes
-- `parallel_giou_distance`: Compute the generalized intersection over union matrix of two sets of boxes in parallel
-- `tiou_distance`: Compute the tracking intersection over union matrix of two sets of boxes
-
-#### Rotated Box Metrics
-- `rotated_iou_distance`: Compute the intersection over union matrix of two sets of rotated boxes in cxcywha format
-- `rotated_giou_distance`: Compute the generalized intersection over union matrix of two sets of rotated boxes in cxcywha format
-
-#### Box NMS
-- `nms`: Non-maximum suppression, returns the indices of the boxes to keep
-- `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.
-
-## Benchmarks
-
-Some benchmarks of powerboxes against various open source alternatives, not all functions are benchmarked. Notice that we use log scales, **all differences are major** !
-
-### Box area
-Here it's torchvision vs powerboxes vs numpy
-
-![Box area](../images/box_area.png)
-
-### Box convert
-Here it's torchvision vs powerboxes
-
-![Box convert](../images/box_convert.png)
-
-### Box IoU matrix
-Torchvision vs numpy vs powerboxes
-
-![Box IoU](../images/box_iou.png)
-
-### NMS
-Torchvision vs powerboxes vs lsnms vs numpy
-
-#### Large image (10000x10000 pixels)
-
-![Box NMS](../images/box_nms_large_image.png)
-
-#### Normal image (1000x1000 pixels)
-
-![Box NMS](../images/box_nms_normal_image.png)

bindings/docs/box_filtering.md

@@ -2,4 +2,4 @@
 
 ::: powerboxes.nms
 
-::: powerboxes.rtree_nms
+::: powerboxes.rtree_nms

bindings/docs/box_ops.md

@@ -2,4 +2,4 @@
 
 ::: powerboxes.box_convert
 
-::: powerboxes.masks_to_boxes
+::: powerboxes.masks_to_boxes

bindings/docs/index.md

@@ -35,4 +35,4 @@ intersection = pb.iou_distance(box, box)
 
 !!! note "supported dtypes by most functions"
 
-    ::: powerboxes.supported_dtypes
+    ::: powerboxes.supported_dtypes

bindings/docs/metrics.md

@@ -8,4 +8,4 @@
 
 ::: powerboxes.diou_distance
 
-::: powerboxes.tiou_distance
+::: powerboxes.tiou_distance

bindings/docs/requirements-doc.txt

@@ -3,4 +3,4 @@ mkdocs-autorefs==0.5.0
 mkdocs-material==9.5.6
 mkdocs-material-extensions==1.3.1
 mkdocstrings==0.24.0
-mkdocstrings-python==1.8.0
+mkdocstrings-python==1.8.0

bindings/docs/rotated_box.md

@@ -2,4 +2,4 @@
 
 ::: powerboxes.rotated_giou_distance
 
-::: powerboxes.rotated_tiou_distance
+::: powerboxes.rotated_tiou_distance

bindings/python/powerboxes/__init__.py

@@ -500,4 +500,4 @@ def rtree_nms(
     "rotated_tiou_distance",
     "rtree_nms",
     "__version__",
-]
+]

bindings/requirements-dev.txt

@@ -3,4 +3,4 @@ pytest-codspeed>=2.0.0
 numpy
 pytest-cov
 pillow
-maturin
+maturin

bindings/src/lib.rs

@@ -1160,4 +1160,4 @@ fn rtree_nms_i16(
         iou_threshold,
         score_threshold,
     )?);
-}
+}

bindings/tests/test_boxes.py

@@ -3,6 +3,7 @@
 import os
 from PIL import Image
 
+
 def test_masks_box():
     expected = np.array(
         [
@@ -15,7 +16,9 @@ def test_masks_box():
             [108, 148, 152, 213],
         ],
     )
-    assets_directory = os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets")
+    assets_directory = os.path.join(
+        os.path.dirname(os.path.abspath(__file__)), "assets"
+    )
     mask_path = os.path.join(assets_directory, "masks.tiff")
     image = Image.open(mask_path)
     masks = np.zeros((image.n_frames, image.height, image.width))

bindings/tests/test_dtypes.py

@@ -412,4 +412,4 @@ def test_diou_distance_dtype():
         diou_distance(
             boxes1.astype(unsuported_dtype_example),
             boxes2.astype(unsuported_dtype_example),
-        )
+        )

bindings/tests/test_speed.py

@@ -196,4 +196,4 @@ def test_nms_many_boxes(benchmark, generate_boxes):
 def test_rtree_nms_many_boxes(benchmark, generate_boxes):
     boxes = generate_boxes
     scores = np.random.random(len(boxes))
-    benchmark(rtree_nms, boxes, scores, 0.5, 0.5)
+    benchmark(rtree_nms, boxes, scores, 0.5, 0.5)

powerboxesrs/README.md

@@ -44,4 +44,3 @@ let boxes = array![[1., 2., 3., 4.], [0., 0., 10., 10.]];
 let areas = box_areas(&boxes);
 assert_eq!(areas, array![4., 100.]);
 ```
-

powerboxesrs/src/diou.rs

@@ -113,4 +113,4 @@ mod tests {
         let diou_distance_result = diou_distance(&boxes1, &boxes2);
         assert_eq!(diou_distance_result, arr2(&[[1.0]]));
     }
-}
+}