From 2c55d1796fd5b1376f1efe2534941a149c5629ca Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 12 Mar 2024 20:30:09 +0000
Subject: [PATCH 1/2] =?UTF-8?q?chore(pre=5Fcommit):=20=E2=AC=86=20pre=5Fco?=
 =?UTF-8?q?mmit=20autoupdate?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

updates:
- [github.com/PyCQA/bandit: 1.7.7 → 1.7.8](https://github.com/PyCQA/bandit/compare/1.7.7...1.7.8)
- [github.com/astral-sh/ruff-pre-commit: v0.2.2 → v0.3.2](https://github.com/astral-sh/ruff-pre-commit/compare/v0.2.2...v0.3.2)
---
 .pre-commit-config.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index d22a43ac..cd129b1e 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -29,7 +29,7 @@ repos:
 
 
   -   repo: https://github.com/PyCQA/bandit
-      rev: '1.7.7'
+      rev: '1.7.8'
       hooks:
       -   id: bandit
           args: ["-c", "pyproject.toml"]
@@ -46,7 +46,7 @@ repos:
 
 
   -   repo: https://github.com/astral-sh/ruff-pre-commit
-      rev: v0.2.2
+      rev: v0.3.2
       hooks:
       -   id: ruff
           args: [--fix, --exit-non-zero-on-fix]

From 8ea1148f7524c7be5e8e622fbf64e3b9aff378cd Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 12 Mar 2024 20:30:19 +0000
Subject: [PATCH 2/2] =?UTF-8?q?fix(pre=5Fcommit):=20=F0=9F=8E=A8=20auto=20?=
 =?UTF-8?q?format=20pre-commit=20hooks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 supervision/metrics/detection.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/supervision/metrics/detection.py b/supervision/metrics/detection.py
index 71007d71..99a11322 100644
--- a/supervision/metrics/detection.py
+++ b/supervision/metrics/detection.py
@@ -836,10 +836,10 @@ class MeanAveragePrecision:
             precision = true_positives / (true_positives + false_positives)
 
             for iou_level_idx in range(matches.shape[1]):
-                average_precisions[
-                    class_idx, iou_level_idx
-                ] = MeanAveragePrecision.compute_average_precision(
-                    recall[:, iou_level_idx], precision[:, iou_level_idx]
+                average_precisions[class_idx, iou_level_idx] = (
+                    MeanAveragePrecision.compute_average_precision(
+                        recall[:, iou_level_idx], precision[:, iou_level_idx]
+                    )
                 )
 
         return average_precisions