From 088b49ed801235b987b960f074ed5e19d995ed7e Mon Sep 17 00:00:00 2001
From: gu12530 <2629144335@qq.com>
Date: Fri, 29 Nov 2024 13:45:30 +0800
Subject: [PATCH 01/22] =?UTF-8?q?=E6=96=87=E6=A1=A3=E4=BF=AE=E6=AD=A3?=
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Content-Type: text/plain; charset=UTF-8
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---
README.md | 7 ++++--
.../opencv_circle_detection/python/README.md | 9 +++++++-
.../opencv_edge_detection/python/README.md | 16 ++++++++++++--
.../python/README.md | 10 ++++++++-
example/special/face_system/README.md | 4 ++--
example/special/face_system/python/README.md | 20 +++++++++---------
.../face_system/python/images/img_1.png | Bin 0 -> 34826 bytes
7 files changed, 48 insertions(+), 18 deletions(-)
create mode 100644 example/special/face_system/python/images/img_1.png
diff --git a/README.md b/README.md
index 94c7645..b60c36f 100644
--- a/README.md
+++ b/README.md
@@ -82,10 +82,13 @@ Lockzhiner Vision Module 拥有丰富的 IO 接口，其接口图片如下图所
### 👍 OpenCV 案例
-OpenCV 是一个开源的计算机视觉库，它提供了一组功能强大的函数，用于处理图像和视频，并进行各种图像处理和计算机视觉任务。它由一系列C函数和少量C++类构成，并提供了Python接口。
+OpenCV 是一个开源的计算机视觉库，它提供了一组功能强大的函数，用于处理图像和视频，并进行各种图像处理和计算机视觉任务。它由一系列 C++ 类构成，并提供了 Python 接口。
-* [凌智视觉模块 OpenCV 圆形检测部署指南](example/opencv_example/opencv_circle_detection)
* [凌智视觉模块 OpenCV 边缘检测案例](example/opencv_example/opencv_edge_detection)
+* [凌智视觉模块 OpenCV 直线检测部署指南](example/opencv_example/opencv_line_detection)
+* [凌智视觉模块 OpenCV 三角形检测部署指南](example/opencv_example/opencv_triangle_detection)
+* [凌智视觉模块 OpenCV 矩形检测部署指南](example/opencv_example/opencv_rectangle_detection)
+* [凌智视觉模块 OpenCV 圆形检测部署指南](example/opencv_example/opencv_circle_detection)
### 👍 目标分类案例
diff --git a/example/opencv_example/opencv_circle_detection/python/README.md b/example/opencv_example/opencv_circle_detection/python/README.md
index 1b2fb22..1e1def4 100644
--- a/example/opencv_example/opencv_circle_detection/python/README.md
+++ b/example/opencv_example/opencv_circle_detection/python/README.md
@@ -34,7 +34,7 @@
## 2 Python API 文档
-```markdown
+```python
def cvtColor(src, code, dstCn=0):
"""
转换图像颜色空间。
@@ -159,12 +159,19 @@ python test_hough_circle.py
```
运行程序后，屏幕上输出
+
+
下载结果
+
+
圆形检测原图
+
+
圆形检测结果图片
+
diff --git a/example/opencv_example/opencv_edge_detection/python/README.md b/example/opencv_example/opencv_edge_detection/python/README.md
index efaa3af..4292817 100644
--- a/example/opencv_example/opencv_edge_detection/python/README.md
+++ b/example/opencv_example/opencv_edge_detection/python/README.md
@@ -35,7 +35,7 @@
## 2 Python API 文档
-```markdown
+```python
def GaussianBlur(src, ksize, sigmaX, sigmaY=0, borderType=cv2.BORDER_DEFAULT):
"""
对图像进行高斯模糊处理。
@@ -91,6 +91,7 @@ def Canny(img, threshold1, threshold2, apertureSize=3, L2gradient=False):
为了快速上手，我们提供了边缘检测案例
**边缘检测图片下载链接：**[边缘检测图片](https://gitee.com/LockzhinerAI/LockzhinerVisionModule/releases/download/v0.0.4/car.png)
+
```python
import lockzhiner_vision_module.cv2 as cv2
# 读取图片
@@ -110,11 +111,12 @@ edges = cv2.Canny(thresholded, 20, 10)
# 保存边缘检测结果
cv2.imwrite('edges.png', edges)
```
+
## 4 上传并测试 Python 程序
参考 [连接设备指南](../../../docs/introductory_tutorial/connect_device_using_ssh.md) 正确连接 Lockzhiner Vision Module 设备。
-
+
请使用 Electerm Sftp 依次上传以下文件:
@@ -122,6 +124,7 @@ cv2.imwrite('edges.png', edges)
- 进入存放 **待检测图片** 存放的目录，将 **待检测图片** 上传到 Lockzhiner Vision Module
上传文件
+
请使用 Electerm Ssh 并在命令行中执行以下命令:
@@ -131,14 +134,23 @@ python test_canny.py
```
运行程序后，屏幕上输出
+
+
下载结果
+
+
边缘检测原图
+
+
边缘检测结果图片
+
+
阈值操作结果图片
+
diff --git a/example/opencv_example/opencv_rectangle_detection/python/README.md b/example/opencv_example/opencv_rectangle_detection/python/README.md
index b736f03..0acdd3c 100644
--- a/example/opencv_example/opencv_rectangle_detection/python/README.md
+++ b/example/opencv_example/opencv_rectangle_detection/python/README.md
@@ -34,7 +34,7 @@
## 2 Python API 文档
-```markdown
+```python
def cvtColor(src, code, dstCn=0):
"""
@@ -174,6 +174,7 @@ cv2.imwrite('img_rectangle.png', image)
- 进入存放 **待检测图片** 存放的目录，将 **待检测图片** 上传到 Lockzhiner Vision Module
上传文件
+
请使用 Electerm Ssh 并在命令行中执行以下命令:
@@ -183,12 +184,19 @@ python test_rectangle.py
```
运行程序后，屏幕上输出
+
+
下载结果
+
+
矩形检测原图
+
+
矩形检测结果图片
+
diff --git a/example/special/face_system/README.md b/example/special/face_system/README.md
index 587436e..acaa987 100644
--- a/example/special/face_system/README.md
+++ b/example/special/face_system/README.md
@@ -41,7 +41,7 @@
训练完模型后，请参考以下教程在凌智视觉模块上部署检测模型例程：
-* [凌智视觉模块 人脸识别系统 Python 部署指南](./python/README.md)
+* [凌智视觉模块人脸识别系统 Python 部署指南](./python/README.md)
## 4 各模型性能指标
@@ -49,4 +49,4 @@
| 人脸识别系统 | FPS(帧/s) | 精度(%) |
|:------------------:|:--------:|:----:|
-| LZ-Face、LZ-Arcface | 23 | - |
\ No newline at end of file
+| LZ-Face+LZ-Arcface | 23 | - |
\ No newline at end of file
diff --git a/example/special/face_system/python/README.md b/example/special/face_system/python/README.md
index be081bb..a80783d 100644
--- a/example/special/face_system/python/README.md
+++ b/example/special/face_system/python/README.md
@@ -1,4 +1,4 @@
-凌智视觉模块 人脸识别系统 Python 部署指南
+凌智视觉模块人脸识别系统 Python 部署指南
发布版本：V0.0.0
@@ -96,7 +96,7 @@ class FaceRecognitionSystem:
input_mat (cv2.Mat): 输入的图像数据，通常是一个 cv2.Mat 变量。
Returns:
- FaceFeatureResult: 识别到的用户，余弦相似度分数，检测到的目标框
+ FaceFeatureResults: 识别到的用户，余弦相似度分数，检测到的目标框
"""
return self.model.predict(input_mat)
@@ -178,15 +178,14 @@ if __name__ == '__main__':
- 进入存放 **test_arc_face[face_system.py](face_system.py).py** 脚本文件的目录，将 **[face_system.py](face_system.py).py** 上传到 Lockzhiner Vision Module
- 进入存放 **LZ-ArcFace.rknn(也可能是其他模型)** 模型存放的目录（模型存放在训练模型后下载的 output 文件夹内），将 **LZ-ArcFace.rknn** 上传到 Lockzhiner Vision Module
- 进入存放 **LZ-Face.rknn(也可能是其他模型)** 模型存放的目录（模型存放在训练模型后下载的 output 文件夹内），将 **LZ-Face.rknn** 上传到 Lockzhiner Vision Module
-- 上传构建人脸数据库的文件夹
- - 文件夹结构：
- - 主目录
- - 人脸数据库文件夹（即为用户名）
- - 人脸图片
-上传文件
-
+
文件夹结构示意图
-
+
+
+
+
+
+
请使用 Electerm Ssh 并在命令行中执行以下命令:
@@ -198,5 +197,6 @@ python face_system.py LZ-Face.rknn LZ-ArcFace.rknn baseDataset_root crop_root
运行程序后，屏幕上开始打印数据库构建的相关信息，并在一段时间后输出
+
diff --git a/example/special/face_system/python/images/img_1.png b/example/special/face_system/python/images/img_1.png
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From 52e5a7b3bdb78ea0e6c10aa8cd3d61cc148f3c84 Mon Sep 17 00:00:00 2001
From: gu12530 <2629144335@qq.com>
Date: Fri, 29 Nov 2024 13:49:46 +0800
Subject: [PATCH 02/22] =?UTF-8?q?=E6=96=87=E6=A1=A3=E4=BF=AE=E6=AD=A3?=
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example/opencv_example/opencv_circle_detection/python/README.md | 1 +
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diff --git a/example/opencv_example/opencv_circle_detection/python/README.md b/example/opencv_example/opencv_circle_detection/python/README.md
index 1e1def4..11f644d 100644
--- a/example/opencv_example/opencv_circle_detection/python/README.md
+++ b/example/opencv_example/opencv_circle_detection/python/README.md
@@ -35,6 +35,7 @@
## 2 Python API 文档
```python
+
def cvtColor(src, code, dstCn=0):
"""
转换图像颜色空间。
--
Gitee
From 36213cd33eaf9de28ccf53764dd06b5e855a5ffc Mon Sep 17 00:00:00 2001
From: gu12530 <2629144335@qq.com>
Date: Fri, 29 Nov 2024 13:54:12 +0800
Subject: [PATCH 03/22] =?UTF-8?q?=E6=96=87=E6=A1=A3=E4=BF=AE=E6=AD=A3?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
---
.../opencv_rectangle_detection/python/README.md | 2 +-
.../python/images/img_rectangle.png | Bin 0 -> 7649 bytes
.../python/images/results.png | Bin 2777 -> 0 bytes
3 files changed, 1 insertion(+), 1 deletion(-)
create mode 100644 example/opencv_example/opencv_rectangle_detection/python/images/img_rectangle.png
delete mode 100644 example/opencv_example/opencv_rectangle_detection/python/images/results.png
diff --git a/example/opencv_example/opencv_rectangle_detection/python/README.md b/example/opencv_example/opencv_rectangle_detection/python/README.md
index 0acdd3c..c932692 100644
--- a/example/opencv_example/opencv_rectangle_detection/python/README.md
+++ b/example/opencv_example/opencv_rectangle_detection/python/README.md
@@ -197,7 +197,7 @@ python test_rectangle.py
矩形检测结果图片
-
+
diff --git a/example/opencv_example/opencv_rectangle_detection/python/images/img_rectangle.png b/example/opencv_example/opencv_rectangle_detection/python/images/img_rectangle.png
new file mode 100644
index 0000000000000000000000000000000000000000..443bec4a97a237159ada9e228acbef120e2986ad
GIT binary patch
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zFf^r28L}xzi0_D><*R&l-A})N@0a$&Ax-M
Date: Fri, 29 Nov 2024 13:55:37 +0800
Subject: [PATCH 04/22] =?UTF-8?q?=E6=96=87=E6=A1=A3=E4=BF=AE=E6=AD=A3?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
---
example/opencv_example/opencv_edge_detection/python/README.md | 3 ---
1 file changed, 3 deletions(-)
diff --git a/example/opencv_example/opencv_edge_detection/python/README.md b/example/opencv_example/opencv_edge_detection/python/README.md
index 4292817..f86175c 100644
--- a/example/opencv_example/opencv_edge_detection/python/README.md
+++ b/example/opencv_example/opencv_edge_detection/python/README.md
@@ -149,9 +149,6 @@ python test_canny.py
-阈值操作结果图片
-
-
--
Gitee
From 3ca9ef792a59099d4806618b61a61ff66b9049b1 Mon Sep 17 00:00:00 2001
From: gu12530 <2629144335@qq.com>
Date: Fri, 29 Nov 2024 14:11:45 +0800
Subject: [PATCH 05/22] =?UTF-8?q?=E6=B7=BB=E5=8A=A0=E4=B8=89=E8=A7=92?=
=?UTF-8?q?=E5=BD=A2=E6=A3=80=E6=B5=8B?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
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.../opencv_edge_detection/README.md | 2 +-
.../opencv_edge_detection/python/README.md | 2 +-
.../opencv_rectangle_detection/README.md | 3 +-
.../python/README.md | 2 +-
.../opencv_triangle_detection/README.md | 40 ++++
.../python/README.md | 202 ++++++++++++++++++
.../python/images/dowmresult.png | Bin 0 -> 32943 bytes
.../python/images/result_triangle.png | Bin 0 -> 7660 bytes
.../python/images/run.png | Bin 0 -> 52907 bytes
.../python/images/triangle.png | Bin 0 -> 5952 bytes
.../python/images/uploads.png | Bin 0 -> 31419 bytes
.../python/test_trangle.py | 41 ++++
12 files changed, 288 insertions(+), 4 deletions(-)
create mode 100644 example/opencv_example/opencv_triangle_detection/README.md
create mode 100644 example/opencv_example/opencv_triangle_detection/python/README.md
create mode 100644 example/opencv_example/opencv_triangle_detection/python/images/dowmresult.png
create mode 100644 example/opencv_example/opencv_triangle_detection/python/images/result_triangle.png
create mode 100644 example/opencv_example/opencv_triangle_detection/python/images/run.png
create mode 100644 example/opencv_example/opencv_triangle_detection/python/images/triangle.png
create mode 100644 example/opencv_example/opencv_triangle_detection/python/images/uploads.png
create mode 100644 example/opencv_example/opencv_triangle_detection/python/test_trangle.py
diff --git a/example/opencv_example/opencv_edge_detection/README.md b/example/opencv_example/opencv_edge_detection/README.md
index 623dca5..7f5f992 100644
--- a/example/opencv_example/opencv_edge_detection/README.md
+++ b/example/opencv_example/opencv_edge_detection/README.md
@@ -30,7 +30,7 @@
## 1 简介
在现代计算机视觉应用中，边缘检测是一项基础而重要的任务，它能够帮助系统理解和解析图像中的关键结构信息。边缘检测技术广泛应用于图像分割、目标识别、特征提取等多个领域。
-本指南将详细介绍如何使用OpenCV库在凌智视觉模块上部署高效的边缘检测算法，旨在为开发者提供一个清晰、实用的操作步骤。
+本指南将详细介绍如何使用 OpenCV 库在凌智视觉模块上部署高效的边缘检测算法，旨在为开发者提供一个清晰、实用的操作步骤。
## 2 在凌智视觉模块上部署边缘检测案例
diff --git a/example/opencv_example/opencv_edge_detection/python/README.md b/example/opencv_example/opencv_edge_detection/python/README.md
index f86175c..1ffd553 100644
--- a/example/opencv_example/opencv_edge_detection/python/README.md
+++ b/example/opencv_example/opencv_edge_detection/python/README.md
@@ -30,7 +30,7 @@
## 1 简介
在现代计算机视觉应用中，边缘检测是一项基础而重要的任务，它能够帮助系统理解和解析图像中的关键结构信息。边缘检测技术广泛应用于图像分割、目标识别、特征提取等多个领域。
-本指南将详细介绍如何使用OpenCV库在凌智视觉模块上部署高效的边缘检测算法，旨在为开发者提供一个清晰、实用的操作步骤。
+本指南将详细介绍如何使用 OpenCV 库在凌智视觉模块上部署高效的边缘检测算法，旨在为开发者提供一个清晰、实用的操作步骤。
## 2 Python API 文档
diff --git a/example/opencv_example/opencv_rectangle_detection/README.md b/example/opencv_example/opencv_rectangle_detection/README.md
index 8290a51..2d9b97f 100644
--- a/example/opencv_example/opencv_rectangle_detection/README.md
+++ b/example/opencv_example/opencv_rectangle_detection/README.md
@@ -29,7 +29,8 @@
## 1 简介
-在现代计算机视觉应用中，矩形检测是一项基本但重要的任务，广泛应用于物体识别、场景理解、文档扫描等领域。本指南将详细介绍如何使用OpenCV库在凌智视觉模块上部署高效的矩形检测算法。
+在现代计算机视觉应用中，矩形检测是一项基本但重要的任务，广泛应用于物体识别、场景理解、文档扫描等领域。本指南将详细介绍如何使用 OpenCV 库在凌智视觉模块上部署高效的矩形检测算法。
+
## 2 在凌智视觉模块上部署矩形检测案例
下载模型后，请参考以下教程使用 Python 在凌智视觉模块上部署分类模型例程：
diff --git a/example/opencv_example/opencv_rectangle_detection/python/README.md b/example/opencv_example/opencv_rectangle_detection/python/README.md
index c932692..43a93d8 100644
--- a/example/opencv_example/opencv_rectangle_detection/python/README.md
+++ b/example/opencv_example/opencv_rectangle_detection/python/README.md
@@ -29,7 +29,7 @@
## 1 简介
-在现代计算机视觉应用中，矩形检测是一项基本但重要的任务，广泛应用于物体识别、场景理解、文档扫描等领域。本指南将详细介绍如何使用OpenCV库在凌智视觉模块上部署高效的矩形检测算法。 本文将详细介绍如何使用 OpenCV 库在凌智视觉模块上实现高效的矩形检测功能。
+在现代计算机视觉应用中，矩形检测是一项基本但重要的任务，广泛应用于物体识别、场景理解、文档扫描等领域。本指南将详细介绍如何使用 OpenCV 库在凌智视觉模块上部署高效的矩形检测算法。 本文将详细介绍如何使用 OpenCV 库在凌智视觉模块上实现高效的矩形检测功能。
## 2 Python API 文档
diff --git a/example/opencv_example/opencv_triangle_detection/README.md b/example/opencv_example/opencv_triangle_detection/README.md
new file mode 100644
index 0000000..9a31085
--- /dev/null
+++ b/example/opencv_example/opencv_triangle_detection/README.md
@@ -0,0 +1,40 @@
+凌智视觉模块 OpenCV 三角形检测部署指南
+
+发布版本：V0.0.0
+
+日期：2024-11-29
+
+文件密级：□绝密 □秘密 □内部资料 ■公开
+
+---
+
+**免责声明**
+
+本文档按**现状**提供，福州凌睿智捷电子有限公司（以下简称**本公司**）不对本文档中的任何陈述、信息和内容的准确性、可靠性、完整性、适销性、适用性及非侵权性提供任何明示或暗示的声明或保证。本文档仅作为使用指导的参考。
+
+由于产品版本升级或其他原因，本文档可能在未经任何通知的情况下不定期更新或修改。
+
+**读者对象**
+
+本教程适用于以下工程师：
+
+- 技术支持工程师
+- 软件开发工程师
+
+**修订记录**
+
+| **日期** | **版本** | **作者** | **修改说明** |
+|:-----------| -------- |--------| ------------ |
+| 2024/11/29 | 0.0.0 | 钟海滨 | 初始版本 |
+
+## 1 简介
+
+在计算机视觉领域，形状检测是一项基本而重要的任务，尤其在工业检测、机器人导航、图像分析等领域有着广泛应用。本指南将详细介绍如何使用 OpenCV 库在凌智视觉模块上部署三角形检测功能。
+
+## 2 在凌智视觉模块上部署三角形检测案例
+
+下载模型后，请参考以下教程使用 Python 在凌智视觉模块上部署分类模型例程：
+
+- [凌智视觉模块 OpenCV 三角形检测 Python 部署指南](./python/README.md)
+
+
diff --git a/example/opencv_example/opencv_triangle_detection/python/README.md b/example/opencv_example/opencv_triangle_detection/python/README.md
new file mode 100644
index 0000000..613ce59
--- /dev/null
+++ b/example/opencv_example/opencv_triangle_detection/python/README.md
@@ -0,0 +1,202 @@
+凌智视觉模块 OpenCV 矩形检测 Python 部署指南
+
+发布版本：V0.0.0
+
+日期：2024-11-29
+
+文件密级：□绝密 □秘密 □内部资料 ■公开
+
+---
+
+**免责声明**
+
+本文档按**现状**提供，福州凌睿智捷电子有限公司（以下简称**本公司**）不对本文档中的任何陈述、信息和内容的准确性、可靠性、完整性、适销性、适用性及非侵权性提供任何明示或暗示的声明或保证。本文档仅作为使用指导的参考。
+
+由于产品版本升级或其他原因，本文档可能在未经任何通知的情况下不定期更新或修改。
+
+**读者对象**
+
+本教程适用于以下工程师：
+
+- 技术支持工程师
+- 软件开发工程师
+
+**修订记录**
+
+| **日期** | **版本** | **作者** | **修改说明** |
+|:-----------| -------- |--------| ------------ |
+| 2024/11/29 | 0.0.0 | 钟海滨 | 初始版本 |
+
+## 1 简介
+
+在现代计算机视觉应用中，矩形检测是一项基本但重要的任务，广泛应用于物体识别、场景理解、文档扫描等领域。本指南将详细介绍如何使用 OpenCV 库在凌智视觉模块上部署高效的矩形检测算法。 本文将详细介绍如何使用 OpenCV 库在凌智视觉模块上实现高效的矩形检测功能。
+
+## 2 Python API 文档
+
+```python
+
+def cvtColor(src, code, dstCn=0):
+ """
+ 转换图像颜色空间。
+ 参数:
+ - src: 输入图像。
+ - code: 颜色空间转换代码。
+ - dstCn: 目标图像的通道数，如果为0则根据code自动确定。
+ 返回:
+ - 转换后的图像。
+ """
+ return cv2.cvtColor(src, code, dstCn)
+
+def GaussianBlur(src, ksize, sigmaX, sigmaY=0, borderType=cv2.BORDER_DEFAULT):
+ """
+ 使用高斯滤波模糊图像。
+ 参数:
+ - src: 输入图像。
+ - ksize: 高斯核的大小，必须是奇数。
+ - sigmaX: 高斯核在X方向的标准差。
+ - sigmaY: 高斯核在Y方向的标准差，如果为0则与sigmaX相同。
+ - borderType: 图像边界的处理方式，默认为cv2.BORDER_DEFAULT。
+ 返回:
+ - 模糊后的图像。
+ """
+ temp_ksize = convert2size(ksize)
+ return cv2.GaussianBlur(src, temp_ksize, sigmaX, sigmaY, borderType)
+
+def threshold(src, thresh, maxval, type):
+ """
+ 对图像应用阈值处理。
+ 参数:
+ - src: 输入图像。
+ - thresh: 阈值。
+ - maxval: 阈值处理后的最大值。
+ - type: 阈值处理的类型。
+ 返回:
+ - 计算出的阈值。
+ - 阈值处理后的图像。
+ """
+ computed_threshold, dst = cv2.threshold(src, thresh, maxval, type)
+ return computed_threshold, dst
+
+def drawContours(img, contours, contourIdx, color, thickness=1, lineType=8, shift=0):
+ """
+ 在图像上绘制轮廓。
+ 参数:
+ - img: 输入图像。
+ - contours: 要绘制的轮廓列表。
+ - contourIdx: 要绘制的轮廓索引，-1表示绘制所有轮廓。
+ - color: 轮廓的颜色。
+ - thickness: 轮廓线的厚度。
+ - lineType: 轮廓线的类型。
+ - shift: 轮廓坐标的小数位数。
+ """
+ temp_color = convert2scalar(color)
+ cv2.drawContours(img, contours, contourIdx, temp_color, thickness, lineType, shift)
+
+def findContours(image, mode, method, point=cv2.Point()):
+ """
+ 在二值图像中检测轮廓。
+ 参数:
+ - image: 输入的二值图像。
+ - mode: 轮廓的检索模式。
+ - method: 轮廓的近似方法。
+ - point: 轮廓检索的起始点。
+ 返回:
+ - 检测到的轮廓列表。
+ - 轮廓的层次结构。
+ """
+ contours, hierarchy = cv2.findContours(image, mode, method, point)
+ return contours, hierarchy
+
+def arcLength(curve, closed):
+ """
+ 计算曲线的长度。
+ 参数:
+ - curve: 输入的曲线，由点序列组成。
+ - closed: 曲线是否封闭。
+ 返回:
+ - 曲线的长度。
+ """
+ return cv2.arcLength(curve, closed)
+
+
+def approxPolyDP(curve, epsilon, closed):
+ """
+ 使用Douglas-Peucker算法近似曲线。
+ 参数:
+ - curve: 输入的曲线，由点序列组成。
+ - epsilon: 近似精度，通常为原始曲线长度的百分之一。
+ - closed: 曲线是否封闭。
+ 返回:
+ - 近似后的曲线。
+ """
+ return cv2.approxPolyDP(curve, epsilon, closed)
+
+```
+
+## 3 在凌智视觉模块上进行边缘检测案例
+
+为了方便大家入手，我们提供了 OpenCV 矩形检测的 Python 例程。该程序可以使用摄像头进行端到端推理。
+**测试图片下载链接：**[矩形检测图片](https://gitee.com/LockzhinerAI/LockzhinerVisionModule/releases/download/v0.0.4/rectangle.png)
+
+```python
+import lockzhiner_vision_module.cv2 as cv2
+# 读取图像
+image = cv2.imread('rectangle.png')
+gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+# 高斯模糊
+blurred = cv2.GaussianBlur(gray, (5, 5), 0)
+# 二值化
+_, binary = cv2.threshold(blurred, 127, 255, cv2.THRESH_BINARY_INV)
+edges = cv2.Canny(binary, 30, 200)
+contours, _ = cv2.findContours(edges.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
+for contour in contours:
+ # 近似轮廓
+ # 计算轮廓周长
+ epsilon = 0.02 * cv2.arcLength(contour, True)
+ # 将轮廓近似为多边形
+ approx = cv2.approxPolyDP(contour, epsilon, True)
+ # 如果近似轮廓有4个顶点，则认为是矩形
+ if len(approx) == 4:
+ cv2.drawContours(image, [approx], -1, (0, 255, 0), 2)
+cv2.imwrite('img_rectangle.png', image)
+
+```
+## 4 上传并测试 Python 程序
+
+参考 [连接设备指南](../../../../docs/introductory_tutorial/connect_device_using_ssh.md) 正确连接 Lockzhiner Vision Module 设备。
+
+
+
+请使用 Electerm Sftp 依次上传以下文件:
+
+- 进入存放 **test_rectangle.py** 脚本文件的目录，将 **test_rectangle.py** 上传到 Lockzhiner Vision Module
+- 进入存放 **待检测图片** 存放的目录，将 **待检测图片** 上传到 Lockzhiner Vision Module
+
+上传文件
+
+
+
+请使用 Electerm Ssh 并在命令行中执行以下命令:
+
+```bash
+python test_rectangle.py
+```
+
+运行程序后，屏幕上输出
+
+
+
+下载结果
+
+
+
+矩形检测原图
+
+
+
+矩形检测结果图片
+
+
+
+
+
diff --git a/example/opencv_example/opencv_triangle_detection/python/images/dowmresult.png b/example/opencv_example/opencv_triangle_detection/python/images/dowmresult.png
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