OpenCV 轻量扩展:Unicode 路径读写、HALCON 风格灰度缩放
Project description
ydl2
ydl2 是对 OpenCV 的轻量补充:解决 Windows 中文路径 读写问题,提供与 HALCON 语义一致的灰度缩放算子,以及基于 HALCON 的形状模板匹配封装。
安装
pip install ydl2
快速使用
Unicode 路径 & 灰度缩放
import ydl2
# Unicode 路径读写(Windows 中文路径)
img = ydl2.imread(r"D:\图片\测试.png")
ydl2.imwrite(r"D:\图片\输出.png", img)
# HALCON 等价算子
stretched = ydl2.scale_image_max(img)
inverted = ydl2.scale_image(img, -1.0, 255.0)
mapped = ydl2.scale_image_range(img, 100, 200)
形状模板匹配
import ydl2
import cv2
# 加载模板(只需一次)
model = ydl2.read_shape_model(r"model.yyds")
# 读图并创建图像句柄(首次)
mat = cv2.imread(r"image.jpg")
b, g, r = cv2.split(mat)
handle = ydl2.any_to_tiyoo(r, g, b)
# 匹配
results = ydl2.find_shape_model(handle, model)
for res in results:
print(res['row'], res['col'], res['score'])
# 后续帧原地更新(零内存分配)
handle = ydl2.any_to_tiyoo(r, g, b, handle=handle)
# 释放
ydl2.clear_image(handle)
ydl2.clear_shape_model(model)
API
| 函数 | 说明 |
|---|---|
imread / imwrite / imshow |
支持中文路径的读写与显示 |
scale_image_max |
每通道 min/max 拉伸到 0–255 |
scale_image |
g' = g * Mult + Add |
scale_image_range |
区间线性映射 |
any_to_tiyoo |
numpy 数组 → Halcon 图像句柄(创建或原地更新) |
tiyoo_to_any |
Halcon 图像句柄 → numpy 数组 |
read_image / write_image / clear_image |
Halcon 图像文件读写与释放 |
read_shape_model / clear_shape_model |
加载 / 释放 Halcon 模板文件 |
find_shape_model |
形状模板匹配,返回 [{'row', 'col', 'angle', 'score'}] |
依赖
- Python >= 3.8
- numpy >= 1.21
- opencv-python >= 4.6
链接
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