| Name | mcv-plus JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | None |
| Summary | Opencv图像处理增强库 |
| upload_time | 2024-10-24 13:35:54 |
| maintainer | None |
| docs_url | None |
| author | KateTseng |
| requires_python | >=3 |
| license | MIT |
| keywords |
auto
script
testing
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# 图像处理模块
本模块提供一个 `Image` 类，用于基本的图像操作和使用 OpenCV 进行模板匹配的功能。
## 类：Image
### `__init__(image: cv2.Mat)`
初始化一个 `Image` 对象。
- **参数：**
- `image`：OpenCV 图像，类型为 `cv2.Mat`。
### 方法
#### 基础功能
- **`read(file_path: str) -> Image`**
- 从文件中读取图像。
- **参数：**
- `file_path`：图像文件的路径。
- **返回：** 一个 `Image` 对象。
- **`save(file_path: str, ext: str = ".png")`**
- 将图像保存到指定的文件。
- **参数：**
- `file_path`：保存图像的路径。
- `ext`：保存图像的文件格式。
- **`show(window_name: str = "Image")`**
- 在窗口中显示图像。
- **参数：**
- `window_name`：窗口的名称。
- **`to_base64() -> str`**
- 将图像转换为 base64 编码的字符串。
- **`to_bytes() -> bytes`**
- 将图像转换为字节数组。
#### 图像处理功能
- **`resize(width: int, height: int) -> Image`**
- 将图像调整为指定的尺寸。
- **参数：**
- `width`：新宽度。
- `height`：新高度。
- **`scale(fx: float = 1.0, fy: float = 1.0) -> Image`**
- 根据指定的比例因子缩放图像。
- **参数：**
- `fx`：宽度的缩放比例。
- `fy`：高度的缩放比例。
- **`grayscale() -> Image`**
- 将图像转换为灰度图像。
- **`clip(x: int, y: int, w: int, h: int) -> Image`**
- 裁剪图像到指定的区域。
- **参数：**
- `x`：起始 x 坐标。
- `y`：起始 y 坐标。
- `w`：裁剪区域的宽度。
- `h`：裁剪区域的高度。
- **`pyr_down() -> Image`**
- 使用金字塔方法下采样图像。
- **`get_pixel(x: int, y: int) -> Tuple[int, int, int]`**
- 获取指定坐标处的像素的 BGR 值。
#### 绘图功能
- **`draw_line(pt1: Sequence[int], pt2: Sequence[int], color: Sequence[float] = (0, 0, 255), thickness: int = 1) -> Image`**
- 在图像上绘制一条线。
- **`draw_rectangle(pt1: Sequence[int], pt2: Sequence[int], color: Sequence[float] = (0, 0, 255), thickness: int = 1) -> Image`**
- 在图像上绘制一个矩形。
- **`draw_circle(center: Sequence[int], radius: int, color: Sequence[float] = (0, 0, 255), thickness: int = 1) -> Image`**
- 在图像上绘制一个圆。
- **`draw_text(text: str, position: Sequence[int], color: Sequence[int] = (0, 0, 255), font_size: int = 1, font_path: str = "simsun.ttc") -> Image`**
- 在图像上绘制文字。
- **`draw_point(center: Sequence[int], radius: int = 1, color: Sequence[float] = (0, 0, 255)) -> Image`**
- 在图像上绘制一个点。
## 模板匹配功能
- **`match_template(img: Image, template: Image, region: Sequence[int] = None, threshold: float = 0.95, max_result: int = 5) -> Optional[List[Tuple[int, int]]]`**
- 执行模板匹配。
- **`match_template_best(img: Image, template: Image, region: Sequence[int] = None, threshold: float = 0.95, level: int = None) -> Optional[Tuple[int, int]]`**
- 找到图像中模板的最佳匹配。
## 找色功能
- **`find_color(img: Image, color: Sequence[int], region: Sequence[int] = None, threshold: int = 4) -> Optional[Tuple[int, int]]`**
- 找到一个匹配特定颜色的像素。
- **`find_all_points_color(img: Image, color: Sequence[int], region: Sequence[int] = None, threshold: int = 4) -> Optional[List[Tuple[int, int]]]`**
- 找到图像中所有匹配特定颜色的点。
- **`find_multi_colors(img: Image, first_color: Sequence[int], colors: List[Tuple[int, int, Sequence[int]]], region: Sequence[int] = None, threshold: int = 4) -> Optional[Tuple[int, int]]`**
- 找到匹配多个颜色的点。
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\u5728\u56fe\u50cf\u4e0a\u7ed8\u5236\u4e00\u6761\u7ebf\u3002\r\n\r\n- **`draw_rectangle(pt1: Sequence[int], pt2: Sequence[int], color: Sequence[float] = (0, 0, 255), thickness: int = 1) -> Image`**\r\n - \u5728\u56fe\u50cf\u4e0a\u7ed8\u5236\u4e00\u4e2a\u77e9\u5f62\u3002\r\n\r\n- **`draw_circle(center: Sequence[int], radius: int, color: Sequence[float] = (0, 0, 255), thickness: int = 1) -> Image`**\r\n - \u5728\u56fe\u50cf\u4e0a\u7ed8\u5236\u4e00\u4e2a\u5706\u3002\r\n\r\n- **`draw_text(text: str, position: Sequence[int], color: Sequence[int] = (0, 0, 255), font_size: int = 1, font_path: str = \"simsun.ttc\") -> Image`**\r\n - \u5728\u56fe\u50cf\u4e0a\u7ed8\u5236\u6587\u5b57\u3002\r\n\r\n- **`draw_point(center: Sequence[int], radius: int = 1, color: Sequence[float] = (0, 0, 255)) -> Image`**\r\n - \u5728\u56fe\u50cf\u4e0a\u7ed8\u5236\u4e00\u4e2a\u70b9\u3002\r\n\r\n## \u6a21\u677f\u5339\u914d\u529f\u80fd\r\n- **`match_template(img: Image, template: Image, region: Sequence[int] = None, threshold: float = 0.95, max_result: int = 5) -> Optional[List[Tuple[int, int]]]`**\r\n - 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