cvlayer 0.32.0

OpenCV Layer Helper

cvlayer

OpenCV Layer Helper

Overview

When performing image-based machine learning/inference, many situations arise that require pre-/post-processing appropriate for the domain environment.

A commonly used library today is OpenCV.

Image processing with OpenCV requires insight into the image and the domain.

However, gaining these insights often requires doing something far from the essence. (Visualization, parameter modification, library conflicts, assertions, etc...)

Here are some problems that occurred to me:

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Features

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Installation

Install cvlayer:

pip install cvlayer

Install cvlayer with opencv-python:

pip install cvlayer[opencv]

Install cvlayer with opencv-python-headless:

pip install cvlayer[headless]

Usage

CvLayer

Just inherit cvlayer.CvLayer.

from cvlayer import CvLayer


class YourApp(CvLayer):
    def func(self, image):
        self.cvl_cvt_color_bgr2hsv(image)

CvWindow

Just inherit cvlayer.CvWindow.

from cvlayer import CvWindow
from numpy.typing import NDArray


class YourApp(CvWindow):
    def on_frame(self, image: NDArray) -> NDArray:
        # TODO: Implement image processing logic ...
        return image


YourApp("/path/to/video/file.mp4").run()

Example

The following sample is a Perspective Transform example:

from sys import argv, stderr
from sys import exit as sys_exit
from typing import List, Optional

from cvlayer import CvLayer, CvMixin, CvWindow
from cvlayer.typing import PointI
from cvlayer.palette.basic import RED
from numpy.typing import NDArray


class YourApp(CvWindow, CvMixin, CvLayer):
    _points: List[PointI]

    def __init__(self, source: str, destination: Optional[str] = None):
        super().__init__(source, destination)
        left_top = 930, 2750
        left_bottom = 846, 3098
        right_top = 1091, 2750
        right_bottom = 1361, 3098
        self._points = [left_top, left_bottom, right_top, right_bottom]
        self._scale = 2, 4

    def on_frame(self, image: NDArray) -> NDArray:
        with self.layer("select-roi") as layer:
            self.roi = layer.param("roi").build_select_roi().value
            layer.frame = layer.prev_frame

        with self.layer("perspective-points") as layer:
            points = layer.param("pp").build_select_points(self._points).value
            canvas = layer.prev_frame.copy()
            for p in points:
                self.cvl_draw_point(canvas, p, color=RED)
            layer.frame = canvas

        with self.layer("perspective-transform") as layer:
            sw = layer.param("scale-width").build_uint(self._scale[0]).value
            sh = layer.param("scale-height").build_uint(self._scale[1]).value

            xs = list(map(lambda point: point[0], self._points))
            ys = list(map(lambda point: point[1], self._points))
            x1, x2 = min(xs), max(xs)
            y1, y2 = min(ys), max(ys)
            width, height = abs(x2 - x1) * sw, abs(y2 - y1) * sh
            roi = 0, 0, width, height
            m = self.cvl_get_perspective_transform_with_quadrilateral(
                left_top=points[0],
                left_bottom=points[1],
                right_top=points[2],
                right_bottom=points[3],
                destination_roi=roi,
            )
            layer.frame = self.cvl_warp_perspective(image, m, (width, height))

        with self.layer("hsv") as layer:
            layer.frame = hsv = self.cvl_cvt_color_bgr2hsv(layer.prev_frame)
        with self.layer("hsv-h") as layer:
            layer.frame = h = hsv[:, :, 0]
        with self.layer("hsv-s") as layer:
            layer.frame = s = hsv[:, :, 1]
        with self.layer("hsv-v") as layer:
            layer.frame = v = hsv[:, :, 2]

        assert h is not None
        assert s is not None
        assert v is not None

        self.cvm_gaussian_blur("v-blur", (3, 19), 0.0, 7.0)
        self.cvm_threshold_binary("v-thresh", 230)

        return self.last_frame


def test_main(*args) -> None:
    source = args[1]
    destination = args[2] if len(args) >= 3 else None

    try:
        app = YourApp(source, destination)
        app.run()
    except Exception as e:
        print(e, file=stderr)
        sys_exit(1)
    else:
        sys_exit(0)


if __name__ == "__main__":
    test_main(*argv)

License

See the LICENSE file for details. In summary, cvlayer is licensed under the MIT license.