drawcv 0.1.2

Stylized OpenCV rectangle and frame drawing helpers for detection overlays.

drawcv

drawcv is a computer-vision helper library that upgrades plain OpenCV bounding boxes into polished, style-rich frames for detection overlays, demos, and dashboards.

It works directly with numpy images and OpenCV, so you can drop it into existing object detection pipelines with minimal code change.

Installation

pip install drawcv

Why drawcv

• Replace plain cv2.rectangle(...) output with modern frame styles.
• Keep your current OpenCV flow (cv2.imread, model inference, draw, cv2.imwrite).
• Choose style by name or index.
• Optionally add a custom color/line overlay on top of any style.

Quick Start

import cv2
from drawcv import drawcv

image = cv2.imread("resource/test.png")

drawcv(
    image=image,
    style_id="pro-clean-blue",  # or style index like 0, 1, 2...
    coords=(80, 60, 280, 220),  # x1, y1, x2, y2
)

cv2.imwrite("output.jpg", image)

OpenCV Comparison

Standard OpenCV

cv2.rectangle(image, (x1, y1), (x2, y2), (0, 255, 0), 2)

drawcv Replacement

from drawcv import drawcv

drawcv(
    image=image,
    style_id="pro-clean-blue",
    coords=(x1, y1, x2, y2),
)

With Optional Overlay Color/Line Width

drawcv(
    image=image,
    style_id="futuristic-hud",
    coords=(x1, y1, x2, y2),
    color=(255, 255, 255),  # BGR
    line_width=1,
)

Available Styles

from drawcv import list_visionframe_styles

print(list_visionframe_styles())

Style Gallery

Current preview of frame styles:

Generate this gallery again:

import cv2
from drawcv import create_visionframe_gallery

gallery = create_visionframe_gallery()
cv2.imwrite("resource/visionframe_styles_gallery.png", gallery)

Local Development

python -m venv .venv
.venv\Scripts\activate
pip install -e .[dev]

Build Package

python -m build