drawbox-cv 0.1.2

A modular, interactive bounding box frame labeler with zoom and pan support.

DrawBox-CV

A modular, cross-platform, Tkinter-based interactive frame annotator for computer vision datasets.

DrawBox-CV provides a desktop-based, lightweight interactive labeling GUI (similar to a local Roboflow editor), enabling real-time frame-by-frame labeling with mouse zoom and pan, dynamic color mapping, unlimited custom classes, and multi-format labels export.

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Key Features

• Pristine Tkinter GUI Engine: A clean, cross-platform desktop interface that natively supports resizing to fit any monitor resolution.
• Interactive Zoom & Pan:
  • Zoom: Scroll mouse wheel (zoom is centered directly around your mouse cursor).
  • Pan: Drag with Right-click to pan and move the canvas.
• Bounding Box Editing:
  • Draw: Click and drag with Left-click on an empty area.
  • Move: Drag inside an existing box with Left-click.
  • Resize: Drag the white corner handles with Left-click.
  • Select: Click a box with Ctrl + Left-click to select it and activate its label class.
• Visual Selection Indicators:
  • Currently selected boxes are drawn with a Red outline.
  • Hovering over any box highlights it in Gold.
  • Automatically assigns unique HSV colors to your classes, strictly avoiding colors close to Red or Gold to prevent confusion.
• Instruction Collapsing: Click the ▼ Instructions or ▼ Classes headers on the sidebars to hide/reveal panels instantly.

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Installation

Ensure you have Python 3.8 or newer installed on your system.

1. Install System Prerequisites (Linux Only)

On Linux systems (e.g., Ubuntu/Debian), Tkinter requires system-level libraries. Install them via your package manager:

sudo apt update
sudo apt install python3-tk

(Windows and macOS include Tkinter by default during Python installation).

2. Install Package

You can install drawbox-cv using pip or uv:

Using pip:

pip install drawbox-cv

Using uv:

uv add drawbox-cv

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How to Run

DrawBox-CV can be launched either via Python code or directly from your terminal.

1. Running via Python Code (API)

from drawbox import AnnotatorApp, AnnotatorConfig

# 1. Create a configuration for your labeling session
config = AnnotatorConfig(
    frames_dir="path/to/your/images",      # Required: Path to the folder containing your source images (.jpg, .png, etc.)
    output_labels_dir="output",            # Optional: Base directory where all label folders, classes.txt, and crops will be saved. Default is "output".
    start_frame=0,                         # Optional: Frame index to start labeling from. Default is 0.
    initial_label_file="",                 # Optional: Path to a file containing initial labels to load on startup. Default is "".
    initial_label_format="tf",             # Optional: Format of the initial labels file ("tf", "yolo", "coco", "voc"). Default is "tf".
    formats=["yolo"],                      # Optional: List of formats to save simultaneously ("tf", "yolo", "coco", "voc"). Default is ["yolo"].
    save_crops=False,                      # Optional: Crop the annotated bounding boxes and save them into separate subfolders. Default is False.
    crops_out_dir=None,                    # Optional: Custom folder to save crop images. Defaults to output_labels_dir/crops.
    carry_over_labels=False                # Optional: Copy edited labels from the previous frame to the next frame automatically. Default is False.
)

# 2. Initialize the main Tkinter application with the configuration
app = AnnotatorApp(config)

# 3. Launch the graphical interface and start labeling!
app.mainloop()

2. Running via Terminal (CLI)

Once installed, you can launch the interactive CLI runner from any folder in your terminal simply by typing:

drawbox

Or, if running directly from the source directory:

python -m drawbox

The CLI will walk you through prompts to specify the input frames folder, output formats, and other options.

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Configuration Parameter Options

Below are the details of all configuration parameters accepted by AnnotatorConfig:

Parameter	Type	Default	Description	Options / Example
frames_dir	str	Required	Path to the directory containing images to label.	"data/frames"
output_labels_dir	str	"output"	Path to the base directory where labels are exported.	"labels_output"
start_frame	int	0	Starting frame index inside the directory.	15
initial_label_file	str	""	Optional initial file with annotations to pre-populate labels.	"prelabels.json"
initial_label_format	str	"tf"	Format of the initial labels file.	"tf", "yolo", "coco", "voc"
formats	list[str]	["yolo"]	List of output formats to write concurrently upon saving.	["yolo", "coco", "voc", "tf"]
save_crops	bool	False	Whether to crop and save the bounding boxes as PNG crops.	True, False
crops_out_dir	str	None	Custom output folder for crops (defaults to output_labels_dir/crops).	"my_crops"
carry_over_labels	bool	False	Automatically carry over bounding boxes to subsequent frames.	True, False

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Output Directory Layout

Annotations are exported into organized subfolders matching each format inside the base output_labels_dir directory:

output_labels_dir/
├── classes.txt                       # Unique class ID mapped to class names (e.g. "0: car")
├── yolo/                             # Normalized yolo coordinates: [class_id, x_center, y_center, width, height]
│   ├── frame_001.txt
│   └── frame_002.txt
├── voc/                              # XML format files matching Pascal VOC standards
│   ├── frame_001.xml
│   └── frame_002.xml
├── tf/                               # Normalized coordinate text files: [class_id, xmin, ymin, xmax, ymax]
│   ├── frame_001.txt
│   └── frame_002.txt
└── crops/                            # categorised PNG crops for each class (if save_crops is Enabled)
    └── 0_car/
        ├── 0.png
        └── 1.png

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Keyboard Shortcuts Map

Key	Description
s / S / Enter	Save labels and move to Next frame
k / K / Right Arrow / Down Arrow	Skip current frame without saving, and move to Next frame
a / A / Left Arrow / Up Arrow	Move back to Previous frame
f / F	Center and fit the image to the window size
Ctrl + Z	Undo the last change
Ctrl + Shift + Z	Redo the last change
r / R	Copy previous frame's labels to current frame
Ctrl + Left Click	Select bounding box and its class label (allows drawing nested boxes)
Delete / Backspace	Delete the currently selected bounding box
0 – 9	Quick-select corresponding class IDs
q / Esc	Close window and exit app