### Install bbox-visualizer from Source with uv

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/installation.md

Install bbox-visualizer from its source code using `uv` for an editable installation.

```console
uv pip install -e .
```

--------------------------------

### Set up development environment

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/CONTRIBUTING.md

Install uv, create a virtual environment, and install development dependencies.

```bash
pip install uv
cd bbox_visualizer
uv venv
uv pip install -e ".[dev]"
```

--------------------------------

### Install bbox-visualizer from Source with pip

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/installation.md

Install bbox-visualizer from its source code using `pip` for an editable installation.

```console
pip install -e .
```

--------------------------------

### Install bbox-visualizer

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Install the package using pip. This is the primary method for adding the library to your project.

```bash
pip install bbox-visualizer
```

--------------------------------

### Install bbox-visualizer with uv

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/installation.md

Install the bbox-visualizer package using the `uv` package manager.

```console
uv pip install bbox-visualizer
```

--------------------------------

### Install bbox-visualizer from Source with uv (Development)

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/installation.md

Install bbox-visualizer from its source code with development dependencies using `uv`.

```console
uv pip install -e ".[dev]"
```

--------------------------------

### Install uv Package Manager

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/installation.md

Install the `uv` package manager, a fast Python package installer and resolver.

```console
pip install uv
```

--------------------------------

### Install bbox-visualizer from Source with pip (Development)

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/installation.md

Install bbox-visualizer from its source code with development dependencies using `pip`.

```console
pip install -e ".[dev]"
```

--------------------------------

### Clone the repository

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/CONTRIBUTING.md

Clone your forked repository locally to start development.

```bash
git clone git@github.com:your_name_here/bbox_visualizer.git
```

--------------------------------

### Object Detection Visualization Example

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/usage.md

Visualize object detection results by drawing bounding boxes and labels with confidence scores on an image. This example simulates detection results.

```python
import bbox_visualizer as bbv
import cv2
import numpy as np

# Simulate object detection results
detections = [
    {"bbox": (50, 50, 150, 150), "label": "Person", "confidence": 0.95},
    {"bbox": (200, 100, 300, 200), "label": "Car", "confidence": 0.87},
    {"bbox": (350, 150, 450, 250), "label": "Dog", "confidence": 0.92}
]

# Load image
image = cv2.imread('detection_image.jpg')

# Visualize each detection
for det in detections:
    bbox = det["bbox"]
    label = f"{det['label']} ({det['confidence']:.2f})"

    # Draw box and label
    image = bbv.draw_box(image, bbox, bbox_color=(0, 255, 0))
    image = bbv.add_label(image, label, bbox)
```

--------------------------------

### Full Object Detection Pipeline Example

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Demonstrates a full object detection pipeline using simulated detector output. Iterates through detections, assigns per-class colors, and draws boxes with confidence labels using `draw_box` and `add_label`.

```python
import bbox_visualizer as bbv
import cv2

# Simulated detector output: (bbox, class_name, confidence)
detections = [
    ([45,  60,  180, 230], "person", 0.97),
    ([210, 85,  370, 260], "car",    0.89),
    ([390, 50,  540, 210], "dog",    0.93),
]

# Per-class BGR colors
class_colors = {
    "person": (0,   255,   0),   # Green
    "car":    (255,   0,   0),   # Blue
    "dog":    (0,     0, 255),   # Red
}

image = cv2.imread("scene.jpg")

for bbox, cls, conf in detections:
    color = class_colors.get(cls, (200, 200, 200))
    label = f"{cls} {conf:.2f}"

    image = bbv.draw_box(image, bbox, bbox_color=color, thickness=2)
    image = bbv.add_label(image, label, bbox, text_bg_color=color, text_color=(0, 0, 0))

cv2.imwrite("annotated_scene.jpg", image)
# => Saves annotated image with colored boxes and confidence labels
```

--------------------------------

### Basic bbox-visualizer Usage

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/usage.md

Import the library and use its functions to draw bounding boxes and add labels to an image. Ensure you have OpenCV and NumPy installed.

```python
import bbox_visualizer as bbv
import cv2
import numpy as np

# Load an image
image = cv2.imread('image.jpg')

# Draw a bounding box
bbox = (100, 100, 200, 200)  # (x1, y1, x2, y2) format
image = bbv.draw_box(image, bbox)

# Add a label
image = bbv.add_label(image, "Object", bbox)
```

--------------------------------

### Create feature branch from dev

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/CONTRIBUTING.md

Start feature development by creating a new branch from the 'dev' branch and pulling the latest changes.

```bash
git checkout dev
git pull origin dev
git checkout -b name-of-your-bugfix-or-feature
```

--------------------------------

### Import necessary libraries

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Import bbox_visualizer and cv2 for image manipulation.

```python
import bbox_visualizer as bbv
import cv2
```

--------------------------------

### Import bbox-visualizer

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Import the library into your Python script. This is a prerequisite for using any of its functions.

```python
import bbox_visualizer as bbv
```

--------------------------------

### Format and lint code with ruff

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/CONTRIBUTING.md

Use ruff to format code and run linting checks. Auto-fix issues where possible.

```bash
# Format with ruff
uv run ruff format .

# Run linting checks with ruff
uv run ruff check .

# Auto-fix ruff issues where possible
uv run ruff check --fix .

# Run tests
uv run pytest
```

--------------------------------

### Clone bbox-visualizer Repository

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/installation.md

Clone the bbox-visualizer source code from the GitHub repository.

```console
git clone git://github.com/shoumikchow/bbox-visualizer
```

--------------------------------

### Load Image and Annotations

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/multiple_objects_example.ipynb

Loads an image and its corresponding annotations from JSON. Converts the image from BGR to RGB format.

```python
import json

import cv2
import matplotlib.pyplot as plt

import bbox_visualizer as bbv

img = cv2.imread("../images/source_multiple.jpg")
annotation = json.load(open("../images/source_multiple.json"))
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
```

--------------------------------

### Prepare Bounding Box Coordinates

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Unpacks the bounding box points into individual variables (xmin, ymin, xmax, ymax) and prints them. This step prepares the coordinates for use with the bbox-visualizer functions.

```python
(xmin, ymin), (xmax, ymax) = points
print((xmin, ymin), (xmax, ymax))
```

--------------------------------

### Troubleshooting: Saving Image

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/usage.md

If the image is not displaying, use `cv2.imwrite()` to save the output image to a file. This is useful in environments without a display server.

```python
cv2.imwrite('output.jpg', image)
```

--------------------------------

### Create a feature branch

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/CONTRIBUTING.md

Create a new branch for local development, specifying the type of task.

```bash
git checkout -b task/what-you-are-doing
```

--------------------------------

### Prepare Bounding Boxes and Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/multiple_objects_example.ipynb

Extracts labels and bounding box coordinates from the annotation data. Bounding boxes are formatted as [xmin, ymin, xmax, ymax].

```python
labels = []
bboxes = []
for shape in annotation["shapes"]:
    labels.append(shape["label"])
    mins = shape["points"][0]
    maxs = shape["points"][1]
    bboxes.append(mins + maxs)
```

--------------------------------

### Draw Bounding Box and Add Label

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/index.md

This snippet shows how to draw a basic bounding box and add a text label to it on a sample image using bbox-visualizer and OpenCV.

```python
import bbox_visualizer as bbv
import cv2
import numpy as np

# Create a sample image
image = np.ones((400, 600, 3), dtype=np.uint8) * 255

# Draw a bounding box with labelbox = (100, 100, 300, 200)
image = bbv.draw_box(image, bbox, bbox_color=(0, 255, 0))
image = bbv.add_label(image, "Object", bbox)

# Display the result
cv2.imshow('Result', image)
cv2.waitKey(0)
```

--------------------------------

### Commit and push changes

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/CONTRIBUTING.md

Stage, commit, and push your changes to your feature branch on GitHub.

```bash
git add .
git commit -m "Your detailed description of your changes."
git push origin task/what-you-are-doing
```

--------------------------------

### Display Image with Flags and Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/multiple_objects_example.ipynb

Displays the image with flags and labels for multiple bounding boxes using matplotlib.

```python
plt.imshow(img_with_flags);
```

--------------------------------

### Drawing a bounding box with an opaque overlay and label inside

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws a bounding box with an opaque background and places the label inside. This ensures the label is clearly visible even on busy image backgrounds.

```APIDOC
## draw_box with opaque overlay and add_label (label inside, no background draw)

### Description
Draws a bounding box with an opaque background and places the label inside. This ensures the label is clearly visible even on busy image backgrounds.

### Method
```python
img = bbv.draw_box(image, bbox, is_opaque=True)
img = bbv.add_label(img, label, bbox, draw_bg=False, top=False)
```

### Parameters
- `image`: The input image.
- `bbox`: A tuple representing the bounding box in the format (xmin, ymin, xmax, ymax).
- `is_opaque` (bool): If True, the bounding box will have an opaque background. Defaults to False.
- `label`: The text label to be added.
- `draw_bg` (bool): If False, the background for the label will not be drawn. Defaults to True.
- `top` (bool): If False, the label is positioned inside the bounding box. Defaults to False.
```

--------------------------------

### Load Image and Annotation

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Loads an image using OpenCV and an annotation file in JSON format. Converts the image from BGR to RGB color space for compatibility with matplotlib.

```python
import json

import cv2
import matplotlib.pyplot as plt

import bbox_visualizer as bbv

img = cv2.imread("../images/source_single.jpg")
annotation = json.load(open("../images/source_single.json"))
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
```

--------------------------------

### Draw Multiple Bounding Boxes and Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws multiple bounding boxes and their corresponding labels on an image. The `bboxes` and `labels` arguments expect lists.

```python
img = bbv.draw_multiple_boxes(img, bboxes)
img = bbv.add_multiple_labels(img, labels, bboxes)
```

--------------------------------

### Draw Multiple Flags with Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws multiple bounding boxes, each with a flag-style label. Requires lists of labels and bounding boxes.

```python
img = bbv.draw_multiple_flags_with_labels(img, labels, bboxes)
```

--------------------------------

### Draw Bounding Box with Label Inside

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws a bounding box and places the label inside the box. The `top=False` argument positions the label within the box.

```python
img = bbv.draw_box(img, bbox)
img = bbv.add_label(img, label, bbox, top=False)
```

--------------------------------

### Display Image with Flag Label

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Displays the image with the flag and label using matplotlib.pyplot.

```python
plt.imshow(img_flag);
```

--------------------------------

### Draw Bounding Box with Label on Top

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws a bounding box and places the label above the box. Ensure the image object and bbox are correctly formatted.

```python
img = bbv.draw_box(img, bbox)
img = bbv.add_label(img, label, bbox, top=True)
```

--------------------------------

### Adding Simple and Multiple Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/usage.md

Add text labels to bounding boxes. Labels can be placed above or inside the box. Supports adding multiple labels for multiple boxes.

```python
# Add label above the box
bbox = (100, 100, 200, 200)
label = "Object"
image = bbv.add_label(image, label, bbox)

# Add label inside the box
image = bbv.add_label(image, label, bbox, top=False)

# Multiple labels
bboxes = [(100, 100, 200, 200), (300, 300, 400, 400)]
labels = ["Object 1", "Object 2"]
image = bbv.add_multiple_labels(image, labels, bboxes)
```

--------------------------------

### Draw Multiple Boxes

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/multiple_objects_example.ipynb

Draws multiple bounding boxes on the image using the prepared bounding box data. Prints the type of the resulting image object.

```python
img_with_boxes = bbv.draw_multiple_boxes(img, bboxes)
print(type(img_with_boxes))
```

--------------------------------

### Draw Bounding Box on Image

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Uses the `draw_box` function from the bbox-visualizer library to draw a bounding box on the image. Prints the type of the returned image object.

```python
img_with_box = bbv.draw_box(img, bbox)
print(type(img_with_box))
```

--------------------------------

### Display Image with Boxes

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/multiple_objects_example.ipynb

Displays the image with the drawn bounding boxes using matplotlib.

```python
plt.imshow(img_with_boxes);
```

--------------------------------

### Draw Bounding Box with Label Inside (T-style)

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws a bounding box and places the label inside the box, styled as a 'T'. This is useful for compact labeling.

```python
img = bbv.draw_box(img, bbox)
img = bbv.add_T_label(img, label, bbox)
```

--------------------------------

### Display Image with T-Format Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/multiple_objects_example.ipynb

Displays the image with bounding boxes and 'T' format labels using matplotlib.

```python
plt.imshow(img_with_T_labels);
```

--------------------------------

### Display Image with Label

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Displays the image with the added label using matplotlib.pyplot.

```python
plt.imshow(img_label);
```

--------------------------------

### Multiple Object Classes with Custom Colors

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/usage.md

Visualize detections from multiple object classes by assigning a unique color to each class. This helps differentiate between various object types.

```python
# Define color scheme for different classes
class_colors = {
    "person": (0, 255, 0),    # Green
    "car": (255, 0, 0),       # Blue
    "dog": (0, 0, 255),       # Red
    "cat": (255, 255, 0)      # Cyan
}

# Process detections with class-specific colors
for det in detections:
    bbox = det["bbox"]
    label = det["label"]
    color = class_colors.get(label.lower(), (128, 128, 128))

    image = bbv.draw_box(image, bbox, bbox_color=color)
    image = bbv.add_label(image, label, bbox)
```

--------------------------------

### Add labels to multiple bounding boxes

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Apply `add_label` to multiple (label, bbox) pairs using `add_multiple_labels`. Ensures lists have matching lengths and raises `ValueError` if either list is empty.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bboxes = [[50, 50, 150, 150], [200, 100, 350, 280], [400, 60, 500, 200]]
labels = ["Person", "Car", "Dog"]

# Labels above each box
image = bbv.draw_multiple_boxes(image, bboxes, bbox_color=(0, 255, 0))
image = bbv.add_multiple_labels(image, labels, bboxes, top=True)

# Labels inside boxes with custom colors
image = bbv.add_multiple_labels(
    image,
    labels,
    bboxes,
    top=False,
    text_bg_color=(50, 50, 50),
    text_color=(255, 255, 255),
)

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

--------------------------------

### Draw Opaque Bounding Box with Label

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws a bounding box with an opaque background and places the label inside. Use `draw_bg=False` in `add_label` to prevent drawing the background again if `draw_box` already handled it.

```python
img = bbv.draw_box(image, bbox, is_opaque=True)
img = bbv.add_label(img, label, bbox, draw_bg=False, top=False)
```

--------------------------------

### Extract Bounding Box Points and Label

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Extracts the bounding box coordinates and the corresponding label from the loaded annotation data. Prints the extracted points and label along with their types.

```python
points = annotation["shapes"][0]["points"]
label = annotation["shapes"][0]["label"]

print(f"Points box: {points}, {type(points)}")
print(f"Label box: {label}, {type(label)}")
```

--------------------------------

### Drawing multiple bounding boxes with labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws multiple bounding boxes and their corresponding labels on an image. This is useful for annotating several objects in a single image.

```APIDOC
## draw_multiple_boxes and add_multiple_labels

### Description
Draws multiple bounding boxes and their corresponding labels on an image. This is useful for annotating several objects in a single image.

### Method
```python
img = bbv.draw_multiple_boxes(img, bboxes)
img = bbv.add_multiple_labels(img, labels, bboxes)
```

### Parameters
- `img`: The input image.
- `bboxes`: A list of tuples, where each tuple represents a bounding box in the format (xmin, ymin, xmax, ymax).
- `labels`: A list of strings, where each string is a label corresponding to a bounding box.
```

--------------------------------

### Draw Multiple Flags with Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/multiple_objects_example.ipynb

Draws flags with labels directly onto the image for multiple bounding boxes. Prints the type of the resulting image object.

```python
img_with_flags = bbv.draw_multiple_flags_with_labels(img, labels, bboxes)
print(type(img_with_flags))
```

--------------------------------

### Add Multiple T-Format Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/multiple_objects_example.ipynb

Adds labels in a 'T' format to the bounding boxes on the image. Prints the type of the resulting image object.

```python
img_with_T_labels = bbv.add_multiple_T_labels(img_with_boxes_2, labels, bboxes)
print(type(img_with_T_labels))
```

--------------------------------

### Customizing Colors and Styles

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/usage.md

Customize the appearance of bounding boxes and labels by specifying custom colors for boxes, text, and background. This applies to various drawing functions.

```python
# Custom colors
bbox_color = (0, 255, 0)  # Green in BGR
text_color = (0, 0, 0)    # Black
bg_color = (255, 255, 255)  # White

# Draw box with custom color
image = bbv.draw_box(image, bbox, bbox_color=bbox_color)

# Add label with custom colors
image = bbv.add_label(
    image,
    label,
    bbox,
    text_color=text_color,
    text_bg_color=bg_color
)

# T-label with custom style
image = bbv.add_T_label(
    image,
    label,
    bbox,
    text_color=text_color,
    text_bg_color=bg_color
)

# Flag with custom colors
image = bbv.draw_flag_with_label(
    image,
    label,
    bbox,
    line_color=bbox_color,
    text_color=text_color,
    text_bg_color=bg_color
)

# Display the result
cv2.imshow('Image with bounding boxes', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
```

--------------------------------

### Display Image with Bounding Box

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Displays the image with the bounding box drawn on it using matplotlib.pyplot. This is typically used after drawing operations to visualize the result.

```python
plt.imshow(img_with_box);
```

--------------------------------

### Add Multiple Labels to Boxes

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/multiple_objects_example.ipynb

Adds multiple labels to the existing bounding boxes on the image. Creates a copy of the image before adding labels. Prints the type of the resulting image object.

```python
img_with_boxes_2 = img_with_boxes.copy()

img_with_boxes = bbv.add_multiple_labels(img_with_boxes, labels, bboxes)
print(type(img_with_boxes))
```

--------------------------------

### Rectangle Drawing

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/api.md

Functions for drawing rectangles and bounding boxes.

```APIDOC
## Rectangle Drawing

### Description
Functions for drawing rectangles and bounding boxes.

### Methods
- `bbox_visualizer.draw_box`
- `bbox_visualizer.draw_multiple_boxes`
- `bbox_visualizer.draw_rectangle`
- `bbox_visualizer.draw_multiple_rectangles`
```

--------------------------------

### Drawing a single bounding box with a label inside

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws a bounding box around an object and adds a label positioned inside the box. This is suitable when space is limited or for a more compact visualization.

```APIDOC
## draw_box and add_label (label inside)

### Description
Draws a bounding box around an object and adds a label positioned inside the box. This is suitable when space is limited or for a more compact visualization.

### Method
```python
img = bbv.draw_box(img, bbox)
img = bbv.add_label(img, label, bbox, top=False)
```

### Parameters
- `img`: The input image.
- `bbox`: A tuple representing the bounding box in the format (xmin, ymin, xmax, ymax).
- `label`: The text label to be added.
- `top` (bool): If False, the label is positioned inside the bounding box. Defaults to False.
```

--------------------------------

### Draw multiple bounding boxes efficiently

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Use `draw_multiple_boxes` for batched drawing of boxes, which is more efficient than individual calls. Raises `ValueError` if the list of boxes is empty.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bboxes = [
    [50,  50,  150, 150],
    [200, 100, 350, 280],
    [400, 60,  500, 200],
]

# All boxes in one call (same color)
image = bbv.draw_multiple_boxes(image, bboxes, bbox_color=(255, 100, 0), thickness=2)

# Opaque filled boxes
image = bbv.draw_multiple_boxes(image, bboxes, is_opaque=True, alpha=0.4)

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

--------------------------------

### Draw a single bounding box on an image

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Use `draw_box` to add a rectangle outline or a semi-transparent overlay to an image. Customize color, thickness, and opacity.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bbox = [100, 80, 300, 250]  # [xmin, ymin, xmax, ymax]

# Outline box (default white, thickness 3)
image = bbv.draw_box(image, bbox)

# Custom color and thickness
image = bbv.draw_box(image, bbox, bbox_color=(0, 255, 0), thickness=2)

# Semi-transparent filled box (50% opacity)
image = bbv.draw_box(image, bbox, is_opaque=True, alpha=0.5, bbox_color=(0, 200, 0))

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

--------------------------------

### Draw Flag Labels for Multiple Boxes

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Applies `draw_flag_with_label` to each (label, bbox) pair. Raises `ValueError` if lists are empty or mismatched. Configurable line, text background, and text colors.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bboxes = [[30, 80, 160, 240], [200, 70, 360, 260], [400, 90, 560, 270]]
labels = ["Cat", "Dog", "Bird"]

image = bbv.draw_multiple_flags_with_labels(
    image,
    labels,
    bboxes,
    line_color=(200, 200, 0),
    text_bg_color=(200, 200, 0),
    text_color=(0, 0, 0),
)

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

--------------------------------

### Label Drawing

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/api.md

Functions for adding labels to bounding boxes.

```APIDOC
## Label Drawing

### Description
Functions for adding labels to bounding boxes.

### Methods
- `bbox_visualizer.add_label`
- `bbox_visualizer.add_multiple_labels`
```

--------------------------------

### Context Manager for Warning Suppression

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Temporarily suppresses warnings within a `with` block, then restores the previous state automatically. Useful for localized suppression without affecting global settings.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bboxes_near_top = [[5, 5, 120, 60], [150, 2, 280, 55]]
labels = ["Label A", "Label B"]

# Suppress only for this block; state is restored after
with bbv.warnings_suppressed():
    for bbox, label in zip(bboxes_near_top, labels):
        image = bbv.draw_flag_with_label(image, label, bbox)

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

--------------------------------

### Drawing a single bounding box with a label on top

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws a bounding box around an object and adds a label positioned above the box. This is useful for clearly identifying objects.

```APIDOC
## draw_box and add_label (label on top)

### Description
Draws a bounding box around an object and adds a label positioned above the box. This is useful for clearly identifying objects.

### Method
```python
img = bbv.draw_box(img, bbox)
img = bbv.add_label(img, label, bbox, top=True)
```

### Parameters
- `img`: The input image.
- `bbox`: A tuple representing the bounding box in the format (xmin, ymin, xmax, ymax).
- `label`: The text label to be added.
- `top` (bool): If True, the label is positioned above the bounding box. Defaults to True.
```

--------------------------------

### Reconcile dev and master branches

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/CONTRIBUTING.md

After merging a feature to 'dev', reconcile 'dev' with 'master' by pulling from 'master' and pushing to 'dev'.

```bash
git checkout dev
git pull origin master
git push origin dev
```

--------------------------------

### Control Warning Messages

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/usage.md

Manage warning messages from the library. You can suppress all warnings, enable them, or use a context manager for temporary suppression.

```python
# Suppress all warnings
bbv.suppress_warnings(True)

# Enable warnings
bbv.suppress_warnings(False)

# Temporarily suppress warnings using context manager
with bbv.warnings_suppressed():
    # Warnings will be suppressed in this block
    image = bbv.draw_flag_with_label(image, "Object", bbox)
```

--------------------------------

### add_label

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Adds a text label with an optional background rectangle to a bounding box on an image. The label is placed above the box by default, but can be placed inside if space is limited.

```APIDOC
## add_label

### Description
Places a text label with an optional background rectangle either above the bounding box (default) or inside it. Automatically falls back to placing the label inside if there is not enough vertical space above the box.

### Parameters
- **image** (numpy.ndarray) - The input image.
- **label** (str) - The text label to add.
- **bbox** (list) - A list containing the bounding box coordinates in [xmin, ymin, xmax, ymax] format.
- **top** (bool, optional) - If True, attempts to place the label above the bounding box. Defaults to True.
- **draw_bg** (bool, optional) - If True, draws a background rectangle for the label. Defaults to True.
- **size** (float, optional) - The font size for the label. Defaults to 0.5.
- **thickness** (int, optional) - The thickness of the label's text and background border. Defaults to 1.
- **text_color** (tuple, optional) - The color of the text in BGR format. Defaults to (0, 0, 0) (black).
- **text_bg_color** (tuple, optional) - The color of the background rectangle in BGR format. Defaults to (255, 255, 255) (white).

### Request Example
```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bbox = [100, 80, 300, 250]

# Label above the box (default)
image = bbv.draw_box(image, bbox, bbox_color=(0, 255, 0))
image = bbv.add_label(image, "Person 0.95", bbox, top=True)

# Label inside the box, no background
image = bbv.add_label(image, "Car", bbox, top=False, draw_bg=False, text_color=(255, 255, 255))

# Custom font size and colors
image = bbv.add_label(
    image,
    "Dog",
    bbox,
    size=0.7,
    thickness=1,
    text_bg_color=(0, 0, 255),   # Red background (BGR)
    text_color=(255, 255, 255),  # White text
    top=True,
)

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

### Response
- **image** (numpy.ndarray) - The image with the label added.
```

--------------------------------

### Drawing a flag with a label

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Creates a visual representation of a flag originating from inside the object, with a label attached. This provides a distinct way to mark objects.

```APIDOC
## draw_flag_with_label

### Description
Creates a visual representation of a flag originating from inside the object, with a label attached. This provides a distinct way to mark objects.

### Method
```python
img = bbv.draw_flag_with_label(img, label, bbox)
```

### Parameters
- `img`: The input image.
- `label`: The text label to be added.
- `bbox`: A tuple representing the bounding box in the format (xmin, ymin, xmax, ymax).
```

--------------------------------

### Draw a Flag-Style Label

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Draws a vertical pole from inside the bounding box upward, with a rectangular text banner at the top. Falls back to a box + regular label if the flag would go out of frame. Pole color and text background are independently configurable. Can draw pole only by setting `write_label=False`.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bbox = [150, 150, 350, 350]

# Flag with default white colors
image = bbv.draw_flag_with_label(image, "Object", bbox)

# Custom pole/background/text colors
image = bbv.draw_flag_with_label(
    image,
    "Traffic Sign",
    bbox,
    line_color=(0, 255, 255),      # Yellow pole (BGR)
    text_bg_color=(0, 255, 255),
    text_color=(0, 0, 0),
)

# Flag without text label (pole only)
image = bbv.draw_flag_with_label(image, "", bbox, write_label=False)

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

--------------------------------

### draw_multiple_boxes / draw_multiple_rectangles

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Efficiently draws multiple bounding boxes on an image in a single batched operation. Raises ValueError if the list of bounding boxes is empty.

```APIDOC
## draw_multiple_boxes / draw_multiple_rectangles

### Description
Draws all boxes in a single batched OpenCV operation using `cv2.polylines`, making it more efficient than looping over `draw_box`. Raises `ValueError` if the list is empty.

### Parameters
- **image** (numpy.ndarray) - The input image.
- **bboxes** (list of lists) - A list where each element is a bounding box in [xmin, ymin, xmax, ymax] format.
- **bbox_color** (tuple, optional) - The color of the bounding boxes in BGR format. Defaults to (255, 255, 255) (white).
- **thickness** (int, optional) - The thickness of the bounding box outlines. Defaults to 3.
- **is_opaque** (bool, optional) - If True, draws filled semi-transparent boxes. Defaults to False.
- **alpha** (float, optional) - The opacity level for the filled boxes when `is_opaque` is True. Defaults to 0.5.

### Request Example
```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bboxes = [
    [50,  50,  150, 150],
    [200, 100, 350, 280],
    [400, 60,  500, 200],
]

# All boxes in one call (same color)
image = bbv.draw_multiple_boxes(image, bboxes, bbox_color=(255, 100, 0), thickness=2)

# Opaque filled boxes
image = bbv.draw_multiple_boxes(image, bboxes, is_opaque=True, alpha=0.4)

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

### Response
- **image** (numpy.ndarray) - The image with the bounding boxes drawn.
```

--------------------------------

### Format Bounding Box as List

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Formats the extracted bounding box coordinates into a list in the [xmin, ymin, xmax, ymax] format. This is a common input format for many visualization functions.

```python
bbox = [xmin, ymin, xmax, ymax]
print(bbox)
```

--------------------------------

### Warning Control

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/api.md

Functions to manage warning suppression within the visualizer.

```APIDOC
## Warning Control

### Description
Functions to manage warning suppression within the visualizer.

### Methods
- `bbox_visualizer.suppress_warnings`
- `bbox_visualizer.warnings_suppressed`
```

--------------------------------

### Drawing multiple bounding boxes with T-shaped labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws multiple bounding boxes and attaches T-shaped labels to them. This is an alternative labeling style for multiple objects.

```APIDOC
## draw_multiple_boxes and add_multiple_T_labels

### Description
Draws multiple bounding boxes and attaches T-shaped labels to them. This is an alternative labeling style for multiple objects.

### Method
```python
img = bbv.draw_multiple_boxes(img, bboxes)
img = bbv.add_multiple_T_labels(img, labels, bboxes)
```

### Parameters
- `img`: The input image.
- `bboxes`: A list of tuples, where each tuple represents a bounding box in the format (xmin, ymin, xmax, ymax).
- `labels`: A list of strings, where each string is a label corresponding to a bounding box.
```

--------------------------------

### Draw Multiple Bounding Boxes with T-style Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws multiple bounding boxes, each with a T-style label inside. This function is suitable for images with numerous objects to label.

```python
img = bbv.draw_multiple_boxes(img, bboxes)
img = bbv.add_multiple_T_labels(img, labels, bboxes)
```

--------------------------------

### Drawing multiple flags with labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws multiple flags originating from objects, each with an associated label. This provides a clear and distinct way to annotate multiple items.

```APIDOC
## draw_multiple_flags_with_labels

### Description
Draws multiple flags originating from objects, each with an associated label. This provides a clear and distinct way to annotate multiple items.

### Method
```python
img = bbv.draw_multiple_flags_with_labels(img, labels, bboxes)
```

### Parameters
- `img`: The input image.
- `labels`: A list of strings, where each string is a label corresponding to a bounding box.
- `bboxes`: A list of tuples, where each tuple represents a bounding box in the format (xmin, ymin, xmax, ymax).
```

--------------------------------

### Drawing Single and Multiple Boxes

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/usage.md

Draw single or multiple bounding boxes on an image. The library supports the standard (x1, y1, x2, y2) format for bounding boxes.

```python
# Single box
bbox = (100, 100, 200, 200)  # (x1, y1, x2, y2) format
image = bbv.draw_box(image, bbox)

# Multiple boxes
bboxes = [(100, 100, 200, 200), (300, 300, 400, 400)]
image = bbv.draw_multiple_boxes(image, bboxes)

# Filled box with transparency
image = bbv.draw_box(image, bbox, is_opaque=True, alpha=0.5)
```

--------------------------------

### Draw Flag with Label

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/README.md

Draws a bounding box with a label that resembles a flag, with the pole originating from inside the object's bounding box.

```python
img = bbv.draw_flag_with_label(img, label, bbox)
```

--------------------------------

### add_multiple_labels

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Applies the `add_label` function to multiple bounding boxes and their corresponding labels. It requires that the lists of labels and bounding boxes have the same length and raises ValueError if either list is empty.

```APIDOC
## add_multiple_labels

### Description
Applies `add_label` to each (label, bbox) pair. Validates that the two lists have the same length and raises `ValueError` if either is empty.

### Parameters
- **image** (numpy.ndarray) - The input image.
- **labels** (list of str) - A list of text labels.
- **bboxes** (list of lists) - A list where each element is a bounding box in [xmin, ymin, xmax, ymax] format.
- **top** (bool, optional) - If True, attempts to place the labels above the bounding boxes. Defaults to True.
- **draw_bg** (bool, optional) - If True, draws a background rectangle for each label. Defaults to True.
- **size** (float, optional) - The font size for the labels. Defaults to 0.5.
- **thickness** (int, optional) - The thickness of the labels' text and background borders. Defaults to 1.
- **text_color** (tuple, optional) - The color of the text in BGR format. Defaults to (0, 0, 0) (black).
- **text_bg_color** (tuple, optional) - The color of the background rectangles in BGR format. Defaults to (255, 255, 255) (white).

### Request Example
```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bboxes = [[50, 50, 150, 150], [200, 100, 350, 280], [400, 60, 500, 200]]
labels = ["Person", "Car", "Dog"]

# Labels above each box
image = bbv.draw_multiple_boxes(image, bboxes, bbox_color=(0, 255, 0))
image = bbv.add_multiple_labels(image, labels, bboxes, top=True)

# Labels inside boxes with custom colors
image = bbv.add_multiple_labels(
    image,
    labels,
    bboxes,
    top=False,
    text_bg_color=(50, 50, 50),
    text_color=(255, 255, 255),
)

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

### Response
- **image** (numpy.ndarray) - The image with the labels added.
```

--------------------------------

### draw_box / draw_rectangle

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Draws a rectangle outline or a semi-transparent filled overlay around an object in an image. These functions are aliases for each other.

```APIDOC
## draw_box / draw_rectangle

### Description
Draws a rectangle outline (or filled semi-transparent overlay) around an object. `draw_box` and `draw_rectangle` are identical aliases.

### Parameters
- **image** (numpy.ndarray) - The input image.
- **bbox** (list) - A list containing the bounding box coordinates in [xmin, ymin, xmax, ymax] format.
- **bbox_color** (tuple, optional) - The color of the bounding box in BGR format. Defaults to (255, 255, 255) (white).
- **thickness** (int, optional) - The thickness of the bounding box outline. Defaults to 3.
- **is_opaque** (bool, optional) - If True, draws a filled semi-transparent box. Defaults to False.
- **alpha** (float, optional) - The opacity level for the filled box when `is_opaque` is True. Defaults to 0.5.

### Request Example
```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bbox = [100, 80, 300, 250]  # [xmin, ymin, xmax, ymax]

# Outline box (default white, thickness 3)
image = bbv.draw_box(image, bbox)

# Custom color and thickness
image = bbv.draw_box(image, bbox, bbox_color=(0, 255, 0), thickness=2)

# Semi-transparent filled box (50% opacity)
image = bbv.draw_box(image, bbox, is_opaque=True, alpha=0.5, bbox_color=(0, 200, 0))

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

### Response
- **image** (numpy.ndarray) - The image with the bounding box drawn.
```

--------------------------------

### Add Label in T Format

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Adds a text label to the bounding box in a 'T' format using the `add_T_label` function. Prints the type of the resulting image.

```python
img_T_label = bbv.add_T_label(img_with_box_2, label, bbox)
print(type(img_T_label))
```

--------------------------------

### draw_multiple_flags_with_labels

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Applies the `draw_flag_with_label` function to multiple bounding boxes and their corresponding labels. This is useful for annotating several objects in an image with flag-style labels.

```APIDOC
## `draw_multiple_flags_with_labels` — Draw Flag Labels for Multiple Boxes

Applies `draw_flag_with_label` to each (label, bbox) pair. Raises `ValueError` if lists are empty or mismatched.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bboxes = [[30, 80, 160, 240], [200, 70, 360, 260], [400, 90, 560, 270]]
labels = ["Cat", "Dog", "Bird"]

image = bbv.draw_multiple_flags_with_labels(
    image,
    labels,
    bboxes,
    line_color=(200, 200, 0),
    text_bg_color=(200, 200, 0),
    text_color=(0, 0, 0),
)

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

--------------------------------

### Add T-Shaped Labels to Multiple Boxes

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Applies `add_T_label` to each (label, bbox) pair. Raises `ValueError` if lists are empty or mismatched. Configure text background and text colors.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bboxes = [[50, 100, 180, 250], [220, 90, 380, 260], [410, 80, 550, 230]]
labels = ["Pedestrian", "Cyclist", "Vehicle"]

image = bbv.draw_multiple_boxes(image, bboxes)
image = bbv.add_multiple_T_labels(
    image,
    labels,
    bboxes,
    text_bg_color=(255, 255, 200),
    text_color=(0, 0, 0),
)

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

--------------------------------

### Globally Toggle Warning Messages

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Enables or disables logging warnings emitted when a label style (T or Flag) goes out of the image frame and falls back to a simpler style. Use `suppress_warnings(True)` to disable and `suppress_warnings(False)` to re-enable.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bbox = [10, 10, 100, 50]   # Near top edge — T/flag label will overflow

# Suppress warnings globally
bbv.suppress_warnings(True)
image = bbv.add_T_label(image, "Edge Object", bbox)  # No warning logged

# Re-enable warnings
bbv.suppress_warnings(False)
```

--------------------------------

### Display Image with T Label

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Displays the image with the 'T' formatted label using matplotlib.pyplot.

```python
plt.imshow(img_T_label);
```

--------------------------------

### Add Label to Bounding Box

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/examples/single_object_example.ipynb

Adds a text label to the bounding box on the image using the `add_label` function. Creates a copy of the image before adding the label to preserve the original. Prints the type of the resulting image.

```python
img_with_box_2 = img_with_box.copy()

img_label = bbv.add_label(img_with_box, label, bbox)
print(type(img_label))
```

--------------------------------

### Add a text label to a bounding box

Source: https://context7.com/shoumikchow/bbox-visualizer/llms.txt

Use `add_label` to place text above or inside a bounding box. The function automatically handles fallback positioning if space above is insufficient. Customize text and background colors, size, and thickness.

```python
import bbox_visualizer as bbv
import cv2

image = cv2.imread("image.jpg")
bbox = [100, 80, 300, 250]

# Label above the box (default)
image = bbv.draw_box(image, bbox, bbox_color=(0, 255, 0))
image = bbv.add_label(image, "Person 0.95", bbox, top=True)

# Label inside the box, no background
image = bbv.add_label(image, "Car", bbox, top=False, draw_bg=False, text_color=(255, 255, 255))

# Custom font size and colors
image = bbv.add_label(
    image,
    "Dog",
    bbox,
    size=0.7,
    thickness=1,
    text_bg_color=(0, 0, 255),   # Red background (BGR)
    text_color=(255, 255, 255),  # White text
    top=True,
)

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

--------------------------------

### Special Labels

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/api.md

Functions for drawing special labels and flags with labels.

```APIDOC
## Special Labels

### Description
Functions for drawing special labels and flags with labels.

### Methods
- `bbox_visualizer.add_T_label`
- `bbox_visualizer.add_multiple_T_labels`
- `bbox_visualizer.draw_flag_with_label`
- `bbox_visualizer.draw_multiple_flags_with_labels`
```

--------------------------------

### Special Label Styles: T-shaped and Flag

Source: https://github.com/shoumikchow/bbox-visualizer/blob/master/docs/usage.md

Utilize special label styles like T-shaped labels and flag-style labels for enhanced visualization. Supports adding multiple labels of these styles.

```python
# T-shaped label
image = bbv.add_T_label(image, "Object", bbox)

# Flag-style label
image = bbv.draw_flag_with_label(image, "Object", bbox)

# Multiple T-shaped labels
image = bbv.add_multiple_T_labels(image, labels, bboxes)

# Multiple flag labels
image = bbv.draw_multiple_flags_with_labels(image, labels, bboxes)
```