pinhole-distance 0.1.0

A Python library for object distance calculations in images using pinhole projection.

pinhole-distance

A Python library for pinhole distance calculations.

Installation

pip install pinhole-distance

Usage

from pinhole_distance import hello
print(hello())

API Reference

class Lens

Represents a camera lens.

Attributes:

• focal_length (float): Focal length of the lens in millimeters.
• pixel_width_um (float): Width of a single pixel in micrometers (μm).
• distortion_table (Optional[dict[float, float]]): Optional mapping of observed radius (pixels or mm) to distortion correction factor (for fisheye lenses).

Example:

lens = Lens(focal_length=4.0, pixel_width_um=1.4, distortion_table={0.0: 1.0, 100.0: 0.98})

---

class Sensor

Represents a camera sensor.

Attributes:

• pixel_height_um (float): Height of a single pixel in micrometers (μm).
• resolution (tuple[int, int]): Sensor resolution as (width_px, height_px).

Example:

sensor = Sensor(pixel_height_um=1.4, resolution=(1920, 1080))

---

class Package

Combines a Lens and a Sensor for distance and dimension calculations.

Attributes:

• lens (Lens): The lens used.
• sensor (Sensor): The sensor used.

Methods:

• distance_to_object(actual_dimension: float, observed_dimension_px: float) -> float
  Returns the distance (in meters) to an object given its actual dimension (height or width, in meters) and observed dimension in the image.
• object_dimension_at_distance(distance: float, observed_dimension_px: float) -> float
  Returns the actual dimension (in meters) of an object at a given distance (in meters), given its observed dimension in the image.

Example:

pkg = Package(lens, sensor)
dist = pkg.distance_to_object(actual_dimension=0.2, observed_dimension_px=150)
dimension = pkg.object_dimension_at_distance(distance=1.0, observed_dimension_px=150)

Example: Using the OV5647 Package

from pinhole_distance import ov5647

distance = ov5647.distance_to_object(
    dimension='y',
    actual_dimension=0.1e-3,  # 0.1 mm in meters
    observed_dimension_px=160
)
print(f"Distance to object: {distance:.4f} meters")

Output: Distance to object: 0.0011 meters, or 1.1mm.

Example: USB Pinhole with manually checked distances

The following example computes the distance to a person with:

• Known width of 21" (0.5334m)
• Observed width of 70 pixels, using YOLO bounding box

I know from measuring that the person was 5m away.

from pinhole_distance import usb_pinhole

distance = usb_pinhole.distance_to_object(
    dimension='x',
    actual_dimension=0.5334,
    observed_dimension_px=70
)
print(f"Distance to object: {distance:.4f} meters")

The output is a distance of 4.8986 meters, or roughly a 2% error.

Publishing

• Build: python -m build
• Publish: twine upload dist/*

License

MIT