Python Docs

Installation

First, follow the instructions in the Installation section to install retinify.
Then, install the Python bindings using:

pip install git+https://github.com/retinify/retinify-python.git

Writing Python code

The Python bindings of retinify are designed to use NumPy arrays as the primary input and output format.
Images loaded using libraries such as Pillow or opencv-python can be passed directly as numpy.ndarray objects.

To perform stereo matching with rectified stereo images, use the following code:

import numpy as np
from PIL import Image
from retinify import Pipeline
 
# LOAD RECTIFIED STEREO INPUT IMAGES
left = np.asarray(Image.open("path/to/left.png").convert("RGB"))
right = np.asarray(Image.open("path/to/right.png").convert("RGB"))
 
# CREATE THE STEREO MATCHING PIPELINE
pipe = Pipeline()
 
# INITIALIZE THE PIPELINE
pipe.initialize(image_width=left.shape[1], 
                image_height=left.shape[0])
 
# EXECUTE STEREO MATCHING
pipe.execute(left, right)
 
# RETRIEVE DISPARITY
disparity = pipe.retrieve_disparity()

When initializing the pipeline, you can provide calibration parameters to enable the following features:

• Distortion correction and rectification
• Depth and point cloud generation

To perform stereo matching with non-rectified stereo images, use the following code:

import numpy as np
from PIL import Image
from retinify import Pipeline, load_calibration_parameters, PixelFormat, DepthMode
 
# LOAD NON-RECTIFIED STEREO INPUT IMAGES
left = np.asarray(Image.open("path/to/left.png").convert("RGB"))
right = np.asarray(Image.open("path/to/right.png").convert("RGB"))
 
# LOAD CALIBRATION PARAMETERS
calib_params = load_calibration_parameters("path/to/calib.json")
 
# CREATE STEREO MATCHING PIPELINE
pipe = Pipeline()
 
# INITIALIZE THE PIPELINE WITH CALIBRATION PARAMETERS
pipe.initialize(image_width=left.shape[1], 
                image_height=left.shape[0],
                pixel_format=PixelFormat.RGB8,
                depth_mode=DepthMode.ACCURATE,
                calibration_parameters=calib_params)
 
# EXECUTE STEREO MATCHING
pipe.execute(left, right)
 
# RETRIEVE RECTIFIED LEFT IMAGE
left_rectified = pipe.retrieve_rectified_left_image()
 
# RETRIEVE DISPARITY
disparity = pipe.retrieve_disparity()
 
# RETRIEVE DEPTH
depth = pipe.retrieve_depth()
 
# RETRIEVE POINT CLOUD
point_cloud = pipe.retrieve_point_cloud()