stereo.py

#!/usr/bin/python

# You need stereovision package to run this. Try "sudo pip install stereovision"

import cv2
from stereovision.blockmatchers import StereoBM, StereoSGBM
from stereovision.calibration import StereoCalibration
from stereovision.stereo_cameras import CalibratedPair
from stereovision.ui_utils import STEREO_BM_FLAG, BMTuner

# Specify paths to left and right camera images below. They must be calibrated and rectified.
image_pair = [cv2.imread(image) for image in ["left.pnm", "right.pnm"]]

block_matcher = StereoBM() # or StereoSGBM() which is a semi-global block matcher

# You will need to tune the block matcher to get better results
# This blog post describes how to do it:
# http://erget.wordpress.com/2014/03/13/building-an-interactive-gui-with-opencv/

bm_tuner_gui = BMTuner(block_matcher, None, image_pair)




# Generate point cloud from the disparity map and generate a point cloud in the PLY format to view in MeshLab
# We need Disparity to depth mapping matrix (4x4 matrix, Q)

# disparity = block_matcher.get_disparity(image_pair)
# points = block_matcher.get_3d(disparity,calibration.disp_to_depth_mat) 
# colors = cv2.cvtColor(image_pair[0], cv2.COLOR_BGR2RGB)
# pcloud = PointCloud(points, colors)

# pcloud = pcloud.filter_infinity()
# pcloud.write_ply(args.output)