kittitool.py

#! /usr/bin/python
# Author: Ruoteng Li
# Date: 6th Aug 2016

import numpy as np
import png
import matplotlib.pyplot as plt
import matplotlib.colors as cl
import flowlib as fl


def flow_read(flow_file):
    """
    Read kitti flow from .png file
    :param flow_file:
    :return:
    """
    flow_object = png.Reader(filename=flow_file)
    flow_direct = flow_object.asDirect()
    flow_data = list(flow_direct[2])
    (w, h) = flow_direct[3]['size']
    flow = np.zeros((h, w, 3), dtype=np.float64)
    for i in range(len(flow_data)):
        flow[i, :, 0] = flow_data[i][0::3]
        flow[i, :, 1] = flow_data[i][1::3]
        flow[i, :, 2] = flow_data[i][2::3]

    invalid_idx = (flow[:, :, 2] == 0)
    flow[:, :, 0:2] = (flow[:, :, 0:2] - 2 ** 15) / 64.0
    flow[invalid_idx, 0] = 0
    flow[invalid_idx, 1] = 0
    return flow


def flow_visualize(flow, save_filename=None, mode='Y'):
    if mode == 'Y':
        # Ccbcr color wheel
        img = fl.flow_to_image(flow)
        plt.imshow(img)
        plt.show()
    elif mode == 'RGB':
        (h, w) = flow.shape[0:2]
        du = flow[:, :, 0]
        dv = flow[:, :, 1]
        valid = flow[:, :, 2]
        max_flow = max(np.max(du), np.max(dv))
        img = np.zeros((h, w, 3), dtype=np.float64)
        # angle layer
        img[:, :, 0] = np.arctan2(dv, du) / (2 * np.pi)
        # magnitude layer, normalized to 1
        img[:, :, 1] = np.sqrt(du * du + dv * dv) * 8 / max_flow
        # phase layer
        img[:, :, 2] = 8 - img[:, :, 1]
        # clip to [0,1]
        small_idx = img[:, :, 0:3] < 0
        large_idx = img[:, :, 0:3] > 1
        img[small_idx] = 0
        img[large_idx] = 1
        # convert to rgb
        img = cl.hsv_to_rgb(img)
        # remove invalid point
        img[:, :, 0] = img[:, :, 0] * valid
        img[:, :, 1] = img[:, :, 1] * valid
        img[:, :, 2] = img[:, :, 2] * valid
        # show
        plt.imshow(img)
        if save_filename is not None:
            plt.savefig(save_filename, bbox_inches='tight')
        else:
            plt.show()

    return