使用颜色模型可视化光流

Question

我已经实现了一个密集的光流算法,我想用以下颜色模型可视化它

(颜色表示某点的流动方向,强度表示位移矢量的长度)

我已经实现了可视化的脏版本

def visualizeFlow(u, v):
    colorModel = cv2.imread('../colormodel.png')
    colorModelCenter = (colorModel.shape[0]/2, colorModel.shape[1]/2)
    res = np.zeros((u.shape[0], u.shape[1], 3), dtype=np.uint8)
    mag = np.max(np.sqrt(u**2 + v**2)) 
    if mag == 0:
        return res, colorModel
    for i in xrange(res.shape[0]):
        for j in xrange(res.shape[1]):
            res[i, j] = colorModel[
                        colorModelCenter[0] + (v[i, j]/mag*colorModelCenter[0]),
                        colorModelCenter[1] + (u[i, j]/mag*colorModelCenter[1])
                    ]
    return res, colorModel

它在一般案例图片中产生很好但是它确实很慢

所以我的问题是,任何人都可以帮我更快地实现这种可视化 如果有人知道可视化密集流动的更好方法,那么它可能很酷

Answer 1

OpenCV教程中的代码:

import cv2
import numpy as np

# Use Hue, Saturation, Value colour model 
hsv = np.zeros(im1.shape, dtype=np.uint8)
hsv[..., 1] = 255

mag, ang = cv2.cartToPolar(flow[..., 0], flow[..., 1])
hsv[..., 0] = ang * 180 / np.pi / 2
hsv[..., 2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
cv2.imshow("colored flow", bgr)
cv2.waitKey(0)
cv2.destroyAllWindows()

Answer 2

您可能想检查一下很棒的flow_vis包裹。引用他们的页面：

1. pip install flow_vis

2. 然后在你的代码中：

import flow_vis
flow_color = flow_vis.flow_to_color(flow_uv, convert_to_bgr=False)