Question

首先，我是编程新手，但我想学习特别是python。我在动画和CGI方面的背景。

我在Windows上安装了python 2.7和openCV x64。我测试了他们有光学流程示例（opt_flow.py）（绿色箭头）我喜欢它，但我想了解如何将数据作为值。我对看到相机输出或绿色箭头不感兴趣我只是想让数据以后再使用它。有没有办法做到这一点？ 例如：x，y的值和绿色箭头的长度。

谢谢大家

Answer 1

您可以在 opt_flow.py 的draw_flow功能中获取光流向量（绿色箭头）。我将如何做到这一点：

#!/usr/bin/env python

'''
example to show optical flow

USAGE: opt_flow.py [<video_source>]

Keys:
 1 - toggle HSV flow visualization
 2 - toggle glitch

Keys:
    ESC    - exit
'''

# Python 2/3 compatibility
from __future__ import print_function

import numpy as np
import math
import cv2
import video


def draw_flow(img, flow, step=16):
    global arrows
    h, w = img.shape[:2]
    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int)
    fx, fy = flow[y,x].T
    lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2)
    lines = np.int32(lines + 0.5)
    vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
    cv2.polylines(vis, lines, 0, (0, 255, 0))
    for (x1, y1), (x2, y2) in lines:
        arrows.append([x1,y1, math.sqrt((x2-x1)*(x2-x1) + (y2-y1)*(y2-y1))])
        cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
    return vis


def draw_hsv(flow):
    h, w = flow.shape[:2]
    fx, fy = flow[:,:,0], flow[:,:,1]
    ang = np.arctan2(fy, fx) + np.pi
    v = np.sqrt(fx*fx+fy*fy)
    hsv = np.zeros((h, w, 3), np.uint8)
    hsv[...,0] = ang*(180/np.pi/2)
    hsv[...,1] = 255
    hsv[...,2] = np.minimum(v*4, 255)
    bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
    return bgr


def warp_flow(img, flow):
    h, w = flow.shape[:2]
    flow = -flow
    flow[:,:,0] += np.arange(w)
    flow[:,:,1] += np.arange(h)[:,np.newaxis]
    res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)
    return res

if __name__ == '__main__':
    import sys
    print(__doc__)
    try:
        fn = sys.argv[1]
    except IndexError:
        fn = 0

    arrows = []
    cam = video.create_capture(fn)
    ret, prev = cam.read()
    prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)
    show_hsv = False
    show_glitch = False
    cur_glitch = prev.copy()

    while True:
        ret, img = cam.read()
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, None, 0.5, 3, 15, 3, 5, 1.2, 0)
        prevgray = gray

        arrows.clear()
        finalImg = draw_flow(gray,flow)
        print(arrows)
        cv2.imshow('flow', finalImg)
        if show_hsv:
            cv2.imshow('flow HSV', draw_hsv(flow))
        if show_glitch:
            cur_glitch = warp_flow(cur_glitch, flow)
            cv2.imshow('glitch', cur_glitch)

        ch = cv2.waitKey(5)
        if ch == 27:
            break
        if ch == ord('1'):
            show_hsv = not show_hsv
            print('HSV flow visualization is', ['off', 'on'][show_hsv])
        if ch == ord('2'):
            show_glitch = not show_glitch
            if show_glitch:
                cur_glitch = img.copy()
            print('glitch is', ['off', 'on'][show_glitch])
    cv2.destroyAllWindows()

在上面的代码中，我将光流向量（起点坐标和向量长度）保存在全局变量arrows中，如下所示：

arrows.append([x1,y1, math.sqrt((x2-x1)*(x2-x1) + (y2-y1)*(y2-y1))])

(x1, y1)箭头的起点和(x2, y2)箭头的终点。

希望它有所帮助。

使用Python openCV从实时馈送（网络摄像头）中提取光流作为数据（数字）

1 个答案: