python - 使用 Python openCV 从实时提要(网络摄像头)中提取光流作为数据(数字)

Question

首先，我是编程新手，但我特别想学习 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。我测试了他们拥有的光流示例 (opt_flow.py)(绿色箭头)我喜欢这样，但我试图了解如何将数据作为值输出。我对看到相机输出或绿色箭头不感兴趣我只是想输出数据以供日后使用。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 函数中获取光流矢量(绿色箭头)。这是我的做法:

#!/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，我将光流矢量(起点坐标和矢量长度)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))])

用 (x1, y1) 箭头的起点和 (x2, y2) 箭头的终点。

希望对您有所帮助。