Question about cartToPolar in different version of opencv

asked 2017-02-08 04:45:50 -0500

mrabo gravatar image
  • OpenCV => 3.2 (brew installed)
  • Operating System / Platform => macOS 10.12
  • Compiler => ipython

i use ipython to learn optical flow and when i try to convert two direction of dense optical flow into a colorful one i found that ver 3.2 could not convert image correctly (or maybe there are some delay in my loop?) but when i use ver 2.4, everything is fine, and image is converted very fast. could you help me find the problem?

here is my code

import numpy as np
import cv2
import time

def modify_image(img):
    h = img.shape[0]
    w = img.shape[1]
    # vertical
    if w < h:
        resize = (256, int(256 * 1.0 / w * h))  # (w, h)
    # horizontal
    else:
        resize = (int(256 * 1.0 / h * w), 256)  # (w, h)
    # modify
    img = cv2.resize(img, resize)
    return img


def color_to_grey(img_clr):
    img_gry = cv2.cvtColor(img_clr, cv2.COLOR_BGR2GRAY)
    return img_gry


def flow_to_image(flw, flw_bnd=15):
    bnd_arr = np.full_like(flw, flw_bnd)

    img_flw = flw.copy()
    img_flw[(img_flw < -flw_bnd)] = -flw_bnd
    img_flw[(img_flw > +flw_bnd)] = +flw_bnd
    img_flw = ((img_flw + bnd_arr) / (2 * bnd_arr) * 255).astype(np.uint8)
    return img_flw


cap = cv2.VideoCapture(0)


cv2.namedWindow('img_clr') 
cv2.namedWindow('img_gry') 
cv2.namedWindow('dof_gry_x') 
cv2.namedWindow('dof_gry_y') 
cv2.namedWindow('dof_hsv') 
cv2.namedWindow('dof_bgr') 


cv2.moveWindow('img_clr', 300, 125)
cv2.moveWindow('img_gry', 775, 125)
cv2.moveWindow('dof_gry_x', 300, 415)
cv2.moveWindow('dof_gry_y', 775, 415) 
cv2.moveWindow('dof_hsv', 300, 705) 
cv2.moveWindow('dof_bgr', 775, 705) 

img_gry_prv = None

while True:
    # Capture frame-by-frame
    ret, frm = cap.read()

    # img_clr
    img_clr = modify_image(frm)
    # img_gry
    img_gry_nxt = color_to_grey(img_clr)

    # dof_gry_x dof_gry_y
    if img_gry_prv is None:
        img_gry_prv = img_gry_nxt
    dof =  cv2.calcOpticalFlowFarneback(prev=img_gry_prv, next=img_gry_nxt, flow=None, pyr_scale=0.500, levels=3, winsize=10, iterations=1, poly_n=7, poly_sigma=1.5, flags=cv2.OPTFLOW_FARNEBACK_GAUSSIAN)
    img_gry_prv = img_gry_nxt

    dof_x = dof[..., 0]
    dof_y = dof[..., 1]

    dof_gry_x = flow_to_image(dof_x)
    dof_gry_y = flow_to_image(dof_y)

    # dof_hsv
    mag, ang = cv2.cartToPolar(dof_x, dof_y)
    dof_hsv = np.zeros_like(img_clr)
    dof_hsv[...,0] = ang*180/np.pi/2
    dof_hsv[...,1] = 255
    dof_hsv[...,2] = cv2.normalize(mag,None,0,255,cv2.NORM_MINMAX)

    # dof_bgr
    dof_bgr = cv2.cvtColor(dof_hsv,cv2.COLOR_HSV2BGR)
    # display
    cv2.imshow('img_clr',img_clr)
    cv2.imshow('img_gry',img_gry_nxt)
    cv2.imshow('dof_gry_x',dof_gry_x)
    cv2.imshow('dof_gry_y',dof_gry_y)
    cv2.imshow('dof_hsv',dof_hsv)
    cv2.imshow('dof_bgr',dof_bgr)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
    time.sleep(0.1)
cv2.destroyAllWindows()
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