禁用python中的opencv警告

2024-03-29 09:25:18 发布

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我下载OpenCV(OpenCV-2.3.1-win-超级包.exe)并在Python2.6上使用它。在

我使用OpenCV\samples\python目录中的find_obj.py。在

一切都很神奇,但即使我使用try except块包装代码,如果代码引发错误,OpenCV也会打印错误。在

OpenCV Error: Bad flag (parameter or structure field) (Unrecognized or unsupported array type) in unknown function, file ......\OpenCV-2.3.1\modules\core\src\array.cpp, line 2482

那么我怎样才能禁用OpenCV警告消息呢。在

编辑:

代码如下:

import numpy as np
import cv2
from functools import partial

help_message = '''SURF image match 

USAGE: findobj.py [ <image1> <image2> ]
'''

FLANN_INDEX_KDTREE = 1  # bug: flann enums are missing

flann_params = dict(algorithm = FLANN_INDEX_KDTREE, trees = 4)

def anorm(a):
    return np.sqrt( anorm2(a) )

def match_bruteforce(desc1, desc2, r_threshold = 0.75):
    res = []
    for i in xrange(len(desc1)):
        dist = anorm( desc2 - desc1[i] )
        n1, n2 = dist.argsort()[:2]
        r = dist[n1] / dist[n2]
        if r < r_threshold:
            res.append((i, n1))
    return np.array(res)


def match_flann(desc1, desc2, r_threshold = 0.6):
    flann = cv2.flann_Index(desc2, flann_params)
    idx2, dist = flann.knnSearch(desc1, 2, params = {}) # bug: need to provide empty dict
    mask = dist[:,0] / dist[:,1] < r_threshold
    idx1 = np.arange(len(desc1))
    pairs = np.int32( zip(idx1, idx2[:,0]) )
    return pairs[mask]


def draw_match(img1, img2, p1, p2, status = None, H = None):
    h1, w1 = img1.shape[:2]
    h2, w2 = img2.shape[:2]
    vis = np.zeros((max(h1, h2), w1+w2), np.uint8)
    vis[:h1, :w1] = img1
    vis[:h2, w1:w1+w2] = img2
    vis = cv2.cvtColor(vis, cv2.COLOR_GRAY2BGR)

    if H is not None:
        corners = np.float32([[0, 0], [w1, 0], [w1, h1], [0, h1]])
        corners = np.int32( cv2.perspectiveTransform(corners.reshape(1, -1, 2), H).reshape(-1, 2) + (w1, 0) )
        cv2.polylines(vis, [corners], True, (255, 255, 255))

    if status is None:
        status = np.ones(len(p1), np.bool_)
    green = (0, 255, 0)
    red = (0, 0, 255)
    for (x1, y1), (x2, y2), inlier in zip(np.int32(p1), np.int32(p2), status):
        col = [red, green][inlier]
        if inlier:
            cv2.line(vis, (x1, y1), (x2+w1, y2), col)
            cv2.circle(vis, (x1, y1), 2, col, -1)
            cv2.circle(vis, (x2+w1, y2), 2, col, -1)
        else:
            r = 2
            thickness = 3
            cv2.line(vis, (x1-r, y1-r), (x1+r, y1+r), col, thickness)
            cv2.line(vis, (x1-r, y1+r), (x1+r, y1-r), col, thickness)
            cv2.line(vis, (x2+w1-r, y2-r), (x2+w1+r, y2+r), col, thickness)
            cv2.line(vis, (x2+w1-r, y2+r), (x2+w1+r, y2-r), col, thickness)
    return vis


def search(fn1, fn2):
    try:        
        img1 = cv2.imread(fn1, 0)
        img2 = cv2.imread(fn2, 0)

        surf = cv2.SURF(1000)
        kp1, desc1 = surf.detect(img1, None, False)
        kp2, desc2 = surf.detect(img2, None, False)
        desc1.shape = (-1, surf.descriptorSize())
        desc2.shape = (-1, surf.descriptorSize())

        def match_and_draw(match, r_threshold):
            try:
                m = match(desc1, desc2, r_threshold)
                matched_p1 = np.array([kp1[i].pt for i, j in m])
                matched_p2 = np.array([kp2[j].pt for i, j in m])
                H, status = cv2.findHomography(matched_p1, matched_p2, cv2.RANSAC, 5.0)
                vis = draw_match(img1, img2, matched_p1, matched_p2, status, H)
                return vis
            except:
                pass

        vis_brute = match_and_draw( match_bruteforce, .9 )
        #vis_flann = match_and_draw( match_flann, 0.6 ) # flann tends to find more distant second # neighbours, so r_threshold is decreased
        if vis_brute != None:
            cv2.imshow('find_obj SURF', vis_brute)
            #cv2.imshow('find_obj SURF flann', vis_flann)
            return True
        else:
            return False
    except:
        return False


print search('obj.png', 'pass.png')
print search('obj.png', 'fail.png')

它搜索图像(目标.png)在更大的图像中,如果搜索成功,一切正常,但如果失败,它总是打印错误。在

编辑2

这是dll列表

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Tags: nonethresholdreturndistmatchnpcolcv2