【发布时间】:2018-10-19 14:44:30
【问题描述】:
我正在使用内置的opencv 函数打开图像,删除背景,裁剪图像,然后计算文件的直方图,将其与不同文件的直方图进行比较。
为了比较直方图,我使用 BGR 颜色空间和函数:
cv2.compareHist(hist_1, hist_2, cv2.HISTCMP_CORREL)
我的代码是
def cv_histogram(image, channels=[0, 1, 2], hist_size=[10, 10, 10], hist_range=[0, 256, 0, 256, 0, 256], hist_type='BGR'):
#convert to different color space if needed
if hist_type=='HSV': image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
elif hist_type=='GRAY': image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
elif hist_type=='RGB': image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image_hist = cv2.calcHist([image], channels, None, hist_size, hist_range)
image_hist = cv2.normalize(image_hist, image_hist).flatten()
return image_hist
def cv_compare_images_histogram(img_base, img_compare, method='correlation'):
hist_1 = cv_histogram(img_base)
hist_2 = cv_histogram(img_compare)
if method == "intersection":
comparison = cv2.compareHist(hist_1, hist_2, cv2.HISTCMP_INTERSECT)
else:
comparison = cv2.compareHist(hist_1, hist_2, cv2.HISTCMP_CORREL)
return comparison
im1 = image_remove_background(cv2.imread("1.jpg"), bg_lower_bgr, bg_upper_bgr)
im2 = image_remove_background(cv2.imread("2.jpg"), bg_lower_bgr, bg_upper_bgr)
sim = cv_compare_images_histogram(im1, im2)
img_new = image_stack(im1, im2)
cv2.imshow('img_new', img_new)
print("Histogram similarity is: ", sim)
如下面的屏幕所示,图像具有不同的颜色/对象,但我收到了非常高的相关性:0.9198019904818888
脚本适用于大多数文件,知道为什么会有如此连线的结果吗?
【问题讨论】:
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请校对您的帖子并修正源代码示例的缩进。 (我猜在我写它的时候,某个好心人为你做了)。
标签: python opencv comparison histogram