来自:https://blog.csdn.net/miracleoa/article/details/104210597
import cv2
import numpy
def oilPainting(img, templateSize, bucketSize, step): # templateSize模板大小,bucketSize桶阵列,step模板滑动步长
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
gray = ((gray / 256) * bucketSize).astype(int) # 灰度图在桶中的所属分区
h, w = img.shape[:2]
oilImg = numpy.zeros(img.shape, numpy.uint8) # 用来存放过滤图像
for i in range(0, h, step):
top = i - templateSize
bottom = i + templateSize + 1
if top < 0:
top = 0
if bottom >= h:
bottom = h - 1
for j in range(0, w, step):
left = j - templateSize
right = j + templateSize + 1
if left < 0:
left = 0
if right >= w:
right = w - 1
# 灰度等级统计
buckets = numpy.zeros(bucketSize, numpy.uint8) # 桶阵列,统计在各个桶中的灰度个数
bucketsMean = [0, 0, 0] # 对像素最多的桶,求其桶中所有像素的三通道颜色均值
# 对模板进行遍历
for c in range(top, bottom):
for r in range(left, right):
buckets[gray[c, r]] += 1 # 模板内的像素依次投入到相应的桶中,有点像灰度直方图
maxBucket = numpy.max(buckets) # 找出像素最多的桶以及它的索引
maxBucketIndex = numpy.argmax(buckets)
for c in range(top, bottom):
for r in range(left, right):
if gray[c, r] == maxBucketIndex:
bucketsMean += img[c, r]
bucketsMean = (bucketsMean / maxBucket).astype(int) # 三通道颜色均值
# 油画图
for m in range(step):
for n in range(step):
oilImg[m + i, n + j] = (bucketsMean[0], bucketsMean[1], bucketsMean[2])
return oilImg
img = cv2.imread(r'my.jpg', cv2.IMREAD_ANYCOLOR)
oil = oilPainting(img, 4, 8, 2)
cv2.imshow('youhua', oil)
cv2.imwrite(r'myyouhua.jpg', oil)