來自:https://blog.csdn.net/miracleoa/article/details/104210597
import cv2 import numpy def oilPainting(img, templateSize, bucketSize, step): # templateSize模板大小,bucketSize桶陣列,step模板滑動步長 gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) gray = ((gray / 256) * bucketSize).astype(int) # 灰度圖在桶中的所屬分區 h, w = img.shape[:2] oilImg = numpy.zeros(img.shape, numpy.uint8) # 用來存放過濾圖像 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 # 灰度等級統計 buckets = numpy.zeros(bucketSize, numpy.uint8) # 桶陣列,統計在各個桶中的灰度個數 bucketsMean = [0, 0, 0] # 對像素最多的桶,求其桶中所有像素的三通道顏色均值 # 對模板進行遍歷 for c in range(top, bottom): for r in range(left, right): buckets[gray[c, r]] += 1 # 模板內的像素依次投入到相應的桶中,有點像灰度直方圖 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) # 三通道顏色均值 # 油畫圖 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)