使用下一个代码我可以拍摄一张图像并将其分成包含感兴趣区域的各种较小图像。
import cv2
import sys
sys.path.insert(0, 'C:\\Users\\Bob\\Desktop\\Project')
sys.path.insert(0, 'C:\\Users\\Bob\\Desktop\\Project\\FOLDER')
sys.path.insert(0, 'C:\\Users\\Bob\\Desktop\\Project\\READER')
import FOLDER.folders
import READER.extractor
timestr = FOLDER.folders.timestr
################## AREA 1 ##################
# Load the image
img = cv2.imread('C:\\Users\\Bob\\Desktop\\Destination\\' + str(timestr) + '\\EXTRACTED\\' + 'area1.png')
# convert to grayscale
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# smooth the image to avoid noises
gray = cv2.medianBlur(gray,5)
# Apply adaptive threshold
thresh = cv2.adaptiveThreshold(gray,255,1,1,11,2)
thresh_color = cv2.cvtColor(thresh,cv2.COLOR_GRAY2BGR)
# apply some dilation and erosion to join the gaps - change iterations value to detect more or less area's
thresh = cv2.dilate(thresh,None,iterations = 15)
thresh = cv2.erode(thresh,None,iterations = 15)
# Find the contours
image,contours,hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
# For each contour, find the bounding rectangle and draw it
idx =0
for cnt in contours:
idx += 1
x,y,w,h = cv2.boundingRect(cnt)
roi = gray[y:y + h, x:x + w]
cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
cv2.rectangle(thresh_color,(x,y),(x+w,y+h),(0,255,0),2)
cv2.imwrite('C:\\Users\\Bob\\Desktop\\Destination\\' + str(timestr) + '\\EXTRACTED\\ex_area1' + str(idx) + '.png',roi)
这是一个例子:
已加载图片
输出
代码还提供了一些我不想要的小图片(让我们说文物)。所有这些图像都低于某些尺寸。
我的问题是:我必须添加到上面的代码中删除这些图像?要删除例如下一个尺寸的图像:250(宽度)X 60(高度)像素?
谢谢
提示:使用此代码检测区域:Improve text area detection (OpenCV, Python)
答案 0 :(得分:2)
首先不要写它们。仅写入60 * 250以上的图像。
IN