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pretreat.py
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pretreat.py
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# encoding:utf-8
import config
import numpy as np
from PIL import Image
import cv2
import sys
import os
def pretreat(img: Image.Image) -> Image.Image:
img_data = np.array(img)
# img_data = np.mean(img_data, -1) # 将rgb转为灰度图
# 二值化
img_data[img_data > 128] = 255
img_data[img_data <= 128] = 0
img = Image.fromarray(img_data)
return img
def custom_blur_demo(image: Image.Image, n: int) -> Image.Image:
image = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
kernel = np.array([[0, -1, 0], [-1, n, -1], [0, -1, 0]], np.float32) # 锐化
dst = cv2.filter2D(image, -1, kernel=kernel)
# cv2.imshow("custom_blur_demo", dst)
return Image.fromarray(dst)
def crop_image(image: Image.Image) -> Image.Image:
"""Crop document from image.
Takes a PIL.image and return a PIL.image. Not resized.
"""
def rectify(h):
h = h.reshape((4, 2))
hnew = np.zeros((4, 2), dtype=np.float32)
add = h.sum(1)
hnew[0] = h[np.argmin(add)]
hnew[2] = h[np.argmax(add)]
diff = np.diff(h, axis=1)
hnew[1] = h[np.argmin(diff)]
hnew[3] = h[np.argmax(diff)]
return hnew
# resize image so it can be processed
# choose optimal dimensions such that important content is not lost
image = np.asarray(image)
# TODO 不知道能不能删掉
# image = cv2.resize(image, (1500, 880))
# creating copy of original image
orig = image.copy()
# convert to grayscale and blur to smooth
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
# blurred = cv2.medianBlur(gray, 5)
# apply Canny Edge Detection
edged = cv2.Canny(blurred, 0, 50)
# orig_edged = edged.copy()
# find the contours in the edged image, keeping only the
# largest ones, and initialize the screen contour
(contours, _) = cv2.findContours(edged, cv2.RETR_LIST,
cv2.CHAIN_APPROX_NONE)
contours = sorted(contours, key=cv2.contourArea, reverse=True)
# x,y,w,h = cv2.boundingRect(contours[0])
# cv2.rectangle(image,(x,y),(x+w,y+h),(0,0,255),0)
# get approximate contour
for c in contours:
p = cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, 0.02 * p, True)
if len(approx) == 4:
target = approx
break
# mapping target points to 800x800 quadrilateral
approx = rectify(target)
# pts2 = np.float32([[0, 0], [800, 0], [800, 800], [0, 800]])
pts2 = np.float32([[0, 0], [config.IMAGE_SIZE[0], 0], [config.IMAGE_SIZE[0], config.IMAGE_SIZE[1]], [0, config.IMAGE_SIZE[1]]])
M = cv2.getPerspectiveTransform(approx, pts2)
# dst = cv2.warpPerspective(orig, M, (800, 800))
dst = cv2.warpPerspective(orig, M, config.IMAGE_SIZE)
cv2.drawContours(image, [target], -1, (0, 255, 0), 2)
# dst = cv2.cvtColor(dst, cv2.COLOR_BGR2GRAY)
# return Image.fromarray(dst).resize(config.IMAGE_SIZE)
return Image.fromarray(dst)
if __name__ == "__main__":
'''
path = "result/" + sys.argv[1] + ".jpg"
img = Image.open(path)
img = custom_blur_demo(img, int(sys.argv[2]))
img = cv2.cvtColor(np.asarray(img), cv2.COLOR_RGB2BGR)
cv2.imshow("img", img)
cv2.waitKey(0)
'''
# path = "data/newdata/HuaWenSun/"
# files = os.listdir(path)
# for f in files:
# print(f)
# img = Image.open(path + f)
# img = crop_image(img)
# img.save("data/HuaWenSun/" + f)
# path = "data/newdata/MicroSun/"
# files = os.listdir(path)
# for f in files:
# print(f)
# img = Image.open(path + f)
# img = crop_image(img)
# img.save("data/MicroSun/" + f)
# path = "data/newdata/error-test/"
path = sys.argv[1]
files = os.listdir(path)
for f in files:
print(f)
img = Image.open(path + f)
img = crop_image(img).convert('RGB')
# img.save("data/error-test/" + f)
img.save(sys.argv[2]+f)