def test_inpainted_input_output_spec_check():
img1 = cv2.imread('./fixture/real_proj/images/bw1.png')
img2 = cv2.imread('./fixture/real_proj/images/bgr1.png')
seg1 = core.segmap(img1)
seg2 = core.segmap(img2)
ret1 = core.inpainted(img1, seg1)
ret2 = core.inpainted(img2, seg2)
def rm_txt(self):
imgpath = state.now_image()
maskpath = state.now_mask()
if imgpath is None: return None
self.saveMask.emit(maskpath) # save edited mask
image = io.load(imgpath, io.IMAGE)
mask =(io.load(maskpath, io.MASK)
if Path(maskpath).exists()
else io.mask2segmap(self.gen_mask()))
inpainted = core.inpainted(image, mask)
io.save(state.now_image(), inpainted)
self.update_gui()
def segmentPage(self,imgPath,outputInpaintedPath,outputTextOnlyPath):
self.resize(imgPath) #because of sickzil has poor quality on high resolution image
#process sickzil
fileName=os.path.basename(imgPath)
oriImage = imgio.load(imgPath, imgio.IMAGE) #ori image
maskImage = imgio.mask2segmap(self.imgpath2mask(imgPath)) #mask image
inpaintedImage = core.inpainted(oriImage, maskImage) #notext image
textOnlyImage= cv2.bitwise_and(oriImage,maskImage) #text only image
textOnlyImage[maskImage==0] = 255
imgio.save(outputInpaintedPath+fileName, inpaintedImage)
imgio.save(outputTextOnlyPath+fileName, textOnlyImage)
def segmentImage(self, downloadFileList, inpaintedFolder, textOnlyFolder):
# image segmentation
for i, imgPath in enumerate(tqdm(downloadFileList)):
print("image path: ", imgPath)
fileName = os.path.basename(imgPath)
oriImage = imgio.load(imgPath, imgio.IMAGE) #ori image
# imgpath2mask(imgPath)
# mask image is a black image with features (text) being white
maskImage = imgio.mask2segmap(
self.imgpath2mask(imgPath)) #mask image
# remove all the text from the original image
# this is used later on to write new translated texts on it.
inpaintedImage = core.inpainted(oriImage, maskImage) #notext image
# convert all the texts from white to black color (white-white => white, else black)
# we need to convert to black color text for what ?
# for easier reading and easier for oct algo to detect text
textOnlyImage = cv2.bitwise_and(oriImage,
maskImage) #text only image
#if i==0:
#cv2.imshow("text_only_img", textOnlyImage)
textOnlyImage[maskImage == 0] = 255
imgio.save(inpaintedFolder + fileName, inpaintedImage)
imgio.save(textOnlyFolder + fileName, textOnlyImage)
def rm_txt(imgpath, maskpath, outputpath):
if imgpath is None: return None
image = io.load(imgpath, io.IMAGE)
mask = io.load(maskpath, io.MASK)
inpainted = core.inpainted(image, mask)
io.save(outputpath, inpainted)