개정판 deb37242
issue #000: fixed findContours because upgrading OpenCV 4.1
Change-Id: Id55cfcf2dc2be5b11532e15f2c9bbc3d65287ab9
| DTI_PID/DTI_PID/DetectSymbolDialog.py | ||
|---|---|---|
| 187 | 187 |
## contours 추출을 위한 색반전 |
| 188 | 188 |
areaImg = cv2.bitwise_not(areaImg) |
| 189 | 189 |
## contours 추출 |
| 190 |
image, contours, hierarchy = cv2.findContours(areaImg, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 190 |
contours, hierarchy = cv2.findContours(areaImg, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
|
| 191 | 191 |
for contour in contours: |
| 192 | 192 |
[x, y, w, h] = cv2.boundingRect(contour) |
| 193 | 193 |
|
| ... | ... | |
| 307 | 307 |
''' |
| 308 | 308 |
def getContours(self, areaImg): |
| 309 | 309 |
|
| 310 |
image, contours, hierarchy = cv2.findContours(areaImg, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 310 |
contours, hierarchy = cv2.findContours(areaImg, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
|
| 311 | 311 |
|
| 312 | 312 |
## RecList 정리 |
| 313 | 313 |
lineWidth = 5 |
| DTI_PID/DTI_PID/LineDetector.py | ||
|---|---|---|
| 578 | 578 |
imgNot = cv2.bitwise_xor(self._image, imgNot) |
| 579 | 579 |
imgNot = cv2.erode(imgNot, np.ones((2,2), np.uint8)) |
| 580 | 580 |
|
| 581 |
image, contours, hierarchy = cv2.findContours(imgNot, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 581 |
contours, hierarchy = cv2.findContours(imgNot, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
|
| 582 | 582 |
if len(contours) is 0: |
| 583 | 583 |
return [] |
| 584 | 584 |
|
| DTI_PID/DTI_PID/MainWindow.py | ||
|---|---|---|
| 2111 | 2111 |
cv2.bitwise_not(imgDiff, imgNot) |
| 2112 | 2112 |
imgNot = cv2.dilate(imgNot, np.ones((8,8), np.uint8)) |
| 2113 | 2113 |
|
| 2114 |
image, contours, hierarchy = cv2.findContours(imgNot, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 2114 |
contours, hierarchy = cv2.findContours(imgNot, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
|
| 2115 | 2115 |
|
| 2116 | 2116 |
## |
| 2117 | 2117 |
idx = 0 |
| DTI_PID/DTI_PID/OcrResultDialog.py | ||
|---|---|---|
| 181 | 181 |
cv2.bitwise_not(img, imgNot) |
| 182 | 182 |
imgNot = cv2.dilate(imgNot, np.ones((8,8), np.uint8)) |
| 183 | 183 |
|
| 184 |
image, contours, hierarchy = cv2.findContours(imgNot, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 184 |
contours, hierarchy = cv2.findContours(imgNot, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
|
| 185 | 185 |
minX, minY, maxX, maxY = sys.maxsize, sys.maxsize, 0 ,0 |
| 186 | 186 |
if len(contours) is 0: |
| 187 | 187 |
minX, minY, maxX, maxY = self.boundingBox.x(), self.boundingBox.y(), self.boundingBox.x() + self.image.width(), self.boundingBox.y() + self.image.height() |
| DTI_PID/DTI_PID/RecognitionDialog.py | ||
|---|---|---|
| 120 | 120 |
configs = appDocData.getConfigs('Small Object Size', 'Max Area')
|
| 121 | 121 |
maxArea = int(configs[0].value) if 1 == len(configs) else 50 |
| 122 | 122 |
|
| 123 |
_,contours,_ = cv2.findContours(image, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 123 |
contours,_ = cv2.findContours(image, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) |
|
| 124 | 124 |
selectedContours=[] |
| 125 | 125 |
for contour in contours: |
| 126 | 126 |
area = cv2.contourArea(contour) |
| DTI_PID/DTI_PID/Shapes/EngineeringLineItem.py | ||
|---|---|---|
| 746 | 746 |
imgLine = cv2.bitwise_not(imgLine) |
| 747 | 747 |
imgLine = cv2.erode(imgLine, np.ones((10, 10), np.uint8)) |
| 748 | 748 |
|
| 749 |
image, contours, hierarchy = cv2.findContours(imgLine, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 749 |
contours, hierarchy = cv2.findContours(imgLine, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) |
|
| 750 | 750 |
if contours: |
| 751 | 751 |
contours = sorted(contours, key=cv2.contourArea, reverse=True) |
| 752 | 752 |
[x, y, w, h] = cv2.boundingRect(contours[0]) |
| DTI_PID/DTI_PID/TextDetector.py | ||
|---|---|---|
| 63 | 63 |
contourImg = np.ones(imgGray.shape, np.uint8) * 255 |
| 64 | 64 |
binaryImg,mask = cv2.threshold(imgGray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU) |
| 65 | 65 |
|
| 66 |
image, contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
|
|
| 66 |
contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) |
|
| 67 | 67 |
for contour in contours: |
| 68 | 68 |
# remove too big one or horizontal/vertical line |
| 69 | 69 |
[x, y, w, h] = cv2.boundingRect(contour) |
| ... | ... | |
| 96 | 96 |
#path = os.path.join(project.getTempPath(), 'bitwise_not_{}.png'.format(appDocData.imgName))
|
| 97 | 97 |
#cv2.imwrite(path, eroded) |
| 98 | 98 |
|
| 99 |
image, contours, hierarchy = cv2.findContours(eroded, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 99 |
contours, hierarchy = cv2.findContours(eroded, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
|
| 100 | 100 |
for contour in contours: |
| 101 | 101 |
area = cv2.contourArea(contour, True) |
| 102 | 102 |
if area < 0: |
| ... | ... | |
| 107 | 107 |
|
| 108 | 108 |
horizontal,max_width = 0,0 |
| 109 | 109 |
vertical,max_height = 0,0 |
| 110 |
_, _contours, _ = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 110 |
_contours, _ = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) |
|
| 111 | 111 |
for xx in _contours: |
| 112 | 112 |
[_x, _y, _w, _h] = cv2.boundingRect(xx) |
| 113 | 113 |
cv2.rectangle(img, (_x, _y), (_x+_w, _y+_h), 255, 1) |
| ... | ... | |
| 131 | 131 |
if shrinkSize > 0: |
| 132 | 132 |
img = cv2.erode(img, np.ones((shrinkSize,shrinkSize), np.uint8)) |
| 133 | 133 |
|
| 134 |
_, _contours, _ = cv2.findContours(img, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 134 |
_contours, _ = cv2.findContours(img, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE) |
|
| 135 | 135 |
for xx in _contours: |
| 136 | 136 |
[_x, _y, _w, _h] = cv2.boundingRect(xx) |
| 137 | 137 |
cv2.rectangle(img, (_x, _y), (_x+_w, _y+_h), 255, 1) |
| DTI_PID/DTI_PID/TrainingImageListDialog.py | ||
|---|---|---|
| 351 | 351 |
# //remove noise |
| 352 | 352 |
''' |
| 353 | 353 |
if self.isNoisable(boxes[index][0]): |
| 354 |
image, contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
|
|
| 354 |
contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) |
|
| 355 | 355 |
for contour in contours: |
| 356 | 356 |
# remove too big one |
| 357 | 357 |
[x, y, w, h] = cv2.boundingRect(contour) |
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