개정판 a1f892b5
issue #000
| DTI_PID/DTI_PID/RecognitionDialog.py | ||
|---|---|---|
| 254 | 254 |
listWidget.addItem("Start recognition : " + mainRes)
|
| 255 | 255 |
threadLock.acquire() |
| 256 | 256 |
offset = (area.x, area.y) if area is not None else (0,0) |
| 257 |
if worker.isTextChecked: |
|
| 258 |
textAreas = textDetector.detectTextAreas(area.img if area is not None else appDocData.imgSrc, offset) |
|
| 259 |
maxProgressValue = len(textAreas) + 1 |
|
| 257 |
#if worker.isTextChecked:
|
|
| 258 |
# textAreas = textDetector.detectTextAreas(area.img if area is not None else appDocData.imgSrc, offset)
|
|
| 259 |
# maxProgressValue = len(textAreas) + 1
|
|
| 260 | 260 |
|
| 261 | 261 |
if worker.isSymbolChecked: |
| 262 | 262 |
### calculate total count of symbol |
| ... | ... | |
| 291 | 291 |
_img = appDocData.imgSrc[round(item.getSp()[1]):round(item.getSp()[1]+item.getHeight()), round(item.getSp()[0]):round(item.getSp()[0]+item.getWidth())] |
| 292 | 292 |
cv2.imwrite(os.path.join(project.getTempPath(), 'Tile', item.getName()+'.png'), _img) |
| 293 | 293 |
## up to here |
| 294 |
|
|
| 294 |
|
|
| 295 |
pool = futures.ThreadPoolExecutor(max_workers = THREAD_MAX_WORKER) |
|
| 296 |
for sym in searchedSymbolList: |
|
| 297 |
pool.submit(Worker.removeDetectedSymbol, sym, appDocData.imgSrc) |
|
| 298 |
pool.shutdown(wait = True) |
|
| 299 |
|
|
| 300 |
## Remove Noise |
|
| 301 |
appDocData.imgSrc = cv2.fastNlMeansDenoising(appDocData.imgSrc, None, 9, 13) |
|
| 302 |
#kernel1 = np.ones((2, 2), np.uint8) |
|
| 303 |
#appDocData.imgSrc = cv2.dilate(appDocData.imgSrc, kernel1) |
|
| 304 |
#appDocData.imgSrc = cv2.erode(appDocData.imgSrc, kernel1) |
|
| 305 |
|
|
| 295 | 306 |
if worker.isTextChecked: |
| 307 |
textAreas = textDetector.detectTextAreas(area.img if area is not None else appDocData.imgSrc, offset) |
|
| 308 |
maxProgressValue = len(textAreas) + 1 |
|
| 309 |
|
|
| 296 | 310 |
worker.displayTitle.emit('텍스트 인식 중...')
|
| 297 | 311 |
textDetector.recognizeText(appDocData.imgSrc, offset, textAreas, searchedSymbolList, worker, listWidget, maxProgressValue) |
| 298 | 312 |
textInfoList = textDetector.textInfoList.copy() if textDetector.textInfoList is not None else None |
| ... | ... | |
| 308 | 322 |
|
| 309 | 323 |
appDocData.imgName = os.path.splitext(os.path.basename(mainRes))[0] |
| 310 | 324 |
|
| 311 |
pool = futures.ThreadPoolExecutor(max_workers = THREAD_MAX_WORKER) |
|
| 312 |
for sym in searchedSymbolList: |
|
| 313 |
pool.submit(Worker.removeDetectedSymbol, sym, appDocData.imgSrc) |
|
| 314 |
pool.shutdown(wait = True) |
|
| 315 |
|
|
| 316 | 325 |
## Remove Noise |
| 317 |
kernel1 = np.ones((2, 2), np.uint8) |
|
| 318 |
appDocData.imgSrc = cv2.dilate(appDocData.imgSrc, kernel1) |
|
| 319 |
appDocData.imgSrc = cv2.erode(appDocData.imgSrc, kernel1) |
|
| 326 |
#kernel1 = np.ones((2, 2), np.uint8)
|
|
| 327 |
#appDocData.imgSrc = cv2.dilate(appDocData.imgSrc, kernel1)
|
|
| 328 |
#appDocData.imgSrc = cv2.erode(appDocData.imgSrc, kernel1)
|
|
| 320 | 329 |
|
| 321 | 330 |
removedSymbolImgPath = os.path.join(project.getTempPath(), os.path.basename(path)) |
| 322 | 331 |
cv2.imwrite(removedSymbolImgPath, appDocData.imgSrc) |
| ... | ... | |
| 995 | 1004 |
return 0 |
| 996 | 1005 |
|
| 997 | 1006 |
#shared area |
| 998 |
x = max(sp[0], pt[0]);
|
|
| 999 |
y = max(sp[1], pt[1]);
|
|
| 1000 |
w = min(sp[0] + width, pt[0] + tw) - x;
|
|
| 1001 |
h = min(sp[1] + height, pt[1] + th) - y;
|
|
| 1007 |
x = max(sp[0], pt[0]) |
|
| 1008 |
y = max(sp[1], pt[1]) |
|
| 1009 |
w = min(sp[0] + width, pt[0] + tw) - x |
|
| 1010 |
h = min(sp[1] + height, pt[1] + th) - y |
|
| 1002 | 1011 |
|
| 1003 | 1012 |
return float((w * h)) / float((tw * th)) * 100 |
| 1004 | 1013 |
|
| ... | ... | |
| 1189 | 1198 |
symImg = cv2.rotate(symImg, cv2.ROTATE_90_COUNTERCLOCKWISE) |
| 1190 | 1199 |
|
| 1191 | 1200 |
threadLock.acquire() |
| 1192 |
temp = [] |
|
| 1193 | 1201 |
temp = imgSrc[sp[1]:sp[1]+sh, sp[0]:sp[0]+sw] |
| 1194 |
symImgBin = cv2.bitwise_not(symImg)
|
|
| 1195 |
result = cv2.bitwise_xor(symImgBin, temp)
|
|
| 1196 |
result = cv2.dilate(result, np.ones((5, 5), np.uint8))
|
|
| 1197 |
imgSrc[sp[1]:sp[1]+sh, sp[0]:sp[0]+sw] = result
|
|
| 1202 |
#symImg = cv2.dilate(symImg, np.ones((2,2), np.uint8))
|
|
| 1203 |
imgXOR = cv2.bitwise_xor(temp, symImg)
|
|
| 1204 |
#imgXOR = cv2.dilate(imgXOR, np.ones((5, 5), np.uint8))
|
|
| 1205 |
imgSrc[sp[1]:sp[1]+sh, sp[0]:sp[0]+sw] = cv2.bitwise_not(imgXOR)
|
|
| 1198 | 1206 |
threadLock.release() |
| 1199 | 1207 |
|
| 1200 | 1208 |
''' |
| DTI_PID/DTI_PID/TextDetector.py | ||
|---|---|---|
| 91 | 91 |
|
| 92 | 92 |
eroded = cv2.bitwise_not(eroded) |
| 93 | 93 |
|
| 94 |
image, contours, hierarchy = cv2.findContours(eroded, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 94 |
image, contours, hierarchy = cv2.findContours(eroded, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 95 | 95 |
for contour in contours: |
| 96 | 96 |
area = cv2.contourArea(contour, True) |
| 97 | 97 |
if area < 0: |
| ... | ... | |
| 102 | 102 |
|
| 103 | 103 |
horizontal,max_width = 0,0 |
| 104 | 104 |
vertical,max_height = 0,0 |
| 105 |
_, _contours, _ = cv2.findContours(img, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 105 |
_, _contours, _ = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
|
| 106 | 106 |
for xx in _contours: |
| 107 | 107 |
[_x, _y, _w, _h] = cv2.boundingRect(xx) |
| 108 | 108 |
cv2.rectangle(img, (_x, _y), (_x+_w, _y+_h), 255, 1) |
| ... | ... | |
| 260 | 260 |
|
| 261 | 261 |
pool = futures.ThreadPoolExecutor(max_workers = THREAD_MAX_WORKER) |
| 262 | 262 |
for tInfo in tInfoList: |
| 263 |
#future = pool.submit(TextDetector.recognizeTextFromImage, tInfo, imgSrc, (0,0), searchedSymbolList, worker, listWidget, maxProgressValue) |
|
| 263 | 264 |
future = pool.submit(TextDetector.recognizeTextFromImage, tInfo, imgOCR, offset, searchedSymbolList, worker, listWidget, maxProgressValue) |
| 264 | 265 |
data = future.result() |
| 265 | 266 |
if data: self.textInfoList.extend(data) |
| 266 | 267 |
pool.shutdown(wait = True) |
| 267 | 268 |
|
| 268 |
if onlyTextArea: |
|
| 269 |
return |
|
| 270 |
# parse texts in area except Drawing area |
|
| 271 |
whiteCharList = appDocData.getConfigs('Text Recognition', 'White Character List')
|
|
| 272 |
for area in appDocData.getAreaList(): |
|
| 273 |
if area.name == 'Drawing': continue |
|
| 269 |
if onlyTextArea:
|
|
| 270 |
return
|
|
| 271 |
# parse texts in area except Drawing area
|
|
| 272 |
whiteCharList = appDocData.getConfigs('Text Recognition', 'White Character List')
|
|
| 273 |
for area in appDocData.getAreaList():
|
|
| 274 |
if area.name == 'Drawing': continue
|
|
| 274 | 275 |
|
| 275 |
if area.name == 'Unit': |
|
| 276 |
if area.name == 'Unit': |
|
| 277 |
img = imgSrc[round(area.y):round(area.y+area.height), round(area.x):round(area.x+area.width)] |
|
| 278 |
if len(whiteCharList) is 0: |
|
| 279 |
texts = TOCR.getTextInfo(img, (area.x, area.y), 0, language='eng') |
|
| 280 |
else: |
|
| 281 |
texts = TOCR.getTextInfo(img, (area.x, area.y), 0, language='eng', conf = whiteCharList[0].value) |
|
| 282 |
if texts is not None and len(texts) > 0: |
|
| 283 |
appDocData.activeDrawing.setAttr('Unit', texts[0].getText())
|
|
| 284 |
self.otherTextInfoList.append([area.name, texts]) |
|
| 285 |
else: |
|
| 286 |
if area is not None and hasattr(area, 'img') and area.img is not None: |
|
| 287 |
if len(whiteCharList) is 0: |
|
| 288 |
texts = TOCR.getTextInfo(area.img, (area.x, area.y), 0, language='eng') |
|
| 289 |
else: |
|
| 290 |
texts = TOCR.getTextInfo(area.img, (area.x, area.y), 0, language='eng', conf=whiteCharList[0].value) |
|
| 291 |
self.otherTextInfoList.append([area.name, texts]) |
|
| 292 |
|
|
| 293 |
titleBlockProps = appDocData.getTitleBlockProperties() |
|
| 294 |
for titleBlockProp in titleBlockProps: |
|
| 295 |
area = Area(titleBlockProp[0]) |
|
| 296 |
area.parse(titleBlockProp[2]) |
|
| 276 | 297 |
img = imgSrc[round(area.y):round(area.y+area.height), round(area.x):round(area.x+area.width)] |
| 277 | 298 |
if len(whiteCharList) is 0: |
| 278 | 299 |
texts = TOCR.getTextInfo(img, (area.x, area.y), 0, language='eng') |
| 279 | 300 |
else: |
| 280 |
texts = TOCR.getTextInfo(img, (area.x, area.y), 0, language='eng', conf = whiteCharList[0].value) |
|
| 281 |
if texts is not None and len(texts) > 0: |
|
| 282 |
appDocData.activeDrawing.setAttr('Unit', texts[0].getText())
|
|
| 283 |
self.otherTextInfoList.append([area.name, texts]) |
|
| 284 |
else: |
|
| 285 |
if area is not None and hasattr(area, 'img') and area.img is not None: |
|
| 286 |
if len(whiteCharList) is 0: |
|
| 287 |
texts = TOCR.getTextInfo(area.img, (area.x, area.y), 0, language='eng') |
|
| 288 |
else: |
|
| 289 |
texts = TOCR.getTextInfo(area.img, (area.x, area.y), 0, language='eng', conf=whiteCharList[0].value) |
|
| 290 |
self.otherTextInfoList.append([area.name, texts]) |
|
| 291 |
|
|
| 292 |
titleBlockProps = appDocData.getTitleBlockProperties() |
|
| 293 |
for titleBlockProp in titleBlockProps: |
|
| 294 |
area = Area(titleBlockProp[0]) |
|
| 295 |
area.parse(titleBlockProp[2]) |
|
| 296 |
img = imgSrc[round(area.y):round(area.y+area.height), round(area.x):round(area.x+area.width)] |
|
| 297 |
if len(whiteCharList) is 0: |
|
| 298 |
texts = TOCR.getTextInfo(img, (area.x, area.y), 0, language='eng') |
|
| 299 |
else: |
|
| 300 |
texts = TOCR.getTextInfo(img, (area.x, area.y), 0, language='eng', conf=whiteCharList[0].value) |
|
| 301 |
self.titleBlockTextInfoList.append([area.name, texts]) |
|
| 301 |
texts = TOCR.getTextInfo(img, (area.x, area.y), 0, language='eng', conf=whiteCharList[0].value) |
|
| 302 |
self.titleBlockTextInfoList.append([area.name, texts]) |
|
| 302 | 303 |
|
| 303 |
if worker is not None: worker.updateProgress.emit(maxProgressValue, None) |
|
| 304 |
if worker is not None: worker.updateProgress.emit(maxProgressValue, None)
|
|
| 304 | 305 |
except Exception as ex: |
| 305 | 306 |
message = 'error occured({}) in {}:{}'.format(ex, sys.exc_info()[-1].tb_frame.f_code.co_filename, sys.exc_info()[-1].tb_lineno)
|
| 306 | 307 |
worker.displayLog.emit(MessageType.Error, message) |
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