def ocr(self, job_id):
picData = tools.readPickle(job_id, 'step2')
images = picData['images']['Points']
file_path = picData['filePath']
logging.info('%s LOAD DATA FROM PICKLE')
img = cv2.imread(file_path, cv2.IMREAD_UNCHANGED)
img_shape = img.shape
logging.info('%s LOAD IMG width: %d, height: %d' %
(tools.getTempTime(), img_shape[1], img_shape[0]))
datas = []
for image in images.items():
data = dict()
data['name'] = image[0]
ocrTemp, _ = tools.createRoi(img, image[1], job_id + '/step3',
'3_' + image[0] + '_Roi')
if data['name'] in ('customer', 'date'):
data['value'] = tools.callOcr(ocrTemp, job_id + '/step3',
img_shape[1], 1992)
else:
data['value'] = tools.callOcr(ocrTemp, job_id + '/step3',
img_shape[1])
datas.append(data)
logging.info('%s CALL COR FOR BLOCK %s result: %s' %
(tools.getTempTime(), data['name'], data['value']))
return datas
def post(self):
json_data = request.get_json(force=True)
job_id = json_data['job_id']
logging.basicConfig(level=logging.INFO)
logging.info('%s STEP TWO BEGIN' % tools.getTempTime())
logging.info('%s LOAD JSON DATA job_id: %s' %
(tools.getTempTime(), job_id))
result = self.extractImage(job_id)
logging.info('%s CREATE JSON DATA' % tools.getTempTime())
images = []
points = result['Points']
paths = result['Paths']
for data in points.items():
image = dict()
image['name'] = data[0]
image['x'] = data[1][0][0]
image['y'] = data[1][0][1]
image['w'] = data[1][1][0] - data[1][0][0]
image['h'] = data[1][1][1] - data[1][0][1]
image['file'] = paths[data[0]]
images.append(image)
dummy_data = {'images': images}
logging.info('%s RETURN JOSN BODY' % tools.getTempTime())
logging.info('%s STEP TWO END' % tools.getTempTime())
return {'code': 0, 'message': 'OK', 'data': dummy_data}
def post(self):
json_data = request.get_json(force=True)
job_id = json_data['job_id']
file_path = json_data['file_path']
logging.basicConfig(level=logging.INFO)
logging.info('%s STEP ONE BEGIN' % tools.getTempTime())
logging.info('%s LOAD JSON DATA job_id: %s, file_path: %s' % (tools.getTempTime(), job_id, file_path))
result = self.detectInvoice(job_id, file_path)
img_shape = result['imgShape']
origin_shape = result['originShape']
rotate_sum = result['rotateSum']
doc_type = result['docType']
file_path = result['compressPath']
a_location = result['feaLoca'][0]
b_location = result['feaLoca'][1]
orig_left_top = result['originLeftTop']
fea_path = result['feaPath']
logging.info('%s CREATE JSON DATA' % tools.getTempTime())
dummy_data = {
'image': {
'w': img_shape[1],
'h': img_shape[0],
'ori_w': origin_shape[1],
'ori_h': origin_shape[0],
'ori_left_top_x': orig_left_top[0],
'ori_left_top_y':orig_left_top[1],
'file': file_path,
'rotate_sum':rotate_sum
},
'docType': doc_type,
'featurePoints': [
{
'x': a_location[0][0],
'y': a_location[0][1],
'w': a_location[1][0] - a_location[0][0],
'h': a_location[1][1] - a_location[0][1],
'file': fea_path[0],
},
{
'x': b_location[0][0],
'y': b_location[0][1],
'w': b_location[1][0] - b_location[0][0],
'h': b_location[1][1] - b_location[0][1],
'file': fea_path[1],
}
]
}
logging.info('%s RETURN JOSN BODY' % tools.getTempTime())
logging.info('%s STEP ONE END' % tools.getTempTime())
return {
'code': 0,
'message': 'OK',
'data': dummy_data
}
def post(self):
json_data = request.get_json(force=True)
job_id = json_data['job_id']
logging.basicConfig(level=logging.INFO)
logging.info('%s STEP THREE BEGIN' % tools.getTempTime())
logging.info('%s LOAD JSON DATA job_id: %s' %
(tools.getTempTime(), job_id))
result = self.ocr(job_id)
ocrs = []
for data in result:
ocr = dict()
ocr['name'] = data['name']
ocr['value'] = data['value']
ocrs.append(ocr)
logging.info('%s RETURN JOSN BODY' % tools.getTempTime())
logging.info('%s STEP THREE END' % tools.getTempTime())
dummy_data = {'ocr': ocrs}
return {'code': 0, 'message': 'OK', 'data': dummy_data}
def extractImage(self, job_id):
# read img
picData = tools.readPickle(job_id, 'step1')
feaLocas = picData['feaLoca']
a = feaLocas[0]
b = feaLocas[1]
file_path = picData['filePath']
logging.info('%s LOAD DATA FROM PICKLE' % tools.getTempTime())
img = cv2.imread(file_path, cv2.IMREAD_UNCHANGED)
rare_img = img.copy()
img_shape = img.shape
logging.info('%s LOAD IMG width: %d, height: %d' %
(tools.getTempTime(), img_shape[1], img_shape[0]))
datas = dict()
points = dict()
paths = dict()
datas['Points'] = points
datas['Paths'] = paths
points['customer'] = tools.findCustomerRect(a[0], a[1], b[0], b[1])
points['number'] = tools.findNumberRect(a[0], a[1], b[0], b[1])
points['date'] = tools.findDateRect(a[0], a[1], b[0], b[1])
# points['seller'] = tools.findSellerRect(a[0], a[1], c[0], c[1])
points['price'] = tools.findPriceRect(a[0], a[1], b[0], b[1])
points['lines'] = tools.findLineRect(a[0], a[1], b[0], b[1])
logging.info('%s DIVIDE THE BLOCKS' % tools.getTempTime())
picData = dict()
picData['images'] = datas
picData['filePath'] = file_path
for point in points.items():
_, path = tools.createRoi(img, point[1], job_id + '/step2',
'2_' + point[0] + '_Roi')
cv2.rectangle(rare_img, point[1][0], point[1][1], 0, 2)
paths[point[0]] = path
tools.writeImageJob(rare_img, job_id + '/step2', '2_divided_img')
logging.info('%s CREATE DIVIDED BLOCK ROIS' % tools.getTempTime())
logging.info('%s SAVE ROIS TO FILE' % tools.getTempTime())
tools.writePickle(picData, job_id, 'step2')
logging.info('%s WRITE PICKLE' % tools.getTempTime())
return datas
def detectInvoice(self, job_id, file_path):
img = cv2.imread(file_path, cv2.IMREAD_UNCHANGED)
origin_shape = img.shape
logging.info('%s LOAD IMG width:%d, height:%d' % (tools.getTempTime(), origin_shape[1], origin_shape[0]))
img, rotate_sum = tools.findLinesandRotate(img)
rotated_shape = img.shape
img, img_detect, new_left_top = tools.matchAndImageCut(img)
img_shape = img.shape
rotate = np.deg2rad(-1*rotate_sum)
x = new_left_top[0]-int(rotated_shape[1]/2)
y = new_left_top[1]-int(rotated_shape[0]/2)
newX, newY = int(np.cos(rotate)*x-np.sin(rotate)*y), int(np.cos(rotate)*y+np.sin(rotate)*x)
origX, origY = -newY+int(origin_shape[1]/2), newX+int(origin_shape[0]/2)
a_location, b_location = tools.detectFeaturePoints(img)
logging.info(
'%s IMG AFTER ROTATE AND CUT width:%d, height:%d' % (tools.getTempTime(), img_shape[1], img_shape[0]))
img_copy1 = img.copy()
img_copy2 = img.copy()
img_compress = img.copy()
img_black = tools.exBlackWords(img_copy1)
img_blue = tools.exBlueWords(img_copy2)
img_black = cv2.cvtColor(img_black, cv2.COLOR_BGR2GRAY)
img_blue = cv2.cvtColor(img_blue, cv2.COLOR_BGR2GRAY)
cv2.rectangle(img_black, a_location[0], a_location[1], 0, 2)
cv2.rectangle(img_black, b_location[0], b_location[1], 0, 2)
logging.info('%s DRAW DOCTYPE TEMPLATE (%d, %d), (%d, %d)' % (
tools.getTempTime(), a_location[0][0], a_location[0][1], a_location[1][0], a_location[1][1]))
logging.info('%s DRAW DOCTYPE TEMPLATE (%d, %d), (%d, %d)' % (
tools.getTempTime(), b_location[0][0], b_location[0][1], b_location[1][0], b_location[1][1]))
# create compress image
k = img_shape[1] / 1000.0
compress_img = cv2.resize(img_compress, (int(img_shape[1] / k), int(img_shape[0] / k)))
logging.info('%s COMPRESS IMAGE SAVED' % tools.getTempTime())
# write img to file
file_path = tools.writeImageJob(img, job_id + '/step1', '1_rotated')
compress_path = tools.writeImageJob(compress_img, job_id + '/step1', '1_compressd')
tools.writeImageJob(img_black, job_id + '/step1', '1_black')
tools.writeImageJob(img_blue, job_id + '/step1', '1_blue')
tools.writeImageJob(img_detect, job_id + '/step1', '1_detect')
logging.info('%s ROTATED IMAGE SAVED IN %s' % (tools.getTempTime(), file_path))
a_roi, a_path = tools.createRoi(img, a_location, job_id + '/step1', '1_type_Roi')
b_roi, b_path = tools.createRoi(img, b_location, job_id + '/step1', '1_number_Roi')
docType = tools.callOcr(a_roi, job_id + '/step1', img_shape[1])
logging.info('%s CREATE TEMPLATE ROIS' % tools.getTempTime())
logging.info('%s CALL OCR docType: %s' % (tools.getTempTime(), docType))
# write tickle to file for next step to use
data = dict()
data['feaLoca'] = [a_location, b_location]
data['originLeftTop'] = [origX, origY]
data['filePath'] = file_path
data['compressPath'] = compress_path
data['imgShape'] = img_shape
data['originShape'] = origin_shape
data['rotateSum'] = rotate_sum
data['docType'] = docType
data['feaPath'] = [a_path, b_path]
tools.writePickle(data, job_id, 'step1')
logging.info('%s WRITE PICKLE' % tools.getTempTime())
return data