Echo/fcb_photo_review
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自动识别新增文档检测与扭曲矫正功能

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liuyebo
2024-08-22 15:26:37 +08:00
parent 15ca978eaf
commit fd6b706803
3 changed files with 40 additions and 29 deletions
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62
photo_review/photo_review.py
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@@ -14,6 +14,8 @@ from sqlalchemy import update
from db import MysqlSession
from db.mysql import BdYljg, BdYlks, ZxIeResult, ZxIeCost, ZxIeDischarge, ZxIeSettlement, ZxPhhd, ZxPhrec
from doc_dewarp import dewarp
from object_detection import doc_detect
from photo_review import PATIENT_NAME, ADMISSION_DATE, DISCHARGE_DATE, MEDICAL_EXPENSES, PERSONAL_CASH_PAYMENT, \
PERSONAL_ACCOUNT_PAYMENT, PERSONAL_FUNDED_AMOUNT, MEDICAL_INSURANCE_TYPE, HOSPITAL, DEPARTMENT, DOCTOR, \
ADMISSION_ID, SETTLEMENT_ID, AGE, OCR, SETTLEMENT_IE, DISCHARGE_IE, COST_IE, PHHD_BATCH_SIZE, SLEEP_MINUTES, \
@@ -79,39 +81,45 @@ def information_extraction(ie, phrecs, identity):
continue
image = image_util.read(img_path)
angles = image_util.parse_rotation_angles(image)
target_images = []
target_images += doc_detect.capture_target_area(image) # 识别文档区域并裁剪
if not target_images:
target_images.append(image) # 识别失败
angle_count = defaultdict(int, {"0": 0}) # 分割后图片的最优角度统计
zx_ie_results = []
split_results = image_util.split(image)
for split_result in split_results:
rotated_img = image_util.rotate(split_result["img"], int(angles[0]))
ie_results = [{"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[0]}]
if not ie_results[0]["result"] or len(ie_results[0]["result"]) < len(ie.kwargs.get("schema")):
rotated_img = image_util.rotate(split_result["img"], int(angles[1]))
ie_results.append({"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[1]})
for target_image in target_images:
dewarped_image = dewarp.dewarp_image(target_image) # 去扭曲
angles = image_util.parse_rotation_angles(dewarped_image)
zx_ie_results = []
split_results = image_util.split(dewarped_image)
for split_result in split_results:
rotated_img = image_util.rotate(split_result["img"], int(angles[0]))
ie_results = [{"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[0]}]
if not ie_results[0]["result"] or len(ie_results[0]["result"]) < len(ie.kwargs.get("schema")):
rotated_img = image_util.rotate(split_result["img"], int(angles[1]))
ie_results.append({"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[1]})
now = util.get_default_datetime()
best_angle = ["0", 0]
for ie_result in ie_results:
if not ie_result["result"]:
continue
now = util.get_default_datetime()
best_angle = ["0", 0]
for ie_result in ie_results:
if not ie_result["result"]:
continue
result_json = json.dumps(ie_result["result"], ensure_ascii=False)
if len(result_json) > 5000:
result_json = result_json[:5000]
zx_ie_results.append(ZxIeResult(pk_phhd=phrec.pk_phhd, pk_phrec=phrec.pk_phrec, id=identity,
cfjaddress=phrec.cfjaddress, content=result_json,
rotation_angle=int(ie_result["angle"]),
x_offset=split_result["x_offset"],
y_offset=split_result["y_offset"], create_time=now, creator=HOSTNAME,
update_time=now, updater=HOSTNAME))
result_json = json.dumps(ie_result["result"], ensure_ascii=False)
if len(result_json) > 5000:
result_json = result_json[:5000]
zx_ie_results.append(ZxIeResult(pk_phhd=phrec.pk_phhd, pk_phrec=phrec.pk_phrec, id=identity,
cfjaddress=phrec.cfjaddress, content=result_json,
rotation_angle=int(ie_result["angle"]),
x_offset=split_result["x_offset"],
y_offset=split_result["y_offset"], create_time=now,
creator=HOSTNAME, update_time=now, updater=HOSTNAME))
result = merge_result(result, ie_result["result"])
result = merge_result(result, ie_result["result"])
if len(ie_result["result"]) > best_angle[1]:
best_angle = [ie_result["angle"], len(ie_result["result"])]
if len(ie_result["result"]) > best_angle[1]:
best_angle = [ie_result["angle"], len(ie_result["result"])]
angle_count[best_angle[0]] += 1
angle_count[best_angle[0]] += 1
img_angle = max(angle_count, key=angle_count.get)
if img_angle != "0":