在自动识别时将图片转正并上传到云端
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@@ -105,4 +105,8 @@
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1. 照片涂抹重新添加方向识别与矫正,因为照片审核人员暂无法保证所有图片的方向正确
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1. 照片涂抹重新添加方向识别与矫正,因为照片审核人员暂无法保证所有图片的方向正确
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2. 添加照片涂抹错误分析
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2. 添加照片涂抹错误分析
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3. 优化图片分割和拓展,对横竖图片分别进行优化
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3. 优化图片分割和拓展,对横竖图片分别进行优化
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4. 优化镜像构建,将依赖与内容分开,显著提高构建速度
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4. 优化镜像构建,将依赖与内容分开,显著提高构建速度
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18. 版本号:1.11.0
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1. 修正含旋转的信息抽取结果的绘制
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2. 调整zx_ocr表名为zx_ie_result
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3. 在自动识别时将图片转正并上传到云端
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@@ -1,6 +1,6 @@
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x-env:
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x-env:
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&template
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&template
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image: fcb_photo_review:1.10.4
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image: fcb_photo_review:1.11.0
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restart: always
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restart: always
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services:
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services:
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@@ -3,6 +3,7 @@ import logging
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import os
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import os
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import tempfile
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import tempfile
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import time
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import time
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from collections import defaultdict
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from time import sleep
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from time import sleep
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import cv2
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import cv2
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@@ -67,25 +68,25 @@ def request_ie_result(task_enum, phrecs):
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# 关键信息提取
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# 关键信息提取
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def information_extraction(ie, phrecs):
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def information_extraction(ie, phrecs, identity):
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result = {}
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result = {}
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# 同一批图的标识
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identity = int(time.time())
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for phrec in phrecs:
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for phrec in phrecs:
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img_path = ufile.get_private_url(phrec.cfjaddress)
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img_path = ufile.get_private_url(phrec.cfjaddress)
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if not img_path:
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if not img_path:
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continue
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continue
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split_results = image_util.split(img_path)
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image = image_util.read(img_path)
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angles = image_util.parse_rotation_angles(image)
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angle_count = defaultdict(int, {"0": 0})
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split_results = image_util.split(image)
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for split_result in split_results:
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for split_result in split_results:
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angles = image_util.parse_rotation_angles(split_result["img"])
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rotated_img = image_util.rotate(split_result["img"], int(angles[0]))
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rotated_img = image_util.rotate(split_result["img"], int(angles[0]))
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ie_results = [{"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[0]}]
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ie_results = [{"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[0]}]
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if not ie_results[0] or len(ie_results[0]) < len(ie.kwargs.get("schema")):
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if not ie_results[0]["result"] or len(ie_results[0]["result"]) < len(ie.kwargs.get("schema")):
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rotated_img = image_util.rotate(split_result["img"], int(angles[1]))
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rotated_img = image_util.rotate(split_result["img"], int(angles[1]))
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ie_results.append({"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[1]})
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ie_results.append({"result": ie_temp_image(ie, OCR, rotated_img), "angle": angles[1]})
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now = util.get_default_datetime()
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now = util.get_default_datetime()
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best_angle = ["0", 0]
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for ie_result in ie_results:
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for ie_result in ie_results:
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result_json = json.dumps(ie_result["result"], ensure_ascii=False)
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result_json = json.dumps(ie_result["result"], ensure_ascii=False)
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if len(result_json) > 5000:
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if len(result_json) > 5000:
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@@ -101,6 +102,23 @@ def information_extraction(ie, phrecs):
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result = merge_result(result, ie_result["result"])
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result = merge_result(result, ie_result["result"])
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if len(ie_result["result"]) > best_angle[1]:
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best_angle = [ie_result["angle"], len(ie_result["result"])]
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angle_count[best_angle[0]] += 1
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img_angle = max(angle_count, key=angle_count.get)
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if img_angle != "0":
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image = image_util.rotate(image, int(img_angle))
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with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as temp_file:
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cv2.imwrite(temp_file.name, image)
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try:
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ufile.upload_file(phrec.cfjaddress, temp_file.name)
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except Exception as e:
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logging.error(f"上传图片({phrec.cfjaddress})失败", exc_info=e)
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finally:
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util.delete_temp_file(temp_file.name)
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return result
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return result
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@@ -159,8 +177,8 @@ def save_or_update_ie(table, pk_phhd, data):
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session.close()
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session.close()
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def settlement_task(pk_phhd, settlement_list):
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def settlement_task(pk_phhd, settlement_list, identity):
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settlement_list_ie_result = information_extraction(SETTLEMENT_IE, settlement_list)
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settlement_list_ie_result = information_extraction(SETTLEMENT_IE, settlement_list, identity)
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settlement_data = {
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settlement_data = {
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"pk_phhd": pk_phhd,
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"pk_phhd": pk_phhd,
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"name": handle_name(get_best_value_in_keys(settlement_list_ie_result, PATIENT_NAME)),
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"name": handle_name(get_best_value_in_keys(settlement_list_ie_result, PATIENT_NAME)),
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@@ -192,8 +210,8 @@ def settlement_task(pk_phhd, settlement_list):
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save_or_update_ie(ZxIeSettlement, pk_phhd, settlement_data)
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save_or_update_ie(ZxIeSettlement, pk_phhd, settlement_data)
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def discharge_task(pk_phhd, discharge_record):
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def discharge_task(pk_phhd, discharge_record, identity):
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discharge_record_ie_result = information_extraction(DISCHARGE_IE, discharge_record)
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discharge_record_ie_result = information_extraction(DISCHARGE_IE, discharge_record, identity)
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discharge_data = {
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discharge_data = {
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"pk_phhd": pk_phhd,
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"pk_phhd": pk_phhd,
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"hospital": handle_hospital(get_best_value_in_keys(discharge_record_ie_result, HOSPITAL)),
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"hospital": handle_hospital(get_best_value_in_keys(discharge_record_ie_result, HOSPITAL)),
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@@ -233,8 +251,8 @@ def discharge_task(pk_phhd, discharge_record):
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save_or_update_ie(ZxIeDischarge, pk_phhd, discharge_data)
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save_or_update_ie(ZxIeDischarge, pk_phhd, discharge_data)
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def cost_task(pk_phhd, cost_list):
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def cost_task(pk_phhd, cost_list, identity):
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cost_list_ie_result = information_extraction(COST_IE, cost_list)
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cost_list_ie_result = information_extraction(COST_IE, cost_list, identity)
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cost_data = {
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cost_data = {
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"pk_phhd": pk_phhd,
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"pk_phhd": pk_phhd,
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"name": handle_name(get_best_value_in_keys(cost_list_ie_result, PATIENT_NAME)),
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"name": handle_name(get_best_value_in_keys(cost_list_ie_result, PATIENT_NAME)),
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@@ -266,9 +284,11 @@ def photo_review(pk_phhd):
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elif phrec.cRectype == "4":
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elif phrec.cRectype == "4":
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cost_list.append(phrec)
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cost_list.append(phrec)
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settlement_task(pk_phhd, settlement_list)
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# 同一批图的标识
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discharge_task(pk_phhd, discharge_record)
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identity = int(time.time())
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cost_task(pk_phhd, cost_list)
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settlement_task(pk_phhd, settlement_list, identity)
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discharge_task(pk_phhd, discharge_record, identity)
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cost_task(pk_phhd, cost_list, identity)
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def main():
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def main():
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