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AI2mark.py

+from numpy import NaN
+import pandas as pd
+import json
+import re
+src=pd.read_excel("第五批.xls")
+alg_result=src['alg_result'].values.tolist()
+src_density_typeO=src['src_density_type'].values.tolist()
+
+focus=[]
+tools=[]
+diy=[]
+filetype=[]
+cnt=[]
+series_id=[]
+src_density_type=[]
+for i,txt in enumerate(alg_result):
+    if alg_result[i]!=alg_result[i]:
+        continue
+    if src_density_typeO[i]==20:
+        src_density_type.append('')
+    else:
+        src_density_type.append(src_density_typeO[i])
+    focus.append("ANNO3")
+    tools.append("CUBOID")
+    diy.append("")
+    filetype.append("")
+    text=json.loads(txt)
+    srcBbox=text["srcBbox"]
+    srcHU_values_path=text['srcNodule_mask_path']
+    if srcHU_values_path=="":
+        srcHU_values_path=text['srcHU_values_path']
+    re1 = r'shjss-aitrox/(.*?)_NODULE'
+    reResult = re.findall(re1, srcHU_values_path)
+    print(reResult)
+    studyid,seriesid=reResult[0].split('/')
+    series_id.append(seriesid)
+    tmp="{\"lesionId\":0,\"position\":"+str(srcBbox)+"}"
+    cnt.append(tmp)
+
+    
+output=pd.DataFrame({"序列号":series_id,"病灶":focus,"影像工具":tools,"影像结果":cnt,"自定义内容":diy,"文件类型":filetype,"肺结节类型":src_density_type})
+output.to_csv("第五批output.csv",index=False,encoding="utf_8_sig")
+