init README of deepdoc, add picture processer. (#71)

* init README of deepdoc, add picture processer.

* add resume parsing

deepdoc/parser/resume/entities/schools.py

@@ -0,0 +1,62 @@
+# -*- coding: UTF-8 -*-
+import os, json,re,copy
+import pandas as pd
+current_file_path = os.path.dirname(os.path.abspath(__file__))
+TBL = pd.read_csv(os.path.join(current_file_path, "res/schools.csv"), sep="\t", header=0).fillna("")
+TBL["name_en"] = TBL["name_en"].map(lambda x: x.lower().strip())
+GOOD_SCH = json.load(open(os.path.join(current_file_path, "res/good_sch.json"), "r"))
+GOOD_SCH = set([re.sub(r"[,. &（）()]+", "", c) for c in GOOD_SCH])
+
+
+def loadRank(fnm):
+    global TBL
+    TBL["rank"] = 1000000
+    with open(fnm, "r",encoding='UTF-8') as f:
+        while True:
+            l = f.readline()
+            if not l:break
+            l = l.strip("\n").split(",")
+            try:
+                nm,rk = l[0].strip(),int(l[1])
+                #assert len(TBL[((TBL.name_cn == nm) | (TBL.name_en == nm))]),f"<{nm}>"
+                TBL.loc[((TBL.name_cn == nm) | (TBL.name_en == nm)), "rank"] = rk
+            except Exception as e:
+                pass
+
+
+loadRank(os.path.join(current_file_path, "res/school.rank.csv"))
+
+
+def split(txt):
+    tks = []
+    for t in re.sub(r"[ \t]+", " ",txt).split(" "):
+        if tks and re.match(r".*[a-zA-Z]$", tks[-1]) and \
+           re.match(r"[a-zA-Z]", t) and tks:
+            tks[-1] = tks[-1] + " " + t
+        else:tks.append(t)
+    return tks
+
+
+def select(nm):
+    global TBL
+    if not nm:return 
+    if isinstance(nm, list):nm = str(nm[0])
+    nm = split(nm)[0]
+    nm = str(nm).lower().strip()
+    nm = re.sub(r"[(（][^()（）]+[)）]", "", nm.lower())
+    nm = re.sub(r"(^the |[,.&（）();；·]+|^(英国|美国|瑞士))", "", nm)
+    nm = re.sub(r"大学.*学院", "大学", nm)
+    tbl = copy.deepcopy(TBL)
+    tbl["hit_alias"] = tbl["alias"].map(lambda x:nm in set(x.split("+")))
+    res = tbl[((tbl.name_cn == nm) | (tbl.name_en == nm) | (tbl.hit_alias == True))]
+    if res.empty:return
+
+    return json.loads(res.to_json(orient="records"))[0]
+
+
+def is_good(nm):
+    global GOOD_SCH
+    nm = re.sub(r"[(（][^()（）]+[)）]", "", nm.lower())
+    nm = re.sub(r"[''`‘’“”,. &（）();；]+", "", nm)
+    return nm in GOOD_SCH
+