Add uie python example and doc (#221)

* add fastdeploy.text.UIEModel

* Add uie python example

* Add one schema for cpp demo

* Add ConvertUIEResultToDict for pretty the uie result in python

* remove default args for SchemaNode

* Add uie example args

* Add uie python api desc

* Add infer.py usage

* truncate some example output

* Add uie schema usage

* Add uie result md

* Add uie c++ api doc

examples/text/uie/cpp/infer.cc

@@ -71,7 +71,7 @@ int main(int argc, char* argv[]) {
   auto predictor =
       fastdeploy::text::UIEModel(model_path, param_path, vocab_path, 0.5, 128,
                                  {"时间", "选手", "赛事名称"}, option);
-  fastdeploy::FDINFO << "After init predictor" << std::endl;
+  std::cout << "After init predictor" << std::endl;
   std::vector<std::unordered_map<std::string, std::vector<UIEResult>>> results;
   // Named Entity Recognition
   predictor.Predict({"2月8日上午北京冬奥会自由式滑雪女子大跳台决赛中中国选手谷"
@@ -80,6 +80,16 @@ int main(int argc, char* argv[]) {
   std::cout << results << std::endl;
   results.clear();
 
+  predictor.SetSchema(
+      {"肿瘤的大小", "肿瘤的个数", "肝癌级别", "脉管内癌栓分级"});
+  predictor.Predict({"（右肝肿瘤）肝细胞性肝癌（II-"
+                     "III级，梁索型和假腺管型），肿瘤包膜不完整，紧邻肝被膜，侵"
+                     "及周围肝组织，未见脉管内癌栓（MVI分级：M0级）及卫星子灶形"
+                     "成。（肿物1个，大小4.2×4.0×2.8cm）。"},
+                    &results);
+  std::cout << results << std::endl;
+  results.clear();
+
   // Relation Extraction
   predictor.SetSchema(
       {SchemaNode("竞赛名称", {SchemaNode("主办方"), SchemaNode("承办方"),