update PP-ShiTu inference doc

deploy/cpp_shitu/src/main.cpp

@@ -174,6 +174,10 @@ int main(int argc, char **argv) {
            .as<std::string>()
            .empty()) {
     detector_ptr = new Detection::ObjectDetector(config.config_file);
+  } else {
+    std::cout << "Found 'Global.det_inference_model_dir' empty, so "
+                 "det_predictor is disabled"
+              << std::endl;
   }
 
   // initialize feature_extractor

deploy/python/predict_system.py

@@ -34,7 +34,7 @@ class SystemPredictor(object):
 
         if not config["Global"]["det_inference_model_dir"]:
             logger.info(
-                f"find 'Global.det_inference_model_dir' empty({config['Global']['det_inference_model_dir']}), so det_predictor is disabled"
+                f"Found 'Global.det_inference_model_dir' empty({config['Global']['det_inference_model_dir']}), so det_predictor is disabled"
             )
             self.det_predictor = None
         else:

docs/zh_CN/deployment/PP-ShiTu/cpp.md

@@ -348,11 +348,25 @@ cd ..
   ./build/pp_shitu -c inference_drink.yaml
   ```
 
-  以 `drink_dataset_v2.0/test_images/nongfu_spring.jpeg` 作为输入图像，则执行上述推理命令可以得到如下结果
+  默认以 `../drink_dataset_v2.0/test_images/100.jpeg` 作为输入图像，则执行上述推理命令可以得到如下结果
 
   ```log
-  ../../deploy/drink_dataset_v2.0/test_images/nongfu_spring.jpeg:
-        result0: bbox[0, 0, 729, 1094], score: 0.688691, label: 农夫山泉-饮用天然水
+  ../drink_dataset_v2.0/test_images/100.jpeg:
+        result0: bbox[437, 72, 660, 723], score: 0.769916, label: 元气森林
+        result1: bbox[220, 71, 449, 685], score: 0.695485, label: 元气森林
+        result2: bbox[795, 104, 979, 653], score: 0.626963, label: 元气森林
+  ```
+
+  识别流程支持灵活配置，用户可以选择不使用主体检测模型，而直接将单幅整图输入到特征提取模型，计算特征向量供后续检索使用，从而减少整体识别流程的耗时。只需将`Global.det_inference_model_dir`后的字段改为`null`或者`""`，再运行以下推理命令即可
+  ```shell
+  ./build/pp_shitu -c inference_drink.yaml
+  ```
+
+  最终输出结果如下
+  ```log
+  Found 'Global.det_inference_model_dir' empty, so det_predictor is disabled
+  ../drink_dataset_v2.0/test_images/100.jpeg:
+          result0: bbox[0, 0, 1199, 801], score: 0.568903, label: 元气森林
   ```
 
   由于python和C++的opencv实现存在部分不同，可能导致python推理和C++推理结果有微小差异。但基本不影响最终的检索结果。

docs/zh_CN/quick_start/quick_start_recognition.md

@@ -234,7 +234,7 @@ python3.7 python/predict_system.py -c configs/inference_general.yaml -o Global.u
 
 最终输出结果如下
 ```log
-INFO: find 'Global.det_inference_model_dir' empty(), so det_predictor is disabled
+INFO: Found 'Global.det_inference_model_dir' empty(), so det_predictor is disabled
 [{'bbox': [0, 0, 1200, 802], 'rec_docs': '元气森林', 'rec_scores': 0.5696486}]
 ```