Fix words

python/fastdeploy/pipeline/pptinypose/__init__.py

@@ -37,7 +37,7 @@ def predict(self, input_image):
 
     @property
     def detection_model_score_threshold(self):
-        """Atrribute of PPTinyPose pipeline model. Stating the score threshold for detectin model to filter bbox before inputting pptinypose model
+        """Attribute of PPTinyPose pipeline model. Stating the score threshold for detection model to filter bbox before inputting pptinypose model
 
         :return: value of detection_model_score_threshold(float)
         """

streamer/python/streamer/c_lib_wrap.py

@@ -16,9 +16,7 @@
 import os
 import sys
 
-
 try:
     from .libs.streamer_main import *
 except:
-    raise RuntimeError("FastDeploy Streamer initalized failed!")
-
+    raise RuntimeError("FastDeploy Streamer initialized failed!")

streamer/src/app/yaml_parser.cc

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #include "app/yaml_parser.h"
+
 #include "gstreamer/utils.h"
 
 namespace fastdeploy {
@@ -28,7 +29,7 @@ YamlParser::YamlParser(const std::string& config_file) {
   config_file_ = config_file;
 }
 
-void YamlParser::ParseAppConfg(AppConfig& app_config) {
+void YamlParser::ParseAppConfig(AppConfig& app_config) {
   ValidateConfig();
   auto elem = yaml_config_["app"];
 
@@ -41,9 +42,11 @@ void YamlParser::ParseAppConfg(AppConfig& app_config) {
     FDASSERT(false, "Unsupported app type: %s.", type_str.c_str());
   }
 
-  app_config.enable_perf_measurement = elem["enable-perf-measurement"].as<bool>();
+  app_config.enable_perf_measurement =
+      elem["enable-perf-measurement"].as<bool>();
   if (app_config.enable_perf_measurement) {
-    app_config.perf_interval_sec = elem["perf-measurement-interval-sec"].as<int>();
+    app_config.perf_interval_sec =
+        elem["perf-measurement-interval-sec"].as<int>();
   }
   app_config_ = app_config;
 }
@@ -78,7 +81,8 @@ std::string YamlParser::YamlToPipelineDescStr() {
   return pipeline_desc;
 }
 
-void YamlParser::ParseElement(const std::string& name, const YAML::Node& properties) {
+void YamlParser::ParseElement(const std::string& name,
+                              const YAML::Node& properties) {
   if (name == "app") return;
 
   if (name == "nvurisrcbin_list") {
@@ -93,9 +97,10 @@ void YamlParser::ParseElement(const std::string& name, const YAML::Node& propert
   elem_descs_.push_back(elem_desc);
 }
 
-void YamlParser::ParseNvUriSrcBinList(const std::string& name, const YAML::Node& properties) {
+void YamlParser::ParseNvUriSrcBinList(const std::string& name,
+                                      const YAML::Node& properties) {
   std::string elem_name = "nvurisrcbin";
-  
+
   auto uri_list = properties["uri-list"].as<std::vector<std::string>>();
   auto pad_prefix = properties["pad-prefix"].as<std::string>();
   for (size_t i = 0; i < uri_list.size(); i++) {
@@ -111,7 +116,8 @@ void YamlParser::ParseNvUriSrcBinList(const std::string& name, const YAML::Node&
   }
 }
 
-std::string YamlParser::ParseProperty(const YAML::Node& name, const YAML::Node& value) {
+std::string YamlParser::ParseProperty(const YAML::Node& name,
+                                      const YAML::Node& value) {
   std::string prop_name = name.as<std::string>();
   std::string prop_value = value.as<std::string>();
 

streamer/src/app/yaml_parser.h

@@ -31,7 +31,7 @@ class YamlParser {
    */
   explicit YamlParser(const std::string& config_file);
 
-  void ParseAppConfg(AppConfig& app_config);
+  void ParseAppConfig(AppConfig& app_config);
 
   void ValidateConfig();
 

streamer/src/fd_streamer.cc

@@ -13,9 +13,10 @@
 // limitations under the License.
 
 #include "fd_streamer.h"
-#include "app/yaml_parser.h"
+
 #include "app/video_analytics.h"
 #include "app/video_decoder.h"
+#include "app/yaml_parser.h"
 #include "fastdeploy/utils/unique_ptr.h"
 
 namespace fastdeploy {
@@ -24,7 +25,7 @@ namespace streamer {
 bool FDStreamer::Init(const std::string& config_file) {
   AppConfig app_config;
   YamlParser parser(config_file);
-  parser.ParseAppConfg(app_config);
+  parser.ParseAppConfig(app_config);
   if (app_config.type == AppType::VIDEO_ANALYTICS) {
     app_ = utils::make_unique<VideoAnalyticsApp>(app_config);
     auto casted_app = dynamic_cast<VideoAnalyticsApp*>(app_.get());
@@ -39,13 +40,9 @@ bool FDStreamer::Init(const std::string& config_file) {
   return true;
 }
 
-bool FDStreamer::Run() {
-  return app_->Run();
-}
+bool FDStreamer::Run() { return app_->Run(); }
 
-bool FDStreamer::RunAsync() {
-  return app_->RunAsync();
-}
+bool FDStreamer::RunAsync() { return app_->RunAsync(); }
 
 bool FDStreamer::TryPullFrame(FDTensor& tensor, int timeout_ms) {
   auto casted_app = dynamic_cast<VideoDecoderApp*>(app_.get());

tutorials/multi_thread/python/pipeline/multi_thread_process_ocr.py

@@ -253,7 +253,7 @@ def get_result(self):
         thread_num = args.thread_num
         image_num_each_thread = int(len(imgs_list) / thread_num)
         # unless you want independent model in each thread, actually model.clone()
-        # is the same as model when creating thead because of the existence of
+        # is the same as model when creating thread because of the existence of
         # GIL(Global Interpreter Lock) in python. In addition, model.clone() will consume
         # additional memory to store independent member variables
         for i in range(thread_num):

tutorials/multi_thread/python/single_model/multi_thread_process.py

@@ -151,7 +151,7 @@ def get_result(self):
         thread_num = args.thread_num
         image_num_each_thread = int(len(imgs_list) / thread_num)
         # unless you want independent model in each thread, actually model.clone()
-        # is the same as model when creating thead because of the existence of
+        # is the same as model when creating thread because of the existence of
         # GIL(Global Interpreter Lock) in python. In addition, model.clone() will consume
         # additional memory to store independent member variables
         for i in range(thread_num):