diff --git a/demos/python_demos/image_retrieval_demo/README.md b/demos/python_demos/image_retrieval_demo/README.md index 3ca31ae2a1c..f3768a63a17 100644 --- a/demos/python_demos/image_retrieval_demo/README.md +++ b/demos/python_demos/image_retrieval_demo/README.md @@ -9,7 +9,7 @@ This demo demonstrates how to run Image Retrieval models using OpenVINO™. The demo application expects an image retrieval model in the Intermediate Representation (IR) format. As input, the demo application takes: -* a path to a list of images represeneted by textfile with following format 'path_to_image' 'ID' `--images` +* a path to a list of images represented by textfile with following format 'path_to_image' 'ID' `--images` * a path to a video file or a device node of a web-camera specified with a command line argument `--video` The demo workflow is the following: diff --git a/demos/security_barrier_camera_demo/README.md b/demos/security_barrier_camera_demo/README.md index 696d9a564e2..771ee151daf 100644 --- a/demos/security_barrier_camera_demo/README.md +++ b/demos/security_barrier_camera_demo/README.md @@ -98,7 +98,7 @@ To do inference for two video inputs using two asynchronous infer request on FPG ./security_barrier_camera_demo -i /inputVideo_0.mp4 /inputVideo_1.mp4 -m /vehicle-license-plate-detection-barrier-0106.xml -m_va /vehicle-attributes-recognition-barrier-0039.xml -m_lpr /license-plate-recognition-barrier-0001.xml -d HETERO:FPGA,CPU -d_va HETERO:FPGA,CPU -d_lpr HETERO:FPGA,CPU -nireq 2 ``` -> **NOTE**: For the `-tag` option (HDDL plugin only), you must specify the number of VPUs for each network in the `hddl_service.config` file located in the `/deployment_tools/inference_engine/external/hddl/config/` direcrtory using the following tags: +> **NOTE**: For the `-tag` option (HDDL plugin only), you must specify the number of VPUs for each network in the `hddl_service.config` file located in the `/deployment_tools/inference_engine/external/hddl/config/` directory using the following tags: > * `tagDetect` for the Vehicle and License Plate Detection network > * `tagAttr` for the Vehicle Attributes Recognition network > * `tagLPR` for the License Plate Recognition network @@ -114,7 +114,7 @@ To do inference for two video inputs using two asynchronous infer request on FPG ### Optimization Hints for Heterogeneous Scenarios with FPGA -If you build the Inference Engine with the OMP, you can use the following parameters for Heterogeneous scenarois: +If you build the Inference Engine with the OMP, you can use the following parameters for Heterogeneous scenarios: * `OMP_NUM_THREADS`: Specifies number of threads to use. For heterogeneous scenarios with FPGA, when several inference requests are used asynchronously, limiting the number of CPU threads with `OMP_NUM_THREADS` allows to avoid competing for resources between threads. For the Security Barrier Camera Demo, recommended value is `OMP_NUM_THREADS=1`. * `KMP_BLOCKTIME`: Sets the time, in milliseconds, that a thread should wait, after completing the execution of a parallel region, before sleeping. The default value is 200ms, which is not optimal for the demo. Recommended value is `KMP_BLOCKTIME=1`. diff --git a/demos/text_detection_demo/README.md b/demos/text_detection_demo/README.md index a0af006301d..60400310807 100644 --- a/demos/text_detection_demo/README.md +++ b/demos/text_detection_demo/README.md @@ -32,7 +32,7 @@ Options: -m_tr "" Required. Path to the Text Recognition model (.xml) file. -dt "" Required. Input data type: "image" (for a single image), "list" (for a text file where images paths are listed), "video" (for a saved video), "webcam" (for a webcamera device). By default, it is "image". -m_tr_ss "" Optional. Symbol set for the Text Recognition model. - -cc Optional. If it is set, then in case of absence of the Text Detector, the Text Reconition model takes a central image crop as an input, but not full frame. + -cc Optional. If it is set, then in case of absence of the Text Detector, the Text Recognition model takes a central image crop as an input, but not full frame. -w_td "" Optional. Input image width for Text Detection model. -h_td "" Optional. Input image height for Text Detection model. -thr "" Optional. Specify a recognition confidence threshold. Text detection candidates with text recognition confidence below specified threshold are rejected. diff --git a/demos/text_detection_demo/text_detection_demo.hpp b/demos/text_detection_demo/text_detection_demo.hpp index ce41f3fb3d6..c9502ea150b 100644 --- a/demos/text_detection_demo/text_detection_demo.hpp +++ b/demos/text_detection_demo/text_detection_demo.hpp @@ -16,7 +16,7 @@ static const char text_detection_model_message[] = "Required. Path to the Text D static const char text_recognition_model_message[] = "Required. Path to the Text Recognition model (.xml) file."; static const char text_recognition_model_symbols_set_message[] = "Optional. Symbol set for the Text Recognition model."; static const char text_central_image_crop_message[] = "Optional. If it is set, then in case of absence of the Text Detector, " - "the Text Reconition model takes a central image crop as an input, but not full frame."; + "the Text Recognition model takes a central image crop as an input, but not full frame."; static const char image_width_for_text_detection_model_message[] = "Optional. Input image width for Text Detection model."; static const char image_height_for_text_detection_model_message[] = "Optional. Input image height for Text Detection model."; static const char text_recognition_threshold_message[] = "Optional. Specify a recognition confidence threshold. Text detection candidates with " diff --git a/models/intel/person-attributes-recognition-crossroad-0230/description/person-attributes-recognition-crossroad-0230.md b/models/intel/person-attributes-recognition-crossroad-0230/description/person-attributes-recognition-crossroad-0230.md index ffdc40049cc..015f04bc541 100644 --- a/models/intel/person-attributes-recognition-crossroad-0230/description/person-attributes-recognition-crossroad-0230.md +++ b/models/intel/person-attributes-recognition-crossroad-0230/description/person-attributes-recognition-crossroad-0230.md @@ -1,7 +1,7 @@ # person-attributes-recognition-crossroad-0230 ## Use Case and High-Level Description -This model presents a person attributes classification algorithm analysis scenario. It produces probability of person attributions existing on the sample and a position of two point on sample, whiches can be used for color prob (like, color picker in graphical editors) +This model presents a person attributes classification algorithm analysis scenario. It produces probability of person attributions existing on the sample and a position of two point on sample, which can be used for color prob (like, color picker in graphical editors) ## Examples diff --git a/models/intel/person-attributes-recognition-crossroad-0230/model.yml b/models/intel/person-attributes-recognition-crossroad-0230/model.yml index b721de655f2..f80df16e88b 100644 --- a/models/intel/person-attributes-recognition-crossroad-0230/model.yml +++ b/models/intel/person-attributes-recognition-crossroad-0230/model.yml @@ -15,7 +15,7 @@ description: >- This model presents a person attributes classification algorithm analysis scenario. It produces probability of person attributions existing on the sample and a - position of two point on sample, whiches can be used for color prob (like, color + position of two point on sample, which can be used for color prob (like, color picker in graphical editors) task_type: object_attributes files: