Comments (1)
The internal logic of YoloV8 should be thread safe, however GPUs sometimes cannot perform inference in parallel, for this there is the property YoloV8parameters.SuppressParallelInference
which when it is set to true
the inference is performed inside a lock block, the preprocess and postprocess will still work in parallel to speed up the results.
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Related Issues (20)
- Result serialization and deserialization HOT 1
- How to use the model in a multithreaded application HOT 3
- inferred HOT 1
- How to package YOLOv8 as DLL and call it HOT 3
- After upgrading from version 1.4 to version 1.5-1.6, it became very difficult to detect. HOT 3
- To improve efficiency, it is recommended to consider modifying the Preprocess function. HOT 9
- Multithreaded execution error. HOT 1
- Model not supported HOT 6
- System.InvalidOperationException: 'The loaded model does not support this task' HOT 3
- Results different between python and .net HOT 1
- 请问是不是只能在.net上边使用,不能在.net Framework项目上用?
- Solving problems with multithreading when working with GPU HOT 6
- Application hangs on Detect() with GPU HOT 1
- Understanding Yolov8 Task Input and Output Formats in OnnxRuntime HOT 1
- Difference between Python and DotNet HOT 1
- How to enable GPU HOT 3
- Inconsistent model results HOT 3
- Suggest adding OBB support HOT 2
- [discussion] optimize code logic to improve operational efficiency HOT 2
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