AI Based Object Redaction/Performance: Difference between revisions
No edit summary |
No edit summary |
||
| Line 1: | Line 1: | ||
<noinclude> | <noinclude> | ||
{{AI Based Object Redaction/Head|previous=|next=|metakeywords=}} | {{AI Based Object Redaction/Head|previous=Examples|next=Performance/Jetson_Xavier_NX|metakeywords=}} | ||
</noinclude> | </noinclude> | ||
<!---- | <!---- | ||
{{DISPLAYTITLE: | {{DISPLAYTITLE:AI Based Object Redaction - Performance|noerror}} | ||
----> | ----> | ||
| Line 17: | Line 17: | ||
* The tracker is implemented only with support for CPU. | * The tracker is implemented only with support for CPU. | ||
Check the following links for performance: | Check the following links for performance: | ||
* [[ | |||
*;[[AI_Based_Object_Redaction/Performance/Jetson_Xavier_NX|Jetson Xavier NX]] | |||
* [[ | *;[[AI_Based_Object_Redaction/Performance/Jetson_Xavier_AGX|Jetson Xavier AGX]] | ||
<noinclude> | <noinclude> | ||
{{AI Based Object Redaction/Foot||}} | {{AI Based Object Redaction/Foot|Examples|Performance/Jetson_Xavier_NX}} | ||
</noinclude> | </noinclude> | ||
Revision as of 17:02, 28 December 2023
| AI Based Object Redaction |
|---|
 |
| Overview |
| Getting Started |
| GStreamer Plugin |
| Examples |
| Performance |
| Troubleshooting |
| FAQ |
| Contact Us |
The library has four major consuming methods: convert the input buffer to the desired format and size of the AI model, the detection of the desired object done by the ONNX model, tracking and the application of the redaction effect.
For testing purposes, take into account the following points:
- Jetpack 5.1.X
- Tested with GPU and CPU only. For GPU, execution is done with TensorRT and CUDA.
- The library offers two approaches: each method used separately and all together using the apply method.
- The metrics measured are CPU and GPU consumption, processing time, and FPS.
- The tracker is implemented only with support for CPU.
Check the following links for performance: