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quantumliu de4404244b | 1 year ago | |
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datas | 1 year ago | |
examples | 1 year ago | |
logos | 2 years ago | |
openiva | 1 year ago | |
weights | 2 years ago | |
.gitignore | 1 year ago | |
LICENSE | 2 years ago | |
README.md | 2 years ago | |
README_zh.md | 2 years ago | |
requirements.txt | 2 years ago | |
setup.py | 1 year ago |
English | 中文
OpenIVA is an end-to-end intelligent video analytics development toolkit based on different inference backends, designed to help individual users and start-ups quickly launch their own video AI services.
OpenIVA implements varied mainstream facial recognition, object detection, segmentation and landmark detection algorithms. And it provides an efficient and lightweight service deployment framework with a modular design. Users only need to replace the algorithm model used for their own tasks.
Run
python test_landmark.py
batchsize=8
, top_k=68
, 67 faces in the image
Face detection
Model face_detector_640_dy_sim
onnxruntime EPs | FPS | faces per sec |
---|---|---|
CPU | 32 | 2075 |
OpenVINO | 81 | 5374 |
CUDA | 105 | 7074 |
TensorRT(FP32) | 124 | 7948 |
TensorRT(FP16) | 128 | 8527 |
Face landmark
Model landmarks_68_pfld_dy_sim
onnxruntime EPs | faces per sec |
---|---|
CPU | 69 |
OpenVINO | 890 |
CUDA | 2061 |
TensorRT(FP32) | 2639 |
TensorRT(FP16) | 3131 |
Run
python test_face.py
batchsize=8
arc_mbv2_ccrop_sim
onnxruntime EPs | faces per sec |
---|---|
CPU | 212 |
OpenVINO | 865 |
CUDA | 1790 |
TensorRT(FP32) | 2132 |
TensorRT(FP16) | 2812 |
Run
python test_yolo.py
batchsize=8
, 4 objects in the image
YOLOX objects detect
Model yolox_s(ms_coco)
onnxruntime EPs | FPS | Objects per sec |
---|---|---|
CPU | 9.3 | 37.2 |
OpenVINO | 13 | 52 |
CUDA | 77 | 307 |
TensorRT(FP32) | 95 | 380 |
TensorRT(FP16) | 128 | 512 |
Model yolox_m(ms_coco)
onnxruntime EPs | FPS | Objects per sec |
---|---|---|
CPU | 4 | 16 |
OpenVINO | 5.5 | 22 |
CUDA | 46.8 | 187 |
TensorRT(FP32) | 64 | 259 |
TensorRT(FP16) | 119 | 478 |
Model yolox_nano(ms_coco)
onnxruntime EPs | FPS | Objects per sec |
---|---|---|
CPU | 47 | 188 |
OpenVINO | 80 | 320 |
CUDA | 210 | 842 |
TensorRT(FP32) | 244 | 977 |
TensorRT(FP16) | 269 | 1079 |
Model yolox_tiny(ms_coco)
onnxruntime EPs | FPS | Objects per sec |
---|---|---|
CPU | 33 | 133 |
OpenVINO | 43 | 175 |
CUDA | 209 | 839 |
TensorRT(FP32) | 248 | 995 |
TensorRT(FP16) | 327 | 1310 |
Asynchronous & multithreading
Lightweight service
GUI visualization tools
Common algorithms
Facial recognition
Face detection
Face landmark
Face embedding
Object detection
Semantic/Instance segmentation
Scene classification
Data I/O
OpenIVA is an end-to-end intelligent video analytics development toolkit based on different inference backends, which implements varied mainstream facial recognition, object detection, tracking and keypoint detection algorithms in modular design.
Python Markdown Text other
Dear OpenI User
Thank you for your continuous support to the Openl Qizhi Community AI Collaboration Platform. In order to protect your usage rights and ensure network security, we updated the Openl Qizhi Community AI Collaboration Platform Usage Agreement in January 2024. The updated agreement specifies that users are prohibited from using intranet penetration tools. After you click "Agree and continue", you can continue to use our services. Thank you for your cooperation and understanding.
For more agreement content, please refer to the《Openl Qizhi Community AI Collaboration Platform Usage Agreement》