Add models benchmarks
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55
README.md
55
README.md
@@ -4,7 +4,6 @@ NVIDIA DeepStream SDK 6.1 / 6.0.1 / 6.0 configuration for YOLO models
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### Future updates
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* Models benchmarks
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* DeepStream tutorials
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* YOLOX support
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* YOLOv6 support
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@@ -27,6 +26,7 @@ NVIDIA DeepStream SDK 6.1 / 6.0.1 / 6.0 configuration for YOLO models
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* **PP-YOLOE support**
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* **YOLOv7 support**
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* **Optimized NMS** [#142](https://github.com/marcoslucianops/DeepStream-Yolo/issues/142)
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* **Models benchmarks**
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##
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@@ -98,7 +98,58 @@ NVIDIA DeepStream SDK 6.1 / 6.0.1 / 6.0 configuration for YOLO models
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### Benchmarks
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New tests comming soon.
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#### Config
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```
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board = NVIDIA Tesla V100 16GB (AWS: p3.2xlarge)
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batch-size = 1
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eval = val2017 (COCO)
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sample = 1920x1080 video
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```
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**NOTE**: Used maintain-aspect-ratio=1 in config_infer file for YOLOv4 (with letter_box=1), YOLOv5 and YOLOR models.
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#### NMS config
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- Eval
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```
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nms-iou-threshold = 0.6 / 0.65 (YOLOv5, YOLOR, YOLOv7 PyTorch) / 0.7 (PP-YOLOE)
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pre-cluster-threshold = 0.001
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topk = 300
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```
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- Test
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```
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nms-iou-threshold = 0.45 / 0.7 (PP-YOLOE)
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pre-cluster-threshold = 0.25
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topk = 300
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```
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#### Results
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**NOTE**: * = PyTorch
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| DeepStream | Precision | Resolution | IoU=0.5:0.95 | IoU=0.5 | IoU=0.75 | FPS<br />(without display) |
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|:------------------:|:---------:|:----------:|:------------:|:-------:|:--------:|:--------------------------:|
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| PP-YOLOE-x | FP16 | 640 | 0.506 | 0.681 | 0.551 | 116.54 |
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| PP-YOLOE-l | FP16 | 640 | 0.498 | 0.674 | 0.545 | 187.93 |
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| PP-YOLOE-m | FP16 | 640 | 0.476 | 0.646 | 0.522 | 257.42 |
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| PP-YOLOE-s (400) | FP16 | 640 | 0.422 | 0.589 | 0.463 | 465.23 |
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| YOLOv7* | FP16 | 640 | 0.476 | 0.660 | 0.518 | 237.32 |
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| YOLOv7-Tiny Leaky* | FP16 | 640 | 0.345 | 0.516 | 0.372 | 611.24 |
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| YOLOv7-Tiny Leaky* | FP16 | 416 | 0.328 | 0.492 | 0.348 | 633.81 |
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| YOLOv5x6 6.1 | FP16 | 1280 | 0.508 | 0.683 | 0.554 | 54.88 |
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| YOLOv5l6 6.1 | FP16 | 1280 | 0.494 | 0.668 | 0.540 | 87.86 |
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| YOLOv5m6 6.1 | FP16 | 1280 | 0.469 | 0.644 | 0.514 | 142.68 |
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| YOLOv5s6 6.1 | FP16 | 1280 | 0.399 | 0.581 | 0.438 | 271.19 |
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| YOLOv5n6 6.1 | FP16 | 1280 | 0.317 | 0.487 | 0.344 | 392.20 |
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| YOLOv5x 6.1 | FP16 | 640 | 0.470 | 0.652 | 0.513 | 152.99 |
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| YOLOv5l 6.1 | FP16 | 640 | 0.454 | 0.636 | 0.496 | 247.60 |
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| YOLOv5m 6.1 | FP16 | 640 | 0.421 | 0.604 | 0.458 | 375.06 |
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| YOLOv5s 6.1 | FP16 | 640 | 0.344 | 0.528 | 0.371 | 602.44 |
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| YOLOv5n 6.1 | FP16 | 640 | 0.247 | 0.413 | 0.256 | 629.04 |
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##
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@@ -22,6 +22,6 @@ custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
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engine-create-func-name=NvDsInferYoloCudaEngineGet
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[class-attrs-all]
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nms-iou-threshold=0.45
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nms-iou-threshold=0.7
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pre-cluster-threshold=0.25
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topk=300
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