From 8bef544bae2e7f7d935abe0f7c986a78fd99218c Mon Sep 17 00:00:00 2001 From: Micaela Verucchi Date: Thu, 6 Aug 2020 11:05:26 +0200 Subject: [PATCH] Update README.md --- README.md | 16 +++++++++++++++- 1 file changed, 15 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index d9b5755..ea55785 100644 --- a/README.md +++ b/README.md @@ -14,7 +14,7 @@ M. Verucchi, G. Brilli, D. Sapienza, M. Verasani, M. Arena, F. Gatti, A. Capoton "A Systematic Assessment of Embedded Neural Networks for Object Detection", in IEEE International Conference on Emerging Technologies and Factory Automation (2020) ``` -## Results +## FPS Results Inference FPS of yolov4 with tkDNN, average of 1200 images with the same dimesion as the input size, on * RTX 2080Ti (CUDA 10.2, TensorRT 7.0.0, Cudnn 7.6.5); * Xavier AGX, Jetpack 4.3 (CUDA 10.0, CUDNN 7.6.3, tensorrt 6.0.1 ); @@ -40,6 +40,20 @@ Inference FPS of yolov4 with tkDNN, average of 1200 images with the same dimesio | Nano | yolo4 512 | 2,32 | 2,34 | 3,02 | 3,04 | - | - | | Nano | yolo4 608 | 1,40 | 1,41 | 1,92 | 1,93 | - | - | +## MAP Results +Results for COCO val 2017 (5k images), on RTX 2080Ti, with conf threshold=0.001 + +| | CodaLab | CodaLab | CodaLab | CodaLab | tkDNN map | tkDNN map | +| -------------------- | :-----------: | :-------: | :-----------: | :---------: | :-----------: | :-------: | +| | **tkDNN** | **tkDNN** | **darknet** | **darknet** | **tkDNN** | **tkDNN** | +| | MAP(0.5:0.95) | AP50 | MAP(0.5:0.95) | AP50 | MAP(0.5:0.95) | AP50 | +| Yolov3 (416x416) | 0.381 | 0.675 | 0.380 | 0.675 | 0.372 | 0.663 | +| yolov4 (416x416) | 0.468 | 0.705 | 0.471 | 0.710 | 0.459 | 0.695 | +| yolov3tiny (416x416) | 0.096 | 0.202 | 0.096 | 0.201 | 0.093 | 0.198 | +| yolov4tiny (416x416) | 0.202 | 0.400 | 0.201 | 0.400 | 0.197 | 0.395 | +| Cnet-dla34 (512x512) | 0.366 | 0.543 | \- | \- | 0.361 | 0.535 | +| mv2SSD (512x512) | 0.226 | 0.381 | \- | \- | 0.223 | 0.378 | + ## Index - [tkDNN](#tkdnn) - [Index](#index)