maryjul1211 / opencv_zoo

Model Zoo For OpenCV DNN and Benchmarks.

OpenCV Zoo and Benchmark

A zoo for models tuned for OpenCV DNN with benchmarks on different platforms.

Guidelines:

• Clone this repo to download all models and demo scripts:

  # Install git-lfs from https://git-lfs.github.com/
  git clone https://github.com/opencv/opencv_zoo && cd opencv_zoo
  git lfs install
  git lfs pull

• To run benchmarks on your hardware settings, please refer to benchmark/README.

Models & Benchmark Results

Model	Input Size	INTEL-CPU (ms)	RPI-CPU (ms)	JETSON-GPU (ms)	KV3-NPU (ms)	D1-CPU (ms)
YuNet	160x120	1.45	6.22	12.18	4.04	86.69
SFace	112x112	8.65	99.20	24.88	46.25	---
DB-IC15	640x480	142.91	2835.91	208.41	---	---
DB-TD500	640x480	142.91	2841.71	210.51	---	---
CRNN-EN	100x32	50.21	234.32	196.15	125.30	---
CRNN-CN	100x32	73.52	322.16	239.76	166.79	---
PP-ResNet	224x224	56.05	602.58	98.64	75.45	---
MobileNet-V1	224x224	9.04	92.25	33.18	145.66 (per-channel)	---
MobileNet-V2	224x224	8.86	74.03	31.92	146.31 (per-channel)	---
PP-HumanSeg	192x192	19.92	105.32	67.97	74.77	---
WeChatQRCode	100x100	7.04	37.68	---	---	---
DaSiamRPN	1280x720	36.15	705.48	76.82	---	---
YoutuReID	128x256	35.81	521.98	90.07	44.61	---

Hardware Setup:

• INTEL-CPU: Intel Core i7-5930K @ 3.50GHz, 6 cores, 12 threads.
• RPI-CPU: Raspberry Pi 4B, Broadcom BCM2711, Quad core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5GHz.
• JETSON-GPU: NVIDIA Jetson Nano B01, 128-core NVIDIA Maxwell GPU.
• KV3-NPU: Khadas VIM3, 5TOPS Performance. Benchmarks are done using quantized models. You will need to compile OpenCV with TIM-VX following this guide to run benchmarks. The test results use the per-tensor quantization model by default.
• D1-CPU: Allwinner D1, Xuantie C906 CPU (RISC-V, RVV 0.7.1) @ 1.0GHz, 1 core. YuNet is supported for now. Visit here for more details.

Important Notes:

• The data under each column of hardware setups on the above table represents the elapsed time of an inference (preprocess, forward and postprocess).
• The time data is the median of 10 runs after some warmup runs. Different metrics may be applied to some specific models.
• Batch size is 1 for all benchmark results.
• --- represents the model is not availble to run on the device.
• View benchmark/config for more details on benchmarking different models.

License

OpenCV Zoo is licensed under the Apache 2.0 license. Please refer to licenses of different models.