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fengyuentau merged 7 commits into from
Jan 10, 2022
Merged

Add hardware: Khadas VIM3 & update benchmarks #39

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b129575
add backend TIMVX & target NPU
fengyuentau Jan 9, 2022
2a1e44c
update benchmarking results on Khadas VIM3 NPU
fengyuentau Jan 9, 2022
35e93f2
fix wrong column header
fengyuentau Jan 9, 2022
ce0f0df
update readme
fengyuentau Jan 9, 2022
801dda1
re-order column KV3-NPU
fengyuentau Jan 10, 2022
8469ec4
re-order KV3-NPU specs line
fengyuentau Jan 10, 2022
61f2c69
add additional description regarding TIM-VX backend and NPU target fo…
fengyuentau Jan 10, 2022
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27 changes: 14 additions & 13 deletions README.md
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Expand Up @@ -14,24 +14,25 @@ Guidelines:

## Models & Benchmark Results

| Model | Input Size | INTEL-CPU (ms) | RPI-CPU (ms) | JETSON-GPU (ms) | D1-CPU (ms) |
|-------|------------|-----------|---------|------------|--------|
| [YuNet](./models/face_detection_yunet) | 160x120 | 1.45 | 6.22 | 12.18 | 86.69 |
| [SFace](./models/face_recognition_sface) | 112x112 | 8.65 | 99.20 | 24.88 | --- |
| [DB-IC15](./models/text_detection_db) | 640x480 | 142.91 | 2835.91 | 208.41 | --- |
| [DB-TD500](./models/text_detection_db) | 640x480 | 142.91 | 2841.71 | 210.51 | --- |
| [CRNN-EN](./models/text_recognition_crnn) | 100x32 | 50.21 | 234.32 | 196.15 | --- |
| [CRNN-CN](./models/text_recognition_crnn) | 100x32 | 73.52 | 322.16 | 239.76 | --- |
| [PP-ResNet](./models/image_classification_ppresnet) | 224x224 | 56.05 | 602.58 | 98.64 | --- |
| [PP-HumanSeg](./models/human_segmentation_pphumanseg) | 192x192 | 19.92 | 105.32 | 67.97 | --- |
| [WeChatQRCode](./models/qrcode_wechatqrcode) | 100x100 | 7.04 | 37.68 | --- | --- |
| [DaSiamRPN](./models/object_tracking_dasiamrpn) | 1280x720 | 36.15 | 705.48 | 76.82 | --- |
| [YoutuReID](./models/person_reid_youtureid) | 128x256 | 35.81 | 521.98 | 90.07 | --- |
| Model | Input Size | INTEL-CPU (ms) | RPI-CPU (ms) | JETSON-GPU (ms) | KV3-NPU (ms) | D1-CPU (ms) |
|-------|------------|----------------|--------------|-----------------|--------------|-------------|
| [YuNet](./models/face_detection_yunet) | 160x120 | 1.45 | 6.22 | 12.18 | 4.04 | 86.69 |
| [SFace](./models/face_recognition_sface) | 112x112 | 8.65 | 99.20 | 24.88 | 46.25 | --- |
| [DB-IC15](./models/text_detection_db) | 640x480 | 142.91 | 2835.91 | 208.41 | --- | --- |
| [DB-TD500](./models/text_detection_db) | 640x480 | 142.91 | 2841.71 | 210.51 | --- | --- |
| [CRNN-EN](./models/text_recognition_crnn) | 100x32 | 50.21 | 234.32 | 196.15 | 125.30 | --- |
| [CRNN-CN](./models/text_recognition_crnn) | 100x32 | 73.52 | 322.16 | 239.76 | 166.79 | --- |
| [PP-ResNet](./models/image_classification_ppresnet) | 224x224 | 56.05 | 602.58 | 98.64 | 75.45 | --- |
| [PP-HumanSeg](./models/human_segmentation_pphumanseg) | 192x192 | 19.92 | 105.32 | 67.97 | 74.77 | --- |
| [WeChatQRCode](./models/qrcode_wechatqrcode) | 100x100 | 7.04 | 37.68 | --- | --- | --- |
| [DaSiamRPN](./models/object_tracking_dasiamrpn) | 1280x720 | 36.15 | 705.48 | 76.82 | --- | --- |
| [YoutuReID](./models/person_reid_youtureid) | 128x256 | 35.81 | 521.98 | 90.07 | 44.61 | --- |

Hardware Setup:
- `INTEL-CPU`: [Intel Core i7-5930K](https://www.intel.com/content/www/us/en/products/sku/82931/intel-core-i75930k-processor-15m-cache-up-to-3-70-ghz/specifications.html) @ 3.50GHz, 6 cores, 12 threads.
- `RPI-CPU`: [Raspberry Pi 4B](https://www.raspberrypi.com/products/raspberry-pi-4-model-b/specifications/), Broadcom BCM2711, Quad core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5GHz.
- `JETSON-GPU`: [NVIDIA Jetson Nano B01](https://developer.nvidia.com/embedded/jetson-nano-developer-kit), 128-core NVIDIA Maxwell GPU.
- `KV3-NPU`: [Khadas VIM3](https://www.khadas.com/vim3), 5TOPS Performance. Benchmarks are done using **quantized** models. [TIM-VX backend and NPU target support for OpenCV](https://github.com/opencv/opencv/pull/21036) is under reivew. You will need to compile OpenCV with TIM-VX following [this guide](https://gist.github.com/zihaomu/f040be4901d92e423f227c10dfa37650) to run benchmarks.
- `D1-CPU`: [Allwinner D1](https://d1.docs.aw-ol.com/en), [Xuantie C906 CPU](https://www.t-head.cn/product/C906?spm=a2ouz.12986968.0.0.7bfc1384auGNPZ) (RISC-V, RVV 0.7.1) @ 1.0GHz, 1 core. YuNet is supported for now. Visit [here](https://github.com/fengyuentau/opencv_zoo_cpp) for more details.

***Important Notes***:
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9 changes: 5 additions & 4 deletions benchmark/benchmark.py
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Expand Up @@ -5,7 +5,6 @@
import numpy as np
import cv2 as cv

# from ..models import MODELS
from models import MODELS
from utils import METRICS, DATALOADERS

Expand Down Expand Up @@ -61,7 +60,8 @@ def __init__(self, **kwargs):
# inference_engine=cv.dnn.DNN_BACKEND_INFERENCE_ENGINE,
opencv=cv.dnn.DNN_BACKEND_OPENCV,
# vkcom=cv.dnn.DNN_BACKEND_VKCOM,
cuda=cv.dnn.DNN_BACKEND_CUDA
cuda=cv.dnn.DNN_BACKEND_CUDA,
timvx=cv.dnn.DNN_BACKEND_TIMVX
)
self._backend = available_backends[backend_id]

Expand All @@ -75,7 +75,8 @@ def __init__(self, **kwargs):
# fpga=cv.dnn.DNN_TARGET_FPGA,
cuda=cv.dnn.DNN_TARGET_CUDA,
cuda_fp16=cv.dnn.DNN_TARGET_CUDA_FP16,
# hddl=cv.dnn.DNN_TARGET_HDDL
# hddl=cv.dnn.DNN_TARGET_HDDL,
npu=cv.dnn.DNN_TARGET_NPU
)
self._target = available_targets[target_id]

Expand Down Expand Up @@ -120,4 +121,4 @@ def printResults(self):
# Run benchmarking
print('Benchmarking {}:'.format(model.name))
benchmark.run(model)
benchmark.printResults()
benchmark.printResults()
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