Add benchmark results on Toybrick RV1126, Khadas Edge2, Horizon Sunrise X3 PI and MAIX-III AX-PI

* use mean as default for benchmark metric; change result representation;
add --all for benchmarking all configs at a time

* fix comments

* add --model_exclude

* pretty print

* improve benchmark result table header: from band-xpu to xpu-band

* suppress print message

* update benchmark results on CPU-RPI

* add the new benchmark results on the new intel cpu

* fix backend and target setting in benchmark; pre-modify the names of int8 quantized models

* add results on jetson cpu

* add cuda results

* print target and backend when using --all

* add results on Khadas VIM3

* pretty print results

* true pretty print results

* update results in new format

* fix broken backend and target vars

* fix broken backend and target vars

* fix broken backend and target var

* update benchmark results on many devices

* add db results on Ascend-310

* update info on CPU-INTEL

* update usage of the new benchmark script

* limit backend and target combination in demos and benchmark

* simpler version checking

* update benchmark and results

* update lpd_yunet & nanodet benchmark results

* update results for PP-HumanSeg, MobileNet-V2, MP-HandPose

* add some notes

* replace pphumanseg with a simplified one

* update demo default

* update preprocess of handpose estimation to handle some conner cases

* back PALM_BOX_ENLARGE_FACTOR to default

* The results of the two models remain the same accuracy.

* re-upload int8 models

* updated by yiyao

* remove the sim suffix

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Co-authored-by: Nzihaomu <zihaomu@outlook.com>

* add cpp demo for yunet

* add a new line before end of file

* new line before eof

* update handpose model

* update quantize model

* fix quantize path

* update readme of quantization and benchmark result

* fix document

* added evaluation script for PPHumanSeg

* added quantized model, renamed dataset

* minor spacing changes

* moved _all variables outside loop and updated accuracy

* removed printing for class accuracy and IoU

* added 2 transforms

* evaluation done on same size tensor as input size with mIoU 0.9085

* final changes

* added mIoU and reference

* update to the latest palm detection model

* quantize palm detection model

* make palm aligned to center when resize

* update benchmark for palm detection

* update benchmark data

* update readme

* update a new quantized model

* update readme

* update document and fix bugs

* re-quantized model to per_tensor mode

* update KV3-NPU benchmark result

add model path searcher and remove hardwritten file paths from benchmark configs; pack ppresnet, mobilenet & crnn with labels; fix palm det data; add flags to enable models of different precision separately (#123)

Signed-off-by: NHelio Perroni Filho <xperroni@gmail.com>
Signed-off-by: NHelio Perroni Filho <xperroni@gmail.com>

* Fix a bug when there is no object

* Add the minimum version requirement for opencv-python

* re-quantize some models from per_channel mode to per_tensor mode

* remove the description about per_channel

Delete YoloX.py (#111):

- Remove the legacy to save git conflicts