* add lpd_yunet

* add quantization and quantized model

* quantize with inc instead

* update benchmark results

Add MobileNet v1 & v2

* replace with yunet of fixed input shape

* update quantized yunet

* update yunet filename used in scripts

* add a note message for https://github.com/opencv/opencv_zoo/issues/44

* add options for selecting backend & targets

* add eol

* add backend TIMVX & target NPU

* update benchmarking results on Khadas VIM3 NPU

* fix wrong column header

* update readme

* re-order column KV3-NPU

* re-order KV3-NPU specs line

* add additional description regarding TIM-VX backend and NPU target for OpenCV DNN

* add scripts for quantization

* update path to pp-resnet50

* add quantized models

* rename dict to models

* add requirements and readme

* fix typos

* update ONNX opset version of YuNet to 11 for quantization

* fix corruption when face detection results is none

* add (ms) to each hardware header

* add a argument for label path

* correct filenames for face detection

* add a download link for face recognition data

* fix path to face recognition data

* correct shasum for face_detection.zip

* fix filename for person_reid benchmark data package

* add benchmark results of YuNet on D1

* add a link for tutorial of benchmarking on D1-CPU

* improve description

* improve hardware namings

* remove extra parentheses

* workable wrapper and demo (demo without visualization)

* add visualization for demo

* impl benchmark for YoutuReID

* update benchmark results on x86_64, arm and cuda

* add charsets and CRNN_CN

* workable wrapper and demo for CRNN_CN

* update README with CRNN_CN; rename models with EN/CN suffix

* impl benchmarks for CRNN_EN and CRNN_CN

* update benchmark result on arm

* update benchmark results on x86_64 & cuda

Make it easier to see benchmark results

* impl wrapper & demo

* add data for object tracking benchmark

* impl benchmark for DaSiamRPN

* update benchmark results for DaSiamRPN

* impl dataloader factory

* set a type to init all instances for benchmarks

* create metrics for different types of behavior

* workable impl calling utils.METRICS in benchmark

* add qrcode detector and parser from wechat

* add a link to download qrcode data

* add model

* add visualize

* imporve visualize in demo

* benchmark impl

* update benchmark results for wechatqrcode

* update readme

* correct upload time

* add suffix of training dataset, arch & upload time to each model

* update DB-IC15 benchmark results

* update benchmark results on Jetson Nano

* update YuNet and SFace impl with opencv-python api

* add PPHumanSeg impl and demo

* add benchmark impl and results for PPHumanSeg

* add PPResNet impl and demo

* add benchmark impl and results for PPResNet

* SFace and demo impl

* benchmark support and results for SFace

* Improve benchmark configurations:

* Move data downloading from configs to download_data.py. Add an alternative download link.

* Add Data class to operate data loading and indexing.

* Add Metric class to operate benchmark runs.

* Benchmark results are now the median or geometric mean of benchmark
  runs.

Benchmark framework impl; add YuNet for face detection, DB for text detection, CRNN for text recognition

* benchmark framework: benchmarks based on configs

* added impl and benchmark for YuNet (face detection)

* added impl and benchmark for DB (text detection)

* added impl and benchmark for CRNN (text recognition)

* add readme
* add license
* add git-lfs tracking for Caffe, Tensorflow, Torch, Darknet & ONNX model weights.