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deep-deploy's Introduction

deploy deep learning model with MNN.

build

  1. install opencv;

  2. build MNN

  3. build this project

    mkdir build;cd build
cmake -DMNN="your MNN path" ..
make

use

image classification

model source demo note
MobileNet V1/V2/V3 link src
EfficientNet link src AdvProp use different preprocess
RepVGG link src 
./mobilenet mobilenet_v2.mnn cat.jpg

Output:

class: 282 prob: 0.537347
class: 283 prob: 0.14923
class: 286 prob: 0.127461
class: 288 prob: 0.0312308
class: 284 prob: 0.0156367

object detection

model source demo note
Yolo V3 link src pass in lastest version
Yolo V3 link src decode box by hard code 
./yolov3 yolov3.mnn image2.jpg

Output:

detection

image segmentation

model source demo note
Deeplab V3 link src 
./deeplab deeplab.mnn image1.jpg

Output:

segmentation

cartoonize/style transfer/paint

model source demo note
White Box Cartoonize link src 
./white-box-cartoonize cartoonize.mnn food16.jpg

super resolution

model source demo note
DBPN link src 
./dbpn dbpn_x2.mnn butterfly_x2.jpg

tools

  1. frozen_graph.py: to fix input shape or make partition.

deep-deploy's People

Contributors

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Stargazers

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Forkers

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