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:

image segmentation

model	source	demo	note
Deeplab V3	link	src

./deeplab deeplab.mnn image1.jpg

Output:

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.