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ArtyZe
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Description

image (semantic segmentation) instance segmentation by darknet or yolo

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yolo_segmentation

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The code is to get segmentation image by darknet

In the process of my project, I have referenced nithi89/unet_darknet in some points and nithilan has give me many important

advices, thanks to him, and if you have interest you can visit his homepage.

This is my third version, I added dilation convolutional, and now it has not so perfect result, but i think it's good enough for me.

I will continue to update afterwards, please stay tuned.

[The Commond to Run My Project]

Compile:

make -j8

Train:

./darknet segmenter train cfg/maskyolo.data cfg/instance_segment.cfg [pretrain weights file I gave to you] 

Test:

./darknet segmenter test cfg/maskyolo.data cfg/instance_segment.cfg [weights file] [image path]

Merge two images:

python Merge.py

And you will get the mask image named final.png

Test image: Merge them together image:

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Output image:(for orig)

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Merge them together image:(not so good, 1. more epochs; 2. deeper or more complex backbone)

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[Pretrain weights file and cfg file]

  1. https://www.dropbox.com/sh/9wrevnyzwfv8hg7/AAA1MJElri9aROsjaPTxO5KCa?dl=0
  2. https://pan.baidu.com/s/15gcrXGzb-fY2vGdl4KlLqg password: bk01

[How to Train with Your Own Dataset ?]

The Way is so easy, you only need three files:

original colorful image;  

label image(pixel value is 0, 1, 2, 3 if you have 3 classes + background);

train.list.

For example with cityscape dataset:

Colorful Original Image:

Image text

Lable Image:

I only have one class so the label image, as 0 is background and others are multi classes. If you have 2 classes, the label image pixel value should be 012 and so on:

Image text

Steps to train you own dataset:

  1. prepare train images and label images like above images  

I have added below function call in my code according to my pictures, you have to change it according to your image name  

#######################################################
find_replace(labelpath, "_leftImg8bit.png", "_gtFine_labelIds.png", labelpath); 
#######################################################
  1. put label images and original images together

  2. generate the train.list file just like:

    /home/user/Desktop/YOLO_train/leftImg8bit/train/aachen_resize/jena_000012_000019_leftImg8bit.png

  3. start train

    ./darknet segmenter train [data_file path] cfg/segment.cfg [pretrain weights file I gave to you]

If you want to see my Result Video, I have put it in: https://pan.baidu.com/s/1uJwFYLHEQ9DGFZ8RkGuagg, and the password is: ic3q

If you want to get how to change the code, see https://github.com/ArtyZe/yolosegmentation/blob/master/TrainDetails.md

What I did to change Yolo for image segmentation, I have written a blog in: https://blog.csdn.net/Artyze/article/details/82721147

After I will do some work in semantic segmentation with yolo.

If you want to do something with Yolo with me, contact me with E-mail: [email protected]

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