Home

Awesome

darknet_scripts - YOLO / YOLOv2 / YOLOv3 / YOLOv4 / YOLOv5 / YOLOv7 / YOLOv8

Auxilary scripts for working with darknet deep learning famework (2017)

  1. How to compute/reproduce YOLOv2 anchors for yolo-voc.cfg?
  2. How to visualize genereted anchors?
  3. Is gen_anchors.py same as YOLOv2 anchor computation?
  4. How to get anchors if My input for network is bigger than 416?
  5. How to plot YOLO loss
  6. YOLO and Anchors tutorial

How to compute/reproduce YOLOv2 anchors for yolo-voc.cfg?

  1. Download The Pascal VOC Data and unpack it to directory build\darknet\x64\data\voc will be created dir build\darknet\x64\data\voc\VOCdevkit\:

    1.1 Download file voc_label.py to dir build\darknet\x64\data\voc: http://pjreddie.com/media/files/voc_label.py

  2. Download and install Python for Windows: https://www.python.org/ftp/python/2.7.9/python-2.7.9rc1.amd64.msi

  3. Run command: python build\darknet\x64\data\voc\voc_label.py (to generate files: 2007_test.txt, 2007_train.txt, 2007_val.txt, 2012_train.txt, 2012_val.txt)

  4. Run command: type 2007_train.txt 2007_val.txt 2012_*.txt > train.txt

  5. Obtain anchors5.txt in generated_anchors/voc-reproduce folder by executing:

python gen_anchors.py -filelist //path//to//voc//filelist/list//train.txt -output_dir generated_anchors/voc-reproduce -num_clusters 5

How to visualize genereted anchors?

After completing the steps above, execute <br />

python visualize_anchors.py -anchor_dir generated_anchors/voc-reproduce 
<br /> Inside the generated_anchors/voc-reproduce directory you will have png visualization of the anchors <br />

Is gen_anchors.py same as YOLOv2 anchor computation?

<h4> Yes, almost. Look at the two visualaziations below:</h4> <br /> <ul> <li> yolo-voc.cfg anchors are provided by the original author <img src= 'https://github.com/Jumabek/darknet_scripts/blob/master/generated_anchors/voc-original/yolo-voc.png' /> </li> <br /> <li> yolo-voc-reproduce.cfg anchors computed by gen_anchors.py <img src= 'https://github.com/Jumabek/darknet_scripts/blob/master/generated_anchors/voc-anchors-reproduce/anchors5.png' /> </li> <br /> </ul>

How to get anchors if My input for network is bigger than 416?

Simply change the lines here https://github.com/Jumabek/darknet_scripts/blob/master/gen_anchors.py#L17 to your input dimension. Then compute the anchors.

How to plot YOLO loss?

In order to plot a loss, you first need a log of the <i>darknet train</i> command For example,below command will save the log into log/aggregate-voc-tiny7.log <br /><br />

darknet.exe detector train data/aggregate-voc-tiny7.data cfg/aggregate-voc-tiny7.cfg  backup/aggregate-voc-tiny7/aggregate-voc-tiny7_21000.weights >> log/aggregate-voc-tiny7.log -gpus 0,1

Once you have \path\to\log\aggregate-voc-tiny7.log, plot the loss by executing

python plot_yolo_log.py \\path\\to\\log\\aggregate-voc-tiny7.log