Tutorials Yolo_Object_Detection for custom data:

Method 1: Use LabelImg -> export file txt

Method 2: Use https://www.makesense.ai/

Note: id classes as number object.

!git clone 'https://github.com/AlexeyAB/darknet.git' 'PATH_to_darknet'

!git clone 'https://github.com/AlexeyAB/darknet.git' '/content/drive/MyDrive/yolov3_v1/darknet'

!make

creating-files-data-and-name.py

creating-train-and-test-txt-files.py

Then Upload file darknet53.conv.74 inside custom_weight

!python3 /content/drive/MyDrive/yolov3_v1/images/creating-files-data-and-name.py

!python3 /content/drive/MyDrive/yolov3_v1/images/creating-train-and-test-txt-files.py

GPU=1

CUDNN=1

OPENCV=1

Then save, upload darknet

Line 6, 7: delete #

Line 20: Max_batch = number class * 2000

Line 22: Step = 90%, 110% max_batch

Find [yolo]: edit: classes, filters

Save name: yolov3_custom.cfg then upload cfg.

!darknet/darknet detector train images/labelled_data.data darknet/cfg/yolov3_custom.cfg custom_weight/darknet53.conv.74 -dont_show