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Hi Everyone in this video I have explained how to train YOLO v4 for custom object detection on google colab utilizing the free GPU resources. This video is very special because it provides complete overview of changing the make file configuration file and creating training and testing dataset feel free to add your custom class and train your own model. I have also explained how to use trained model to detect objects on live video.

1. Add crome extension to download images by below URL
https://bit.ly/3nXfPI8

2. Download rename files jupyter notebook form below link paste in the same folder where you
placed all the images run it all the image files will be renamed

https://github.com/jakkcoder/training...


2.1 Download labelImg tool with below link
https://tzutalin.github.io/labelImg/

3. git link to clone darknet on colab
https://github.com/pjreddie/darknet

4. Get train and test data generator from here
https://github.com/jakkcoder/training...

Note for point 4 : I am not the authors for 2 py files complete credit goes to authors for
creatingfilesdataandname, creatingtrainandtesttxtfiles files.

5. Download pretrained weights for the convolutional layers (154 MB):
http://pjreddie.com/media/files/darkn...

6. command to train the model (take care of single line and spaces)

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

7. Download code to use trained model to detect object on live video
https://github.com/jakkcoder/training...



In this tutorial I’m going to explain you one of the easiest way to train YOLO to detect a custom object even if you’re a beginner and have no experience with coding.

This video cover:
1. Setting up Google Colab as a cloud VM with Free GPU.
2. Commands to get Darknet with YOLOv3 weights installed and running.
3. YOLOv3 pretrained coco model detections in the Cloud.
4. Configuration for Custom YOLOv3 Training in the Cloud.
5. Training Custom YOLOv3 Object Detector in the Cloud.