How to Train YOLO v4 Tiny (Darknet) on a Custom Dataset

YOLOv4-tiny is smaller version of YOLO v4 that emphasizes speed in model predictions, which is perfect for limited compute environments (even CPUs) like mobile phones or embedded machine learning.

This YOLO v4 tiny tutorial breaks down what YOLOv4-tiny is, preparing labeled bounding box data for object detection, training a YOLO v4 tiny Darknet model with free resources on Google Colab on your own dataset, and using that model to perform inference. In this example, we train our example model on infrared thermal images.

Tools:

Create Labeled Data

[__________________________]

I love how you explain and your talking style is very fine love this

[ArunMPEdison]

Great video! Thank you for sharing, curiously watching for which tools you have used for custom training from scratch.

[noorfaleh]

How can download the complete file with weights and cfg file after training it on google colab to use on GPU kit ?

[marcialzipaganjr.]

@Roboflow how should I generate a tflite version of the model I just trained? Also, if I wanted to improve the model again what should I input with the config file? Example the model is initially trained on 2 classes and after sometime I wanted to try it out with 4 more new classes? Should I input 4 on the number of classes or 6?

[Iamanandraj]

can you tell me which software you are using for screen recording and virtual webcam.

[brili]

I finished these steps. So, how to transplant the training model in colab to jetson nano platform?

[CoxopopYance]

Do you have a .py to use that custom pre trained dataset in my desktop??? I want it to use with my video camera

[shahrinnakkhatra]

what if i want to do augmentation for specific classes only? ( I want to use SMOTE to balance my dataset)

[nikhilshashidhar]

Can I use YOLOv4-Tiny generated weights and use those weights on a scaled v4 algorithm?

[asdg]

I know its already been mentioned below. But if you get this error: CUDA Error: no kernel image is available for execution on the device CUDA Error: no kernel image is available for execution on the device: File exists darknet: ./src/utils.c:325: error: Assertion `0' failed.

you can try to change the -gencode arch and code. What I didn't realise was that one line above that comment the guy who wrote the program put this:

# compute_30, sm_30 for Tesla K80
# compute_75, sm_75 for Tesla T4

so yeah it was a bit embarrassing that i didn't see that. Hope this helps you

[avirupdey]

At 20:15 you have got a CUDA error, exactly same as mine. Surprisingly, you just ignored that and headed to another notebook. How to fix that error? Pls reply.

[hessaaleissa]

At “set up training file directions for custom dataset” there is error “No such file or directory ‘/content/darknet/‘/content” how can i fix that error?

[sureshkumar]

How to plot the learning graph for this Project?

[syedmuslim]

hey can you help me out i am stuck in your video in custom training config for yolo v4 the cfg file have you written it or have copied it from somewhere it'll a great help if you respond to make question!! waiting for your reply.. the timing around 19:20

[akashanil]

can we use inference on an vid by replacing img path with a video path

[anime_on_data]

how can we try to run on video. what command we should give for it?

[eswar]

Now there is no Darknet executable file. what can I do? from where can I get that file?

[preeyank]

I am getting cuda error everytime during training if I get K80 or T4 gpu. Can anyone help?

[malikbilal]

If its possible to test Yolov4-Tiny Object detection Model on Arduino Nano .

[Huds-uxxb]

Hey i cant use yolov4 with darknet, can you give me any tutorial