$2.00
Link for the tutorial : https://youtu.be/MHXx2HY29uc
Link for the full post : https://eranfeit.net/self-supervised-learning-made-easy-with-lightlytrain-image-classification-tutorial/
In this tutorial, we will show you how to use LightlyTrain to train
a model on your own dataset for image classification.
Self-Supervised Learning (SSL) is reshaping computer vision, just like LLMs reshaped text. The newly launched LightlyTrain framework empowers AI teams—no PhD required—to easily train robust, unbiased foundation models on their own datasets. Let’s dive into how SSL with LightlyTrain beats traditional methods
Imagine training better computer vision models—without labeling a single image.
That’s exactly what LightlyTrain offers.
It brings self-supervised pretraining to your real-world pipelines,
using your unlabeled image or video data to kickstart model training.
We’ll walk through how to load the model, modify it for your dataset, preprocess the images, load the trained weights, and run predictions—including drawing labels on the image using OpenCV.
LightlyTrain page: https://www.lightly.ai/lightlytrain?utm_source=youtube&utm_medium=description&utm_campaign=eran
LightlyTrain Github : https://github.com/lightly-ai/lightly-train
LightlyTrain Docs: https://docs.lightly.ai/train/stable/index.html
Lightly Discord: https://discord.gg/xvNJW94
🔥 What You’ll Learn:
✅ Download and prepare the dataset
✅ How to Pre-train your custom dataset
✅ How to fine-tune your model with a new dataset / categories
✅ Test the model