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 will 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 :
Part 1: Download and prepare the dataset
Part 2: How to Pre-train your custom dataset
Part 3: How to fine-tune your model with a new dataset / categories
Part 4: Test the model
Link for the code : https://ko-fi.com/s/9be1ebf845
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Check out our tutorial here : https://youtu.be/MHXx2HY29uc&list=UULFTiWJJhaH6BviSWKLJUM9sg
#Python #ImageClassification # LightlyTrain