This is an example source of related image detection using faiss.
Faiss is an efficient and high-performance library for similarity search and clustering tasks in large datasets. It is commonly used for tasks such as nearest neighbor search and similarity-based retrieval. The name "Faiss" stands for "Facebook AI Similarity Search."
Meta Git : https://github.com/facebookresearch/faiss
This code trains a custom MobileNetV2 model for image classification, saving the trained model's weights and extracting feature vectors from the model for future use.
This code extracts image embeddings using a MobileNetV2 model, builds a Faiss index for image retrieval, and demonstrates two examples:
- Searching for similar images to a specific image from the dataset
- Searching for similar images to a new input image.
python -m venv venv
.\venv\Scripts\activate
pip install faiss-cpu
pip3 install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio===0.12.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html
pip install -r requirements.txt
