Zero-shot object detection with CLIP, utilizing Faster R-CNN for region proposals.
Welcome! This project enables zero-shot object detection using OpenAI's CLIP model, complemented by the Fast R-CNN model for generating region proposals.
To dive into the magic of CLIP-based object detection, make sure you have the following installed:
CLIP (Contrastive Language–Image Pre-training) is a neural network trained on a massive dataset of 400 million image-text pairs. By learning to predict the correct text for images and vice versa, CLIP effectively bridges the gap between visual and textual understanding. This self-supervised model excels in various image-language tasks, including classification and object detection, without the need for labeled training data.
Original Image:
Candidate Regions:
These are the regions identified by Faster R-CNN from the original image.
Detected Objects:
Here’s what CLIP detected in the image.
Explore the potential of CLIP for zero-shot object detection and see how it performs without needing extensive training data. Happy detecting! 🕵️♂️