SkalskiP / fashion-assistant
Our idea is to combine the power of computer vision model and LLMs. We use YOLO, CLIP and DINOv2 to extract high-level features from images. We pass the prompt, along with the extracted features, to LLM, allowing for advanced image dataset queries.
☆99Updated last year
Related projects ⓘ
Alternatives and complementary repositories for fashion-assistant
- Use Grounding DINO, Segment Anything, and GPT-4V to label images with segmentation masks for use in training smaller, fine-tuned models.☆65Updated 11 months ago
- ☆27Updated 10 months ago
- EdgeSAM model for use with Autodistill.☆25Updated 4 months ago
- YOLOExplorer : Iterate on your YOLO / CV datasets using SQL, Vector semantic search, and more within seconds☆123Updated this week
- Evaluate the performance of computer vision models and prompts for zero-shot models (Grounding DINO, CLIP, BLIP, DINOv2, ImageBind, model…☆34Updated last year
- Simplify Your Visual Data Ops. Find and visualize issues with your computer vision datasets such as duplicates, anomalies, data leakage, …☆67Updated last year
- Eye exploration☆22Updated last month
- Run zero-shot prediction models on your data☆30Updated 4 months ago
- A curated list of papers that released datasets along with their work☆124Updated 2 weeks ago
- Accurately locating each head's position in the crowd scenes is a crucial task in the field of crowd analysis. However, traditional densi…☆20Updated 7 months ago
- GroundedSAM Base Model plugin for Autodistill☆44Updated 6 months ago
- ☆29Updated last month
- ☆13Updated 11 months ago
- Vehicle speed estimation using YOLOv8☆30Updated 6 months ago
- ☆60Updated last year
- Use Florence 2 to auto-label data for use in training fine-tuned object detection models.☆59Updated 2 months ago
- My journey during 10 weeks of building FiftyOne plugins☆18Updated 11 months ago
- Everything you need to know about Transformers! 🤖☆127Updated last year
- Framework agnostic computer vision inference.☆118Updated this week
- A modular end-to-end tracking framework for research and development☆94Updated last month
- PyTorch at the Edge: Deploying Over 964 TIMM Models on Android with TorchScript and Flutter.☆42Updated last year
- Implementation on Custom Dataset☆59Updated last year
- Use Segment Anything 2, grounded with Florence-2, to auto-label data for use in training vision models.☆89Updated 3 months ago
- DETIC module for use with Autodistill.☆13Updated 11 months ago
- GPT-4V(ision) module for use with Autodistill.☆25Updated 3 months ago
- NVIDIA DeepStream SDK 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 application for YOLO-Pose models☆120Updated 3 months ago
- autoAnnoter its a tool to auto annotate data using a exisiting models☆43Updated 2 months ago
- Official Code for Tracking Any Object Amodally☆113Updated 3 months ago
- The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained mode…☆9Updated 3 months ago
- Pretraining and finetuning for visual instruction following with Mixture of Experts☆9Updated 9 months ago