streamline the fine-tuning process for multimodal models: PaliGemma, Florence-2, and Qwen2-VL
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Updated
Oct 1, 2024 - Python
streamline the fine-tuning process for multimodal models: PaliGemma, Florence-2, and Qwen2-VL
Tag manager and captioner for image datasets
Use Segment Anything 2, grounded with Florence-2, to auto-label data for use in training vision models.
VLM driven tool that processes surveillance videos, extracts frames, and generates insightful annotations using a fine-tuned Florence-2 Vision-Language Model. Includes a Gradio-based interface for querying and analyzing video footage.
Use Florence 2 to auto-label data for use in training fine-tuned object detection models.
Rem-WM, a powerful watermark remover tool that leverages the capabilities of Microsoft Florence and Lama Cleaner models.
Florence-2 is a novel vision foundation model with a unified, prompt-based representation for a variety of computer vision and vision-language tasks.
Run SOTA Vision-Language Model Florence-2 on your data!
Simple Video Summarization using Text-to-Segment Anything (Florence2 + SAM2) This project provides a video processing tool that utilizes advanced AI models, specifically Florence2 and SAM2, to detect and segment specific objects or activities in a video based on textual descriptions.
AI-Powered Watermark Remover using Florence-2 and LaMA Models: A Python application leveraging state-of-the-art deep learning models to effectively remove watermarks from images with a user-friendly PyQt6 interface.
vision language models finetuning notebooks & use cases (paligemma - florence .....)
The Ultimate Local LLM Discord Bot!!!
Microsoft の軽量VLMのFlorence-2のColaboratory上でのサンプル
TextSnap: Demo for Florence 2 model used in OCR tasks to extract and visualize text from images.
Image captioning GUI using Florence-2.
Various image processing scripts.
ecko-cli is a simple CLI tool that streamlines the process of processing images in a directory, generating captions, and saving them as text files. Additionally, it provides functionalities to create a JSONL file from images in the directory you specify. Images will be captioned using the Microsoft Florence-2-large model and ONNX
Florence-2 quick test
This project implements an advanced generative AI pipeline for extracting and rating features from images. It combines the power of Florence-2, a state-of-the-art vision-language model, with a fine-tuned version of Mistral-v3, a cutting-edge large language model.
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