Florence-2 is an advanced vision foundation model that uses a prompt-based approach to handle a wide range of vision and vision-language tasks. Florence-2 can interpret simple text prompts to perform tasks like captioning, object detection, and segmentation. It leverages our FLD-5B dataset, containing 5.4 billion annotations across 126 million images, to master multi-task learning. The model's sequence-to-sequence architecture enables it to excel in both zero-shot and fine-tuned settings, proving to be a competitive vision foundation model.
Clone this repository to 'ComfyUI/custom_nodes` folder.
Install the dependencies in requirements.txt, transformers version 4.38.0 minimum is required:
pip install -r requirements.txt
or if you use portable (run this in ComfyUI_windows_portable -folder):
python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\ComfyUI-Florence2\requirements.txt
Supports most Florence2 models, which can be automatically downloaded with the DownloadAndLoadFlorence2Model to ComfyUI/models/LLM:
Official:
https://huggingface.co/microsoft/Florence-2-base
https://huggingface.co/microsoft/Florence-2-base-ft