DeepSeek-VL

Florence-2-large is an advanced vision foundation model developed by Microsoft, capable of handling a wide variety of vision and vision-language tasks, such as captioning, object detection, segmentation, and OCR. Built with a sequence-to-sequence architecture, it uses the FLD-5B dataset containing over 5 billion annotations and 126 million images to master multi-task learning. Florence-2-large excels in both zero-shot and fine-tuned settings, providing high-quality results with minimal training. The model supports tasks including detailed captioning, object detection, and dense region captioning, and can process images with text prompts to generate relevant responses. It offers great flexibility by handling diverse vision-related tasks through prompt-based approaches, making it a competitive tool in AI-powered visual tasks. The model is available on Hugging Face with pre-trained weights, enabling users to quickly get started with image processing and task execution.

Train your own models, get access to pre-trained computer vision models and app templates, learn how to create AI apps or solve a business problem using computer vision in a couple of hours. Start creating your own dataset for detection by adding the images of the object you need to train. You can add up to 5000 images per dataset. After images are added to your dataset, they are pushed automatically into training. Once the model is finished training, you will be notified accordingly. You can simply download your model to be used for detection. You can also integrate your model to our pre-existing app templates for quick coding. Our mobile app which is available on both Android and IOS utilizes the power of computer vision to help people with complete blindness in their day-to-day lives. It is capable of alerting hazardous objects or signs, detecting common objects, recognizing text as well as currencies and understanding basic scenarios through deep learning.