Best AI Vision Models Tools

Explore 24 AI vision models tools to find the perfect solution.

Vision Models

24 tools

Janus-1.3B

A unified multimodal AI model that decouples visual encoding to support both understanding and generation tasks.

YOLOv10

YOLOv10 is a real-time end-to-end object detection tool that improves upon previous YOLO versions through NMS-free training and a comprehensive architectural design to enhance efficiency and accuracy. It offers state-of-the-art performance across various model sizes and is implemented in PyTorch.

BLIP-2

BLIP-2 is an advanced visual-language model that allows zero-shot image-to-text generation, enabling tasks such as image captioning and visual question answering using a combination of pretrained vision and language models.

DeepSeek-VL2

A series of advanced vision-language models designed for multimodal understanding, available in multiple sizes to suit varying complexity and performance requirements.

YOLOv5

YOLOv5 is a popular open-source AI tool aimed at object detection, image segmentation, and image classification, leveraging PyTorch for model building and deployment. It supports various deployment formats including ONNX, CoreML, and TFLite, and is well-documented for ease of use in research and practical applications.

JanusFlow-1.3B

JanusFlow-1.3B is a unified multimodal model by DeepSeek that integrates autoregressive language models with rectified flow, enabling both multimodal understanding and image generation.

Ultralytics YOLOv8

A state‐of‐the‐art object detection model by Ultralytics that provides robust capabilities for object detection, instance segmentation, and pose estimation. It offers both CLI and Python integrations with extensive documentation and performance metrics.

Ultralytics YOLO11

A suite of computer vision models for object detection, segmentation, pose estimation, and classification, integrated with Ultralytics HUB for visualization and training.

DeepSeek-VL2-small

DeepSeek-VL2-small is a variant of the DeepSeek-VL2 series, advanced mixture-of-experts vision-language models designed for multimodal tasks such as visual question answering, optical character recognition, document/table/chart understanding, and visual grounding.

Janus-Series

An open-source repository from deepseek-ai that offers a suite of unified multimodal models (including Janus, Janus-Pro, and JanusFlow) designed for both understanding and generation tasks. The models decouple visual encoding to improve flexibility and incorporate advanced techniques like rectified flow for enhanced text-to-image generation.

olmOCR-7B-0225-preview

A preview release of AllenAI's olmOCR model, fine-tuned from Qwen2-VL-7B-Instruct using the olmOCR-mix-0225 dataset. It is designed for document OCR and recognition, processing PDF images by extracting text and metadata. The model is intended to be used in conjunction with the olmOCR toolkit for efficient, large-scale document processing.

YOLOv8

A state-of-the-art computer vision model for object detection, segmentation, pose estimation, and classification tasks, designed for speed, accuracy, and ease of use.

Janus-Pro-1B

Janus-Pro-1B is a unified multimodal model by DeepSeek that decouples visual encoding for multimodal understanding and generation. It supports both image input (via SigLIP-L) for understanding and image generation using a unified transformer architecture.

Florence-2-large

An advanced vision foundation model by Microsoft designed for a wide range of vision and vision-language tasks such as captioning, object detection, OCR, and segmentation. It uses a prompt-based, sequence-to-sequence transformer architecture pretrained on the FLD-5B dataset and supports both zero-shot and finetuned settings.

GUI-R1

GUI-R1 is a generalist R1-style vision-language action model designed for GUI agents that leverages reinforcement learning and policy optimization to automatically control and interact with graphical user interfaces across multiple platforms (Windows, Linux, macOS, Android, Web).

YOLOv8

A state-of-the-art object detection, segmentation, and classification model known for its speed, accuracy, and ease of use in computer vision tasks.

UniRig

UniRig is an AI-based unified framework for automatic 3D model rigging. It leverages a GPT-like transformer to predict skeleton hierarchies and per-vertex skinning weights, automating the traditionally time-consuming rigging process for diverse 3D assets including humans, animals, and objects.

VLM-R1

VLM-R1 is a stable and generalizable R1-style large Vision-Language Model designed for visual understanding tasks such as Referring Expression Comprehension (REC) and Out-of-Domain evaluation. The repository provides training scripts, multi-node and multi-image input support, and demonstrates state-of-the-art performance with RL-based fine-tuning approaches.

deepfake-detector-model-v1

A deepfake detection image classification model fine-tuned from google/siglip2-base-patch16-512. It leverages the SiglipForImageClassification architecture to classify images as either 'fake' (deepfakes) or 'real', and is intended for applications such as media authentication, content moderation, forensic analysis, and security.

nanoVLM

A lightweight, fast repository for training and fine-tuning small vision-language models using pure PyTorch.

Kimi-VL-A3B-Thinking

Kimi-VL-A3B-Thinking is an efficient open-source Mixture-of-Experts vision-language model specialized in long-context processing and extended chain-of-thought reasoning. With a 128K context window and only 2.8B activated LLM parameters, it excels in multimodal tasks including image and video comprehension, OCR, mathematical reasoning, and multi-turn agent interactions.

Shap-E

Shap-E is an official GitHub repository by OpenAI for generating 3D implicit functions conditioned on text or images. It provides sample notebooks and usage instructions for converting text prompts or images into 3D models, making it a practical tool for generating 3D objects.

SmolVLM

SmolVLM is a 2B parameter vision-language model that is small, fast, and memory-efficient. It builds on the Idefics3 architecture with modifications such as an improved visual compression strategy and optimized patch processing, making it suitable for local deployment, including on laptops. All model checkpoints, training recipes, and tools are released open-source under the Apache 2.0 license.

DeepSeek-OCR

DeepSeek-OCR is an open-weight, multilingual vision-language OCR model from DeepSeek that converts images/documents to text (e.g., Markdown) using a context-aware optical compression approach. It runs via Transformers and vLLM, supports FlashAttention, and is provided as BF16 safetensors (~3B params) with example inference code and broad community adoption.