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Industry-strength Computer Vision workflows with Keras
Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision operations as differentiable tensors to enable integration into deep learning pipelines and supports the transpilation of operations across PyTorch, TensorFlow, JAX, and NumPy. The project provides specialized toolsets for geometric vision and stereo depth, including algorithms for 3D scene reconstruction, camera calibration, and pose estimation. It further distinguishes itself as a differentiable image augmentation framework, applying random geometric and color transformations w
Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying models for object detection, image segmentation, and visual recognition. It provides a research-oriented environment for training complex vision models with multi-GPU acceleration. The project includes a specialized object detection library for identifying and locating multiple objects via bounding boxes, as well as an image segmentation toolkit for creating pixel-level masks through instance, semantic, and panoptic segmentation. Additionally, it features a human pose estimati
CLIP is a neural network architecture designed to map visual and textual data into a shared latent vector space. By utilizing transformer-based feature extraction and multi-modal tokenization, the system aligns images and natural language strings, enabling cross-modal similarity analysis and semantic classification. The project functions as a zero-shot classification engine, identifying image content by calculating the cosine similarity between visual features and arbitrary text labels without requiring task-specific retraining. Beyond inference, it serves as a research toolkit for evaluating
All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
The main features of lightly-ai/lightly-train are: Computer Vision, Computer Vision Frameworks.
Open-source alternatives to lightly-ai/lightly-train include: kornia/kornia — Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision… roboflow/supervision — Supervision is a computer vision toolset for normalizing model outputs, managing datasets, and visualizing… facebookresearch/detectron2 — Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying… keras-team/keras-cv — Industry-strength Computer Vision workflows with Keras. openai/clip — CLIP is a neural network architecture designed to map visual and textual data into a shared latent vector space. By… salesforce/lavis — LAVIS is a multimodal large language model framework and vision-language model library. It provides tools for training…