Detic: A Detector with image classes that can use image-level labels to easily train detectors.
الميزات الرئيسية لـ facebookresearch/detic هي: رؤية الحاسوب, Object Detection, Transformer.
تشمل البدائل مفتوحة المصدر لـ facebookresearch/detic: hustvl/yolos — [NeurIPS 2021] You Only Look at One Sequence. google/automl — Google Brain AutoML. alexeyab/darknet — Darknet is a high-performance C-based inference engine and computer vision library designed for real-time object… facebookresearch/detectron — Detectron is a PyTorch object detection framework and computer vision research platform. It provides implementations… facebookresearch/detectron2 — Detectron2 is a PyTorch computer vision framework and visual recognition platform designed for training and deploying… openai/clip — CLIP is a neural network architecture designed to map visual and textual data into a shared latent vector space. By…
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
Detectron is a PyTorch object detection framework and computer vision research platform. It provides implementations of neural network architectures for locating and identifying objects in images, including Mask R-CNN for generating instance segmentation masks and RetinaNet for one-stage detection. The platform supports computer vision prototyping and object detection research through the deployment of pre-trained baseline models. This allows for the rapid implementation and evaluation of visual recognition systems. Its capabilities cover image object localization and instance segmentation w
Darknet is a high-performance C-based inference engine and computer vision library designed for real-time object identification and localization. It serves as a neural network framework for training and deploying detection models using the YOLO architecture, providing a toolset for deep learning training and deployment. The project differentiates itself through a C and CUDA implementation that enables hardware acceleration for matrix multiplication and inference speed optimization. It provides a shared library interface for embedding detection capabilities into external applications and suppo
Google Brain AutoML