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docs.binaexperts.com
  • Introduction
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      • Uploading Video
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  • annotate
    • Annotation Tools
    • Use BinaExperts Annotate
  • Train
    • Train
    • Framework
      • Tensorflow
      • PyTorch
      • NVIDIA TAO
      • TFLite
    • Models
      • YOLO
      • CenterNet
      • EfficientNet
      • Faster R-CNN
      • Single Shot Multibox Detector (SSD)
      • DETR
      • DETECTRON2 FASTER RCNN
      • RETINANET
    • dataset healthcheck
      • Distribution of annotations based on their size relative
      • Distribution of annotations based on their size relative
    • TensorBoard
    • Hyperparameters
    • Advanced Hyperparameter
      • YAML
      • Image Size
      • Validation input image size
      • Patience
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      • Autoanchor
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      • multi scale
      • learning rate
      • Momentum
  • Deployment
    • Deployment
      • Legacy
      • Deployment model (Triton)
    • Introducing the BinaExperts SDK
  • ابزارهای نشانه گذاری
  • استفاده از نشانه گذاری بینااکسپرتز
  • 🎓آموزش مدل
  • آموزش
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  • مدل
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    • افیشنت نت
    • R-CNN سریعتر
    • SSD
    • DETR
    • DETECTRON2 FASTER RCNN
  • تست سلامت دیتاست
    • توزیع اندازه نسبی
    • رسم نمودار توزیع
  • تنسوربرد
  • ابرمقادیر
  • ابرمقادیر پیشرفته
    • YAML (یامل)
    • اندازه تصویر
    • اعتبار سنجی تصاویر ورودی
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  • سازماندهی
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    • کنترل دسترسی مبتنی بر نقش
  • مجموعه داده ها
    • ایجاد یک پروژه
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      • بارگذاری ویدیو
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    • ایجاد یک نسخه از مجموعه داده
    • پیش‌پردازش تصاویر
    • ایجاد تصاویر افزایش یافته
    • افزودن تگ به تصاویر
    • مدیریت کلاس‌ها
  • برچسب گذاری
    • Page 3
  • آموزش
    • Page 4
  • استقرار
    • Page 5
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  1. Train

Framework

PreviousTrainNextTensorflow

Last updated 12 months ago

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PyTorch and TensorFlow are two widely used frameworks in the field of deep learning.

PyTorch, a product of Facebook’s AI Research lab (FAIR), has attracted many researchers and developers with features such as high compatibility with Python, ease of use, and providing advanced capabilities for building neural networks.

TensorFlow, developed by the Google Brain team, is one of the most popular frameworks in the field of machine learning. This framework, with features such as support for distributed computations, a variety of tools for visualization, and the ability to use different hardware such as GPUs and TPUs, has maintained its place among users.

The NVIDIA TAO Toolkit is an open-source software that simplifies and accelerates the creation of customized and enterprise-ready AI models for computer vision applications. .

The Triton Inference Server (formerly known as TensorRT Inference Server or Triton) is a server software that standardizes the deployment and execution of AI models across every workload. .

It uses transfer learning, vision transformers, AutoML, and cloud-native technology to deliver high accuracy and performance on any platform
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The server supports trained AI models from many frameworks, including TensorFlow, TensorRT, PyTorch, and ONNX
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