Try the Model

Use the widget below to experiment with ResNet-50. You can detect COCO classes such as people, vehicles, animals, household items.

Overview

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ResNet-50 is a popular deep-learning image classification model. Version 1.5 of the Residual Neural Networks family of models, ResNet-50 is a 50-layer convolutional neural network (CNN). Released in 2015, it has remained a notable, powerful option for image classification models, well into a decade after its release.

ResNet-50 has high adaptability, making it the perfect model for transfer learning. In fact, recent models years after ResNet-50 such as Mask R-CNN used ResNet-50 as its backbone architecture.

Deploy Resnet-50 using Roboflow here.

Overall, ResNet-50’s unique combination of residual learning, deep yet manageable architecture, and wide adoption makes it a standout model in the field of deep learning and computer vision.

ResNet-50 License

ResNet-50

is licensed under a

BSD 3

license.

Performance

Deploy a ResNet-50 API

You can use Roboflow Inference to deploy a

ResNet-50

API on your hardware. You can deploy the model on CPU (i.e. Raspberry Pi, AI PCs) and GPU devices (i.e. NVIDIA Jetson, NVIDIA T4).

Below are instructions on how to deploy your own model API.

Label Data Automatically with ResNet-50

You can automatically label a dataset using ResNet-50 with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use ResNet-50 to train a computer vision model.

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