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In this notebook, we want to recognize the objects in the image using pre-trained models. The used models are fasterRCNN, RetinaNet, SSD and FCOS. The code is programmed in Python language and uses PyTorch and TorchVision library.

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Amir-Hofo/object_detection_with_pre_trained_models

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description

In this notebook, we want to recognize the objects in the image using pre-trained models. We are not going to fine-tune the data training models or make any changes in their structure. The used models are fasterRCNN, RetinaNet, SSD and FCOS. You can give any other image to the 'object_detection' function to perform object detection using these models. The code is programmed in Python language and uses PyTorch and TorchVision library.

Presentation1

object-detection

Object detection is a computer vision technique that works to identify and locate objects within an image or video. Specifically, object detection draws bounding boxes around these detected objects, which allow us to locate where said objects are in (or how they move through) a given scene. [fritz.ai]

packages version

python: 3.9.18

torch: 2.1.0

torchvision: 0.16.0

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In this notebook, we want to recognize the objects in the image using pre-trained models. The used models are fasterRCNN, RetinaNet, SSD and FCOS. The code is programmed in Python language and uses PyTorch and TorchVision library.

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