Models
Faster R-CNN vs. YOLOv5

Faster R-CNN vs. YOLOv5

Both Faster R-CNN and YOLOv5 are commonly used in computer vision projects. Below, we compare and contrast Faster R-CNN and YOLOv5.

Models

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Faster R-CNN

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server.
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YOLOv5

A very fast and easy to use PyTorch model that achieves state of the art (or near state of the art) results.
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
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CNN, YOLO
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Frameworks
TensorFlow 1.5
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
7.5k+
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46k+
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License
MIT
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AGPL-3.0
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Training Notebook

Compare Faster R-CNN and YOLOv5 with Autodistill

Compare Faster R-CNN vs. YOLOv5

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.