Models
Faster R-CNN vs. YOLOv3 PyTorch

Faster R-CNN vs. YOLOv3 PyTorch

Both Faster R-CNN and YOLOv3 PyTorch are commonly used in computer vision projects. Below, we compare and contrast Faster R-CNN and YOLOv3 PyTorch.

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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YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.
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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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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7.2k+
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License
MIT
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GPL-3.0
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Training Notebook

Compare Faster R-CNN and YOLOv3 PyTorch with Autodistill

Compare Faster R-CNN vs. YOLOv3 PyTorch

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.