Models
YOLOv3 PyTorch vs. Faster R-CNN

YOLOv3 PyTorch vs. Faster R-CNN

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

Models

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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.
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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.
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
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Frameworks
PyTorch
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TensorFlow 1.5
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
7.2k+
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7.5k+
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License
GPL-3.0
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MIT
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Training Notebook

Compare YOLOv3 PyTorch and Faster R-CNN with Autodistill

Compare YOLOv3 PyTorch vs. Faster R-CNN

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.