Models
Faster R-CNN vs. YOLOS

Faster R-CNN vs. YOLOS

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

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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YOLOS

YOLOS looks at patches of an image to to form "patch tokens", which are used in place of the traditional wordpiece tokens in NLP.
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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Transformer, 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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812+
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License
MIT
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MIT
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Training Notebook

Compare Faster R-CNN and YOLOS with Autodistill

Compare Faster R-CNN vs. YOLOS

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.