Models
Faster R-CNN vs. Scaled-YOLOv4

Faster R-CNN vs. Scaled-YOLOv4

Both Faster R-CNN and Scaled YOLOv4 are commonly used in computer vision projects. Below, we compare and contrast Faster R-CNN and Scaled YOLOv4.

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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Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.
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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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 Scaled YOLOv4 with Autodistill

Compare Faster R-CNN vs. Scaled-YOLOv4

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.