Models
YOLOv3 Keras vs. YOLOv4 PyTorch

YOLOv3 Keras vs. YOLOv4 PyTorch

Both YOLOv3 Keras and YOLOv4 PyTorch are commonly used in computer vision projects. Below, we compare and contrast YOLOv3 Keras and YOLOv4 PyTorch.

Models

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YOLOv3 Keras

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. Keras implementation.
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YOLOv4 PyTorch

YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in PyTorch.
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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YOLO
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Frameworks
Keras
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
7.1k+
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4.4k+
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License
MIT
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Apache-2.0
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Training Notebook

Compare YOLOv3 Keras and YOLOv4 PyTorch with Autodistill

Compare YOLOv3 Keras vs. YOLOv4 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.