Models
4M vs. YOLOv3 Keras

4M vs. YOLOv3 Keras

Both 4M and YOLOv3 Keras are commonly used in computer vision projects. Below, we compare and contrast 4M and YOLOv3 Keras.

Models

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4M

The 4M model is a versatile multimodal Transformer model developed by EPFL and Apple, capable of handling a handful of vision and language tasks.
Learn more about 4M
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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.
Learn more about YOLOv3 Keras
Model Type
Multimodal Model
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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
PyTorch
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Keras
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub
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View Repo
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View Repo
GitHub Stars
1.1k
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7.1k+
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License
Apache 2.0
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MIT
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Paper
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View Paper
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View Paper
Training Notebook
Train on Colab
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Train on Colab
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Deploy Model
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Deploy with Roboflow
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Deploy with Roboflow
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Compare 4M and YOLOv3 Keras with Autodistill

Compare 4M vs. YOLOv3 Keras

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.