Models
PaliGemma-2 vs. YOLOv3 Keras

PaliGemma-2 vs. YOLOv3 Keras

Both PaliGemma-2 and YOLOv3 Keras are commonly used in computer vision projects. Below, we compare and contrast PaliGemma-2 and YOLOv3 Keras.

Models

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PaliGemma-2

PaliGemma-2 is a multimodal model developed by Google.
Learn more about PaliGemma-2
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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
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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
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7.1k+
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License
Gemma License
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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 PaliGemma-2 and YOLOv3 Keras with Autodistill

Compare PaliGemma-2 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.