Models
YOLOv3 Keras vs. Resnet-32

YOLOv3 Keras vs. Resnet-32

Both YOLOv3 Keras and ResNet 32 are commonly used in computer vision projects. Below, we compare and contrast YOLOv3 Keras and ResNet 32.

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.
Learn more about YOLOv3 Keras
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ResNet 32

A fast, simple convolutional neural network that gets the job done for many tasks, including classification.
Learn more about ResNet 32
Model Type
Object Detection
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Classification
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Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
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Annotation Format
Instance Segmentation
Instance Segmentation
Framework
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Keras
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Fast.ai v2
GitHub
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View Repo
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View Repo
GitHub Stars
7.1k+
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32+
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License
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 YOLOv3 Keras and ResNet 32 with Autodistill

Compare YOLOv3 Keras vs. Resnet-32

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.