Models
YOLOv4 Tiny vs. MobileNet V2 Classification

YOLOv4 Tiny vs. MobileNet V2 Classification

Both YOLOv4 Tiny and MobileNet V2 Classification are commonly used in computer vision projects. Below, we compare and contrast YOLOv4 Tiny and MobileNet V2 Classification.

Models

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YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset
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MobileNet V2 Classification

MobileNet is a GoogleAI model well-suited for on-device, real-time classification (distinct from MobileNetSSD, Single Shot Detector). This implementation leverages transfer learning from ImageNet to your dataset.
Model Type
Object Detection
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Classification
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Model Features
Item 1 Info
Item 2 Info
Architecture
ResNet-D, YOLO
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Frameworks
Darknet
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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License
YOLO
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Training Notebook

Compare YOLOv4 Tiny and MobileNet V2 Classification with Autodistill

Compare YOLOv4 Tiny vs. MobileNet V2 Classification

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.