Models
MobileNet V2 Classification vs. YOLOv4 Tiny

MobileNet V2 Classification vs. YOLOv4 Tiny

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

Models

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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.
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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
Model Type
Classification
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
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ResNet-D, YOLO
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Frameworks
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Darknet
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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License
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YOLO
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Training Notebook

Compare MobileNet V2 Classification and YOLOv4 Tiny with Autodistill

Compare MobileNet V2 Classification vs. YOLOv4 Tiny

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.