Models
MobileNet V2 Classification vs. YOLOv7

MobileNet V2 Classification vs. YOLOv7

Both MobileNet V2 Classification and YOLOv7 are commonly used in computer vision projects. Below, we compare and contrast MobileNet V2 Classification and YOLOv7.

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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YOLOv7

YOLOv7 is a state of the art object detection model.
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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YOLO, CNN
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Frameworks
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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13.0k+
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License
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GPL-3.0
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Training Notebook

Compare MobileNet V2 Classification and YOLOv7 with Autodistill

Compare MobileNet V2 Classification vs. YOLOv7

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.