Models
MobileNet V2 Classification vs. Faster R-CNN

MobileNet V2 Classification vs. Faster R-CNN

Both MobileNet V2 Classification and Faster R-CNN are commonly used in computer vision projects. Below, we compare and contrast MobileNet V2 Classification and Faster R-CNN.

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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Faster R-CNN

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server.
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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Frameworks
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TensorFlow 1.5
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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7.5k+
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License
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MIT
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Training Notebook

Compare MobileNet V2 Classification and Faster R-CNN with Autodistill

Compare MobileNet V2 Classification vs. Faster R-CNN

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.