Models
MobileNet V2 Classification vs. YOLOv3 PyTorch

MobileNet V2 Classification vs. YOLOv3 PyTorch

Both MobileNet V2 Classification and YOLOv3 PyTorch are commonly used in computer vision projects. Below, we compare and contrast MobileNet V2 Classification and YOLOv3 PyTorch.

Models

icon-model

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.
icon-model

YOLOv3 PyTorch

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. PyTorch version.
Model Type
Classification
--
Object Detection
--
Model Features
Item 1 Info
Item 2 Info
Architecture
--
YOLO
--
Frameworks
--
PyTorch
--
Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
--
7.2k+
--
License
--
GPL-3.0
--
Training Notebook

Compare MobileNet V2 Classification and YOLOv3 PyTorch with Autodistill

Compare MobileNet V2 Classification vs. YOLOv3 PyTorch

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.