Models
YOLOv10 vs. YOLOv3 Keras

YOLOv10 vs. YOLOv3 Keras

Both YOLOv10 and YOLOv3 Keras are commonly used in computer vision projects. Below, we compare and contrast YOLOv10 and YOLOv3 Keras.

Models

icon-model

YOLOv10

YOLOv10 is a real-time object detection model introduced in the paper "YOLOv10: Real-Time End-to-End Object Detection".
Learn more about YOLOv10
icon-model

YOLOv3 Keras

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. Keras implementation.
Learn more about YOLOv3 Keras
Model Type
Object Detection
--
Object Detection
--
Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
--
YOLO
--
Frameworks
PyTorch
--
Keras
--
Annotation Format
Instance Segmentation
Instance Segmentation
GitHub
--
View Repo
--
View Repo
GitHub Stars
7800
--
7.1k+
--
License
GNU Affero General Public
--
MIT
--
Paper
--
View Paper
--
View Paper
Training Notebook
Train on Colab
--
Train on Colab
--
Deploy Model
--
rocket icon
Deploy with Roboflow
--
rocket icon
Deploy with Roboflow
Compare Alternatives
--
Compare with...
--
Compare with...

Compare YOLOv10 and YOLOv3 Keras with Autodistill

Compare YOLOv10 vs. YOLOv3 Keras

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.