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wuhp/
yolocar

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car-75e-11n

Model Overview

Architecture: YOLOv11
Training Epochs: 75
Batch Size: 32
Optimizer: auto
Learning Rate: 0.0005
Data Augmentation Level: Moderate

Training Metrics

mAP@0.5: 0.88072

Class IDs

Class ID	Class Name
0	Vehicle

Datasets Used

aerial-cars-rqcqh_v2
bikedetection-7bpwy_v2
car-detection-pyxz2_v4
cars-bytt8_v35
transport-rhkah_v8
vehiclecount_v4
vehicles-q0x2v-8kns4_v1

Class Image Counts

Class Name	Image Count
Vehicle	15163

Description

This model was trained using the YOLOv11 architecture on a custom dataset. The training process involved 75 epochs with a batch size of 32. The optimizer used was auto with an initial learning rate of 0.0005. Data augmentation was set to the Moderate level to enhance model robustness.

Usage

To use this model for inference, follow the instructions below:

python

from ultralytics import YOLO

# Load the trained model
model = YOLO('best.pt')

# Perform inference on an image
results = model('path_to_image.jpg')

# Display results
results.show()

wuhp/yolocar