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jkdxbns/autonomous-driving-carla

sourceHugging Facemitupdated 9mo agoView on Hugging Face

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Model Card

Autonomous Driving CARLA Models

Pre-trained models for autonomous driving in the CARLA 0.9.15 simulator.

Models

Model	File	Size	Description
YOLO11n	`yolo_carla_best.pt`	~6MB	Object detection (vehicles, pedestrians, traffic lights, speed signs)
UFLD	`ufld_carla_best.pth`	~735MB	Lane detection fine-tuned on CARLA
TuSimple	`tusimple_18.pth`	~245MB	Pre-trained lane detection backbone

YOLO11n Object Detection

Custom-trained on CARLA simulator data.

Classes:

—0: Vehicle
—1: Pedestrian
—2: Traffic Light
—3: Speed Limit Sign

Training:

—Epochs: 250
—Batch Size: 128
—Optimizer: AdamW
—Learning Rate: 0.005
—Image Size: 640×640

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UFLD Lane Detection

Fine-tuned Ultra Fast Lane Detection model.

Architecture:

—Backbone: ResNet-18
—Grid: 100×56
—Input: 800×288

Training:

—Epochs: 50
—Batch Size: 32
—Optimizer: Adam
—Learning Rate: 1e-4
—Loss: SoftmaxFocalLoss + ParsingRelationLoss

[image]

Usage

python

from huggingface_hub import hf_hub_download

# Download YOLO model
yolo_path = hf_hub_download(
    repo_id="jkdxbns/autonomous-driving-carla",
    filename="yolo_carla_best.pt"
)

# Download UFLD model
ufld_path = hf_hub_download(
    repo_id="jkdxbns/autonomous-driving-carla",
    filename="ufld_carla_best.pth"
)

GitHub Repository

Full source code: github.com/jkdxbns/autonomous-driving-carla

Author

Justin Mascarenhas CMPE 789 - Robot Perception Rochester Institute of Technology

License

MIT License