YOLOV8-traffic-signs Computer Vision Model
How to use the YOLOV8-traffic-signs Detection API
Try This Model
Drop an image here or click to upload
Or try a test image
Model type: Roboflow 3.0 Object Detection (Fast)
Dataset: yolov8-traffic-signs/1 (1006 images)
Checkpoint: COCO
Aug 6, 2024
Code Snippets
from inference_sdk import InferenceHTTPClient
CLIENT = InferenceHTTPClient(
api_url="https://serverless.roboflow.com",
api_key="API_KEY"
)
result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="yolov8-traffic-signs/1")Give your agent everything it needs
Or, Use Free Cycle Lane, NO-Horn and Speed-limit-40 Detection API
Powered by general detection model
Code
pip install inference-sdk# 1. Import the library
from inference_sdk import InferenceHTTPClient
# 2. Connect to your workspace
client = InferenceHTTPClient(
api_url="https://serverless.roboflow.com",
api_key="API_KEY"
)
# 3. Run your workflow on an image
result = client.run_workflow(
workspace_name="<YOUR_WORKSPACE>",
workflow_id="<YOUR_WORKFLOW_ID>",
images={
"image": "YOUR_IMAGE.jpg" # Path to your image file
},
parameters={
"classes": "Cycle Lane, NO-Horn, Speed-limit-40, Speed-limit-80"
},
use_cache=True # cache workflow definition for 15 minutes
)
# 4. Get your results
print(result)Run on custom image
Drop an image here or click to upload
Detecting classes:
Or try a test image
About YOLOV8-traffic-signs Model
This project aim to train the yolov8 model on traffic sign data to recognize the most common traffic sign.👍
Roboflow Agent
Tell the agent what you want to build.
Cite This Project
LicenseCC BY 4.0If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ yolov8-traffic-signs_dataset,
title = { YOLOV8-traffic-signs Dataset },
type = { Open Source Dataset },
author = { GLob },
howpublished = { \url{ https://universe.roboflow.com/glob-krdlr/yolov8-traffic-signs } },
url = { https://universe.roboflow.com/glob-krdlr/yolov8-traffic-signs },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { aug },
note = { visited on 2026-07-29 },
}










