outdoor-finetune Computer Vision Dataset
About outdoor-finetune Dataset
Here are a few use cases for this project:
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Traffic Surveillance: The computer vision model can be applied to monitor real-time traffic situations. It can identify different vehicle types such as bikes, cars, trucks (ltvs), and any other unusual items on the road, which can help in traffic analysis and management.
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Autonomous Vehicles: The model can be integrated into the AI systems of self-driving cars to help them recognize and respond appropriately to the various entities in the outdoor environment, like different types of vehicles, bicycles, and people.
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Outdoor Security Systems: This model can enhance the capabilities of security cameras installed outdoors. With its ability to identify various outdoor objects and people, it can improve the effectiveness and responsiveness of such systems.
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Pedestrian Safety Application: The model can be integrated into apps designed for enhancing pedestrian safety. These apps can alert users when a vehicle or a bike is approaching.
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Smart City Planning: City planners can use the data generated by this model to understand traffic flow, pedestrian activities, and vehicle type distributions, supporting more informed infrastructure planning and development.
Use Free Car, Bike and Person Detection API
Powered by general detection model
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": "car, bike, person, 6, ltv"
},
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
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{ outdoor-finetune_dataset,
title = { outdoor-finetune Dataset },
type = { Open Source Dataset },
author = { Usama Amir },
howpublished = { \url{ https://universe.roboflow.com/usama-amir/outdoor-finetune } },
url = { https://universe.roboflow.com/usama-amir/outdoor-finetune },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { jun },
note = { visited on 2026-07-29 },
}