yolov8plus Computer Vision Dataset
How to use the yolov8plus Detection API
Try This Model
Drop an image here or click to upload
Or try a test image
Model type: Roboflow Instant
Dataset: yolov8plus/1 (253 images)
Model ID: yolos-workspace-lp8ri/yolov8plus-instant-1
Mar 31, 2026
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="yolos-workspace-lp8ri/yolov8plus-instant-1")Give your agent everything it needs
Or, Use Free Resistor, Capacitor and Wire 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": "Resistor, capacitor, Wire, ADS1115"
},
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 yolov8plus Model
A description for this project has not been published yet.
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{ yolov8plus_dataset,
title = { yolov8plus Dataset },
type = { Open Source Dataset },
author = { yolos Workspace },
howpublished = { \url{ https://universe.roboflow.com/yolos-workspace-lp8ri/yolov8plus } },
url = { https://universe.roboflow.com/yolos-workspace-lp8ri/yolov8plus },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2026 },
month = { jul },
note = { visited on 2026-07-29 },
}










