TEST Computer Vision Model
How to use the TEST 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: test-fkbqb/2 (1569 images)
Checkpoint: test-fkbqb/1
Nov 11, 2023
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="test-fkbqb/2")Give your agent everything it needs
Or, Use Free JD Belfeld VH Natuurrood, KDN OVH Bruin Engobe and Laumans OVH Herfstkleur 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": "JD Belfeld VH Natuurrood, KDN OVH Bruin Engobe, Laumans OVH Herfstkleur, Laumans OVH Natuurrood, Laumans VH Zwart Verglaasd"
},
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 TEST Model
A description for this project has not been published yet.
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Cite This Project
LicenseCC BY 4.0If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ test-fkbqb_dataset,
title = { TEST Dataset },
type = { Open Source Dataset },
author = { Bart van de Luijtgaarde },
howpublished = { \url{ https://universe.roboflow.com/bart-van-de-luijtgaarde-ptwsc/test-fkbqb } },
url = { https://universe.roboflow.com/bart-van-de-luijtgaarde-ptwsc/test-fkbqb },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { nov },
note = { visited on 2026-07-29 },
}