rld_Experiment Computer Vision Model
How to use the rld_Experiment Segmentation API
Try This Model
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Model type: Roboflow 3.0 Instance Segmentation (Fast)
Dataset: rld_experiment/4 (10296 images)
Checkpoint: COCOn-seg
Mar 10, 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="rld_experiment/4")Give your agent everything it needs
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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": "bacterial_leaf_blight, fungal_spot, leaf_scald, rice_hispa, tungro"
},
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 rld_Experiment Model
testing to make the model more efficient at detecting
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{ rld_experiment_dataset,
title = { rld_Experiment Dataset },
type = { Open Source Dataset },
author = { Clifford Baniel },
howpublished = { \url{ https://universe.roboflow.com/clifford-baniel-nnyzo/rld_experiment } },
url = { https://universe.roboflow.com/clifford-baniel-nnyzo/rld_experiment },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2026 },
month = { mar },
note = { visited on 2026-07-29 },
}