foam ipal Computer Vision Model
How to use the foam ipal Segmentation API
Try This Model
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Model type: Roboflow 3.0 Instance Segmentation (Accurate)
Dataset: foam-ipal-3dcyf/3 (757 images)
Checkpoint: foam_sungai-6nk31/2
Sep 5, 2025
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="foam-ipal-3dcyf/3")Give your agent everything it needs
Or, Use Free Foam-ipal Detection API
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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": "foam-ipal"
},
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 foam ipal Model
Mendeteksi Foam / Busa di sungai dan Bak IPAL untuk menghitung luas Foam
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{ foam-ipal-3dcyf_dataset,
title = { foam ipal Dataset },
type = { Open Source Dataset },
author = { cun+lpr },
howpublished = { \url{ https://universe.roboflow.com/cun-lpr/foam-ipal-3dcyf } },
url = { https://universe.roboflow.com/cun-lpr/foam-ipal-3dcyf },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { sep },
note = { visited on 2026-07-29 },
}










