ALS Detection (Prototype) Computer Vision Dataset
How to use the ALS Detection (Prototype) Detection API
Try This Model
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Model type: Roboflow Instant
Dataset: als-detection-prototype/1 (0 images)
Model ID: oil-palm-bagworm/als-detection-prototype-instant-1
Dec 9, 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="oil-palm-bagworm/als-detection-prototype-instant-1")Give your agent everything it needs
Or, Use Free 0, 11 and BOTTOM_DSI0 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": "0, 11, BOTTOM_DSI0, BOTTOM_DSI1, BOTTOM_DSI2"
},
use_cache=True # cache workflow definition for 15 minutes
)
# 4. Get your results
print(result)Run on custom image
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Detecting classes:
Or try a test image
About ALS Detection (Prototype) Model
UAV-based image dataset for detecting leaf severity levels in oil palm. Leaf regions are labeled using a DSI 0–4 scale based on color changes to support early development of an AI model for Algal Leaf Spot detection.
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Cite This Project
LicenseBY-NC-SA 4.0If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ als-detection-prototype_dataset,
title = { ALS Detection (Prototype) Dataset },
type = { Open Source Dataset },
author = { Oil Palm Bagworm },
howpublished = { \url{ https://universe.roboflow.com/oil-palm-bagworm/als-detection-prototype } },
url = { https://universe.roboflow.com/oil-palm-bagworm/als-detection-prototype },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { dec },
note = { visited on 2026-07-29 },
}