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Project Type
Object Detection
Classification
Instance Segmentation
+3

Model Type
RF-DETR
YOLO26
YOLOv11
YOLOv8
YOLO-NAS
+4

Related Objects of Interest:
변성잔류암제올라이트탄산염암페그마타이트

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Custom

Try Sillimanite Detection API

Run on custom image

Drop or click to upload

# 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": "sillimanite"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Top Sillimanite Datasets and Models

The datasets below can be used to train fine-tuned models for sillimanite detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.

Related Objects of Interest:
변성잔류암제올라이트탄산염암페그마타이트
thin section - 2 project thumbnail
Classification

thin section - 2

by GyoengSan Science school

173 images·3
sillimanite각섬암굴조개규암남정석대리암반려암백립암변성잔류암복족류사암사장석삼엽충석회석회암섬록암셰일안산암유문암이암
thin section - 1 project thumbnail
Classification

thin section - 1

by GyeongSan science high school

432 images·1 model·4
sillimanite각섬암굴조개규암남정석대리암반려암백립암변성잔류암복족류사암사장석삼엽충석회석회암섬록암셰일안산암유문암이암
thin section - 3 project thumbnail
Object Detection

thin section - 3

by GyeongSan science high school

431 images·2 models·5
BasaltCarbonatgesteinCrassostreaGastropodaGranuliteKyaniteMudstonePhylliteQuartziteSchistShaleZeoliteamphiboliteandesitechertdioritegabbrogneissgranitehornfels
Showing 1 - 3 of 3
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