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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:
red_piecered_kingboardgreen_kinghand

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Custom

Try Green_piece 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": "green_piece"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Top Green_piece Datasets and Models

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

Related Objects of Interest:
red_piecered_kingboardgreen_kinghand
checkers-board-hand-detection project thumbnail
Object Detection

checkers-board-hand-detection

by css

374 images·1 model
boardhand0board_cornergreen_kinggreen_piecered_kingred_piecesquare_brightsquare_dark
checkers-board-hand-detection 2 project thumbnail
Object Detection

checkers-board-hand-detection 2

by css

374 images
boardhandgreen_kinggreen_piecered_kingred_piecesquare_brightsquare_dark
ludo pieces detection project thumbnail
Object Detection

ludo pieces detection

by New Workspace

73 images·1 model
blue_piecegreen_pieceludo_boardred_pieceyellow_piece
ludo red & green project thumbnail
Object Detection

ludo red & green

by New Workspace

141 images
blue_piecegreen_piecered_pieceyellow_piece
checkers-dataset project thumbnail
Object Detection

checkers-dataset

by css

48 images
Empty_squareEmpty_square_greyEmpty_square_whiteGreen__kingGreen_pieceRed_KingRed_piecepieces
Showing 1 - 5 of 5
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