Universe

Train_chai Computer Vision Dataset

bySPKTTask:
Object Detection
License:CC BY 4.0

How to use the Train_chai Detection API

Try This Model

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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="spkt-kpu6m/train_chai-instant-1")
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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": "Dao, Dau, Soda, Train-chai, Viet quoc"
  },
  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 
See all 60 imagesTrain_chai Train-chai sample showing Dao, Dau, Soda, Viet quocTrain_chai Train-chai sample showing Dao, Dau, Soda, Viet quocTrain_chai Train-chai sample showing Dao, Dau, Soda, Viet quocTrain_chai Train-chai sample showing Viet quocTrain_chai Train-chai sample showing DauTrain_chai Train-chai sample showing DauTrain_chai Train-chai sample showing Dao, Dau, Soda, Viet quocTrain_chai Train-chai sample showing DauTrain_chai Train-chai sample showing DauTrain_chai Train-chai sample showing Dao, Dau, Soda, Viet quocTrain_chai Train-chai sample showing Viet quocTrain_chai Train-chai sample showing Viet quoc

About Train_chai Model

A description for this project has not been published yet.

Cite This Project

LicenseCC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ train_chai_dataset,
  title = { Train_chai Dataset },
  type = { Open Source Dataset },
  author = { SPKT },
  howpublished = { \url{ https://universe.roboflow.com/spkt-kpu6m/train_chai } },
  url = { https://universe.roboflow.com/spkt-kpu6m/train_chai },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2026 },
  month = { jun },
  note = { visited on 2026-07-29 },
}

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