jhb Computer Vision Dataset

bytrafficsignTask:
Classification
License:CC BY 4.040 views2 downloads

About jhb Dataset

A description for this project has not been published yet.

Use Free ≠•奆♆ нЂ•ђ•≠вЃҐ, ™га熥Ѓбвм and Б†™в•ஆЂм≠†п ѓпв≠®бвЃбвм Bacterial_spot Detection API

Powered by general detection model

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": "≠•奆♆ нЂ•ђ•≠вЃҐ, ™га熥Ѓбвм, Б†™в•ஆЂм≠†п ѓпв≠®бвЃбвм Bacterial_spot, В•аи®≠≠†п £≠®Ђм Blossom end rot, вЂп"
  },
  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 

Cite This Project

LicenseCC BY 4.0

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

@misc{ jhb-ya1wo_dataset,
  title = { jhb Dataset },
  type = { Open Source Dataset },
  author = { trafficsign },
  howpublished = { \url{ https://universe.roboflow.com/trafficsign-j7rrn/jhb-ya1wo } },
  url = { https://universe.roboflow.com/trafficsign-j7rrn/jhb-ya1wo },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { sep },
  note = { visited on 2026-07-29 },
}

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