Flowchart Computer Vision Dataset

bytestTask:
Object Detection
License:CC BY 4.0

About Flowchart Dataset

Used on this project:

Forked from:

  • Author: ISC UPIIZ students
  • Title: Flowchart 3b
  • Version: 3.0
  • Date: May 2020.
  • Editors: Onder F. Campos and David Betancourt.
  • Publisher Location: Zacatecas, Mexico.
  • Electronic Retrieval Location: https://www.kaggle.com/davbetm/flowchart-3b

Use Free Arrow_line_down, Arrow_line_left and Arrow_line_right 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": "arrow_line_down, arrow_line_left, arrow_line_right, arrow_line_up, decision"
  },
  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{ flowchart-etfvh-cqcnj_dataset,
  title = { Flowchart Dataset },
  type = { Open Source Dataset },
  author = { test },
  howpublished = { \url{ https://universe.roboflow.com/test-8oflz/flowchart-etfvh-cqcnj } },
  url = { https://universe.roboflow.com/test-8oflz/flowchart-etfvh-cqcnj },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2024 },
  month = { sep },
  note = { visited on 2026-07-29 },
}

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