PFE Computer Vision Dataset

byNADINETask:
Object Detection
License:CC BY 4.0

How to use the PFE Detection API

Try This Model

Drop an image here or click to upload

Or try a test image 

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="nadine-ew77n/pfe-vtoui-instant-1")
Give your agent everything it needs

Or, Use Free Bavure, Manque_milieu and Manque_surface Detection API

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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": "bavure, manque_milieu, manque_surface"
  },
  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 

About PFE 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{ pfe-vtoui_dataset,
  title = { PFE Dataset },
  type = { Open Source Dataset },
  author = { NADINE },
  howpublished = { \url{ https://universe.roboflow.com/nadine-ew77n/pfe-vtoui } },
  url = { https://universe.roboflow.com/nadine-ew77n/pfe-vtoui },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2026 },
  month = { may },
  note = { visited on 2026-07-29 },
}

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