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Project Type
Object Detection
Classification
Instance Segmentation
+3

Model Type
RF-DETR
YOLO26
YOLOv11
YOLOv8
YOLO-NAS
+4


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Custom

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

# 4. Get your results
print(result)

Top Bavure Datasets and Models

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

Automated inspection project thumbnail
Object Detection

Automated inspection

by Custom data PFE

30 images·2
AnomalieBavureMicrobilleRestache-noir
YOLO PROJET project thumbnail
Object Detection

YOLO PROJET

by QUALITY INSPECTION

535 images·1 model
PN-1SNA1-NOK-BAVUREPN-1SNA1-NOK-CONTAMINATIONPN-1SNA1-NOK-MANQUE DE MATIEREPN-1SNA1-OKobjects
clean_data project thumbnail
Object Detection

clean_data

by test

56 images
corrosionbavurefroissépointtrou
Détection des défauts des plaque project thumbnail
Object Detection

Détection des défauts des plaque

by zekri plauqs ondules

95 images·4 models
D-tection-des-d-fauts-des-plaqueDefaut de delaminagedefaut bavuredefaut de casse au coindefaut_fissureplauqe confomre
PFE project thumbnail
Object Detection

PFE

by NADINE

1.18k images
bavuremanque_milieumanque_surface
Showing 1 - 5 of 5
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