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Project Type
Object Detection
Classification
Instance Segmentation
+3

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

Related Objects of Interest:
a l ordre deecheance1echeance2montant-chiffre1montant-chiffre2

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Custom

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

# 4. Get your results
print(result)

Top Acceptation Datasets and Models

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

Related Objects of Interest:
a l ordre deecheance1echeance2montant-chiffre1montant-chiffre2
My First Project project thumbnail
Object Detection

My First Project

by Projet

230 images·3 models
A l ordre deAcceptationAcceptation signatureDate1Date2DomicilliationDomicilliation adresseEcheance1Echeance2Montant en lettresMontant-chiffre1Montant-chiffre2Montant-lettresMontant1Montant2Nom et adresseNom et adresse de tireNumOrdre de paimentOui - Non
Lettre de Change 13 objets project thumbnail
Object Detection

Lettre de Change 13 objets

by Projet

230 images
A l ordre deAcceptationDomiciliationEcheance1Echeance2Montant-chiffre1Montant-chiffre2Montant-lettresNom et adresseOrdre_de_paimentRIB 1RIB 2Signature_du_tire
Showing 1 - 2 of 2
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