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yolo11n-seg-bonnetjes

Object Detection
ultralytics
PyTorch
English
Dutch
segmentation
vision
yolo11
pickle
roboflow-universe
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metadata
license: apache-2.0
base_model:
  - Ultralytics/YOLO11
language:
  - en
  - nl
tags:
  - object-detection
  - segmentation
  - vision
  - ultralytics
  - yolo11
  - pytorch
  - pickle
  - roboflow-universe
library_name: ultralytics

Yolo11n bonnetjes

A YOLO11n segmentation model trained on receipts dataset.

Model summary

  • Layers: 203 layers
  • Parameters: 2,842,803
  • GFLOPs: 10.4
  • File size: 6 MB

example

Requirements 

pip install ultralytics

Python 

from ultralytics import YOLO

# Load model
model = YOLO("yolo11n-seg-bonnetjes.pt")

# Load image
image = Image.open('image.jpg')

# Inference
results = model.predict(
    image,
    imgsz=640,
    conf=0.60,
)

# Display result
results[0].show()

Dataset

  • Train: 4428
  • Valid: 242
  • Test: 146

Preprocessing (created w/ Roboflow)

  • Auto-Orient: Applied
  • Resize: 640x640

Augmentations (created w/ Roboflow)

  • Outputs per training example: 3
  • Flip: Horizontal
  • 90° Rotate: Clockwise, Counter-Clockwise, Upside Down
  • Crop: 0% Minimum Zoom, 20% Maximum Zoom
  • Rotation: Between -15° and +15°
  • Shear: ±10° Horizontal, ±10° Vertical
  • Grayscale: Apply to 15% of images
  • Saturation: Between -27% and +27%
  • Brightness: Between -21% and +21%
  • Exposure: Between -82% and +82%
  • Noise: Up to 0.1% of pixels

Results

example