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End of preview. Expand in Data Studio

Nameplate Detection Dataset

This dataset contains 1000 images for object detection of nameplates and related warning signs.

Dataset Details

  • Total Images: 1000
  • Classes: 4 (nameplate, w, warning, yellow)
  • Train: 702 images
  • Validation: 149 images
  • Test: 149 images

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("kahua-ml/nameplate1")

# Access splits
train_data = dataset["train"]
val_data = dataset["valid"] 
test_data = dataset["test"]

# Example usage
example = train_data[0]
print(f"Image ID: {example['image_id']}")
print(f"Image size: {example['width']}x{example['height']}")
print(f"Number of objects: {len(example['objects']['bbox'])}")
print(f"Categories: {example['objects']['category']}")

Data Format

Each example contains:

  • image_id: Unique identifier for the image
  • image: PIL Image object
  • width: Image width in pixels
  • height: Image height in pixels
  • objects: Dictionary containing:
    • bbox: List of bounding boxes [x, y, width, height] in COCO format
    • category_id: List of category IDs
    • category: List of category names
    • area: List of bounding box areas
    • iscrowd: List of crowd flags

Original Dataset

This dataset was sourced from Roboflow Universe: https://universe.roboflow.com/flying-squirrels/nameplate-detection

Citation

@misc{
    nameplate-detection_dataset,
    title = { Nameplate Detection Dataset },
    type = { Open Source Dataset },
    author = { Flying Squirrels },
    howpublished = { \url{ https://universe.roboflow.com/flying-squirrels/nameplate-detection } },
    url = { https://universe.roboflow.com/flying-squirrels/nameplate-detection },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { mar },
    note = { visited on 2025-01-25 },
}
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