Sky Outline Matting Dataset

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Project Overview:

Objective

In creating the Pest Detection Dataset, our goal was to build a comprehensive resource for identifying and classifying agricultural pests and diseases. This dataset is intended to be the foundation for developing AI tools that help farmers detect pests early and manage them effectively.

Scope

Our team set out to gather a diverse range of images, concentrating on horizons and skies. Consequently, we carefully annotated this collection to highlight sky regions, demonstrating our expertise in creating datasets for machine learning models. By diligently labeling each image, we ensured the data’s accuracy and usability.

Sources

Urban cityscapes showcasing towering buildings.
Idyllic rural settings with serene landscapes.
Peaceful beach views.
Rugged mountain scenes.
Beautiful sunsets and sunrises.
Enchanting night skies, with and without stars.

Data Collection Metrics

Total Images: 80,000
Cityscapes: 20,000
Rural Landscapes: 15,000
Beach Horizons: 12,000
Mountainous Terrains: 18,000
Sunsets/Sunrises: 10,000
Night Skies: 5,000

Annotation Process

Stages

Image Pre-processing: We start by enhancing the image quality. This crucial step ensures a clear demarcation of the sky.
Sky Region Identification: Next, we employ advanced tools to precisely highlight the sky regions, ensuring accuracy.
Matting Annotation: After identifying the sky, we focus on matting annotation. This involves accurately marking the sky boundaries, even including semi-translucent areas.
Validation: Finally, we rigorously cross-check the results. We use both automated tools and manual reviews to ensure the highest accuracy.

Annotation Metrics

Total Sky Boundary Pixels Annotated: 160 million
Fully Opaque Sky Pixels: 120 million
Semi-Translucent Sky Pixels: 40 million

Quality Assurance

Stages

Automated Matting Tools: Using advanced technology, we validate with precision and efficiency in our processes. Additionally, this ensures our results are reliable and accurate.
Expert Review: Furthermore, we involve industry specialists to oversee complex cases. Their expertise and accuracy help us handle even the most challenging tasks effectively.
Inter-annotator Agreement: To ensure consistency among different annotators, we implement rigorous standards. Moreover, we conduct regular checks to maintain high-quality results.

QA Metrics

Annotations Reviewed by Experts: 3 million pixels
Inconsistencies Identified and Rectified: 600,000 pixels

Conclusion

The Sky Outline Matting Dataset is a top provider of high-quality data for sky segmentation tasks. It drives advancements in graphics, film production, and simulation tools. With careful annotation and validation, the dataset ensures top accuracy and precision. Consequently, it stands out as a reliable resource in its field.