Dog Poop Dataset

The Dog Pooping Dataset (DPD) is a meticulously curated collection of images designed to train and evaluate AI-powered image classification models, such as MobileNet V2, for detecting whether a dog is pooping or not. Tailored for binary classification tasks, this dataset categorizes images into two distinct classes:
✔ Poop – Images where a dog is actively pooping.
✔ Not Poop – Images where a dog is in any other posture or activity.

Key Features

✅ High-Quality, Labeled Images – Manually labeled, cropped, and processed for precision.
✅ Diverse Representation – Includes various dog breeds, environments, and postures to enhance model generalizability.
✅ AI & Deep Learning Optimized – Suitable for CNN models like MobileNet V2, ResNet, EfficientNet, and more.
✅ Ideal for Binary Classification – Perfect for training AI models in pet activity recognition & behavior analysis.
✅ Valuable for Smart Pet Monitoring – Supports automated pet monitoring systems, smart home devices, and veterinary research.

Dataset Composition & Sources

Images in the Dog Pooping Dataset (DPD) are sourced from a mix of publicly available videos and original recordings to ensure a broad representation of real-world pet activities. Each image has been carefully processed to maintain quality and consistency, making it ideal for machine learning research and AI-based pet monitoring applications.

Applications

🔹 AI-powered pet behavior analysis & monitoring
🔹 Computer vision models for smart pet cameras
🔹 Veterinary research & animal activity tracking
🔹 Automated dog activity classification for smart devices