Monocular_Depth_Essentials

Monocular_Depth_Essentials is a lightweight, curated core dataset tailored specifically for Monocular Depth Estimation tasks.

Following the data preparation guidelines from the classic bts repository , this dataset extracts only the essential image-depth pairs from the massive raw KITTI and NYU Depth V2 datasets based strictly on the official Eigen Split train/test text lists.

If you are benchmarking or reproducing Depth Anything (V1/V2), BTS, or other monocular depth estimation models, this dataset allows you to bypass the tedious raw data downloading, filtering, and cleaning phases, offering a true "plug-and-play" experience.

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📌 Dataset Features & Structure

• Streamlined Data: Redundant sequences not evaluated in standard benchmarks are excluded, leaving only the exact samples specified by the official txt splits.
• Standard Evaluation: Fully adheres to the academic standard Eigen Split, ensuring fair and direct experimental comparison.
• Clean Directory: Organised to seamlessly align with dataloaders in mainstream depth estimation codebases.