Model Details: DPT Hybrid (also known as MiDaS 3.0) Dense Prediction Transformer (DPT) model trained on 1.4 million images for monocular depth estimation. It was introduced in the paper Vision Transformers for Dense Prediction by Ranftl et al. (2021) and first released in this repository. DPT uses the Vision Transformer (ViT) as backbone and adds a neck + head on top for monocular depth estimation. This repository hosts the "hybrid" version of the model as stated in the paper. DPT Hybrid diverges from DPT by using ViT hybrid as a backbone and taking some activations from the backbone. The model card has been written in combination by the Hugging Face team and Intel. Model Detail Description Model Authors Company Intel Date December 22, 2022 Version 1 Type Computer Vision Monocular Depth Estimation Paper or Other Resources Vision Transformers for Dense Prediction and GitHub Repo License Apache 2.0 Questions or Comments Community Tab and Intel Developers Discord Intended Use Description Primary intended uses You can use the raw model for zero shot monocular depth estimation. See the model hub to look for fine tuned versions on a task that interests you. Primary intended users Anyone…
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