# Holoscan Sample App Data for AI-based Endoscopy Depth Estimation

This resource contains the model for depth estimation in laparoscopic videos by Ozyoruk et. al [1].

  [[1] Ozyoruk, K. B., Gokceler, G. I., Bobrow, T. L., Coskun, G., Incetan, K., Almalioglu, Y., ... & Turan, M. (2021). EndoSLAM dataset and an unsupervised monocular visual odometry and depth estimation approach for endoscopic videos. Medical image analysis, 71, 102058.](https://arxiv.org/abs/2006.16670)

## Model
The AI model for depth estimation in endoscopy is a fully convolutional model that expects a RGB image with size `480x270`, normalized in the range `[-2.0, 2.44]`.

Note: The provided model is in ONNX format. It will automatically be converted into a TensorRT model (.engine) the first time it is processed by a Holoscan application.

## License
Refer to the [license agreement](https://github.com/CapsuleEndoscope/EndoSLAM/blob/master/LICENSE) for the use of the depth estimation model.

holoscan_endoscopy_depth_estimation_sample_data

Holoscan Sample App Data for AI-based Endoscopy Depth Estimation

Endoscopy Depth Estimation App Data

Holoscan Sample App Data for AI-based Endoscopy Depth Estimation

Model

License