Test Depth Estimation Accuracy on Panoramic Images

[Waidhoferj]

Our depth estimation relies on the out-of-the-box implementation of the MiDaS model. MiDaS works well on standard aspect-ratio images, but we need to ensure it works for panoramic data.

Suggestions:

1. Find a dataset for panoramic imagery with accurate depth representations. Here is an example to look into.
2. Feed one of these images into the MiDaS model. Feel free to use the example MiDaS Notebook I built.
3. Describe model accuracy with a loss function.
4. Report back with your findings (in the comments below)
5. Mess around with transfer learning and try to improve the default model accuracy.

[nairrrahul]

Tried out MiDaS with 10 images from this dataset
Used mean squared error for loss calculations
Original Image and Corresponding "Error Map" for 10 images, white -> black is more -> less error
the main sources for error are generally foliage, detail in the distance, or distortion from the sides of the image
Colab (.npy files taken from /val/depth in dataset)

[richagadgil]

Wanted to add an extra, optional step: Assessing how well each model works with our test set of Cal Poly panoramas.