Commit 48471608 authored by Clément Pinard's avatar Clément Pinard
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README fix links

parent 9e81b536
......@@ -8,8 +8,8 @@ For a brief recap of what it does, see section [How it works](#how-it-works)
* [Software Dependencies](#software-dependencies)
* [Hardware Dependencies](#hardware-dependencies)
* [How it works](#how-it-works)
* [Step by step guide](#usage)
* [Special case : adding new images to an existing constructed dataset](#special-case-adding-new-images-to-an-existing-dataset)
* [Usage](#usage)
* [Special case : adding new images to an existing constructed dataset](#special-case--adding-new-images-to-an-existing-dataset)
* [Using the constructed dataset for evaluation](#evaluation)
* [Detailed method with the manoir example](#detailed-method-with-the-manoir-example)
* [TODO](#todo)
......@@ -38,7 +38,7 @@ For PDrAW, there should be a `native-wrapper.sh` file that you to keep a track o
For COLMAP, you will need a vocab tree for feature matching. You can download them at https://demuc.de/colmap/#download . In our tests, we took the 256K version.
## Hardware dependecies
## Hardware dependencies
To recreate the results of the study, you will need these hardware pieces :
- Parrot Anafi
......@@ -1100,6 +1100,9 @@ All these steps can be done under the script `picture_localization.py` with the
* `--rebuild_occlusion_mesh` : If selected, will rebuild a new dense point cloud and delauney mesh. Useful when new images see new parts of the model
* `--generic_model` : COLMAP model for image folders. Same zoom level assumed throughout whole folders. See https://colmap.github.io/cameras.html (default: OPENCV)
## Evaluation
TODO
## Detailed method with the "Manoir" example
......@@ -1175,7 +1178,7 @@ Thorough photogrammetry was done with 1000 frames. Notice that not all the area
[![Alt text](https://img.youtube.com/vi/NLIvrzUB9bY/0.jpg)](https://www.youtube.com/watch?v=NLIvrzUB9bY&list=PLMeM2q87QjqjAAbg8RD3F_J5D7RaTMAJj)
#Todo
# Todo
## Better point cloud registration
......
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