To receive notifications about scheduled maintenance, please subscribe to the mailing-list gitlab-operations@sympa.ethz.ch. You can subscribe to the mailing-list at https://sympa.ethz.ch

README.md 1.52 KB
Newer Older
1
# PhenoFly data processing tools
luroth's avatar
luroth committed
2

3
© Lukas Roth, Group of crop science, ETH Zurich
4

5
License: GPL-2 
6

luroth's avatar
luroth committed
7
## Content
8
9
10
11
12

The *PhenoFly data processing tool* repository hosts Python code related to **high-throughput field phenotyping** with unmanned aerial systems (UAS).
Methods are based on viewing geometries [1] and **multi-view images** [2].

Three major steps are required to preprocess flight campaigns:
13
14

1. [Image mask generation (Standalone Agisoft Script)](ImageProjectionAgisoft/README.md)
15
16
17
2. [Image segmentation with Random Forest](ActiveLearningSegmentation/README.md)
3. [Multi-view image generation](MultiViewImage/README.md)

18
After these steps, one of the following methods can be used to extract phenotyping traits:
19

20
- [Early growth trait extraction](EarlyGrowthTraitExtraction/README.md)
21

luroth's avatar
luroth committed
22
23
Additionally, usefull utils for other tasks can be found here:
- [Utils](Util/README.md)
24

luroth's avatar
luroth committed
25
## Deprecated content
26

luroth's avatar
luroth committed
27
- [Image mask generation (Ray tracing to DTM, deprecated)](ImageProjectionRayTracing/README.md)
28

29
---
30

luroth's avatar
luroth committed
31
[1]: Roth, Aasen, Walter, Liebisch (2018). Extracting leaf area index using viewing geometry effects—A new perspective on high-resolution unmanned aerial system photography, ISPRS Journal of Photogrammetry and Remote Sensing. https://doi.org/10.1016/j.isprsjprs.2018.04.012
32

luroth's avatar
luroth committed
33
[2]: Roth, Camenzind, Aasen, Kronenberg, Barendregt, Camp, Walter, Kirchgessner, Hund (2020). Repeated Multiview Imaging for Estimating Seedling Tiller Counts of Wheat Genotypes Using Drones. Plant Phenomics, 2020(3729715). https://doi.org/10.34133/2020/3729715