Extract geometric traits from images of tomatoes, peppers, and more.
Extract geometric trait measurements from images of tomatoes and other fruit.
General approach inspired by Suxing Liu, in particular Smart Plant Growth Top-Down Traits.
PlantCV also used for skeletonization, pruning, leaf & stem counting, etc.
Docker is required to run this project in a Unix environment.
To install from source, clone the project with git clone https://github.com/van-der-knaap-lab/tomato-analyzer-lite.git
, then build the image from the root directory with docker build -t <your tag> -f Dockerfile .
.
Alternatively, you can just pull the pre-built image with docker pull van-der-knaap-lab/tomato-analyzer-lite
, or allow it to be pulled automatically from another Docker CLI command (as below).
To analyze an image:
docker run wbonelli/tomato-analyzer-lite python3.8 /opt/tomato-analyzer-lite/talite.py <input file>
By default, output files will be written to the current working directory. To specify a different output location, use -o <full path to output directory>
.
To set up a development environment and explore or modify the source, just mount the project root as your container’s working directory, for instance:
docker run -it -v $(pwd):/opt/dev -w /opt/dev wbonelli/tomato-analyzer-lite bash
Then invoke the CLI with python3.8 /opt/code/cli.py <input file>
.
Git is also instructed to ignore data
and output
directories for convenience.