From dfe26ba8effeb48ca74a070443f1fd2165a46bf4 Mon Sep 17 00:00:00 2001 From: Darmstadtium Date: Sat, 31 Dec 2022 11:39:56 +0100 Subject: [PATCH] Update 'README.md' --- README.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index c00bdd4..d07edb0 100644 --- a/README.md +++ b/README.md @@ -13,13 +13,15 @@ A project made in collaboration with otyugh. - _dict_classification.json: https://univangersfr-my.sharepoint.com/:u:/g/personal/aurelien_valentin_etud_univ-angers_fr/EUk27BFQRKdJlSPFi30-BScBLsY3Kno4XaubfzcaCljVYg?e=5fcA7V 3- While the files are downloading, you'll have to choose the species you want to learn. Three ways are proposed: -- You can use the default list of all species found in France (sorted by their frequence in this country). -- You can go on GeoPl@ntNet (https://identify.plantnet.org/prediction) and select an area. An AI will list you the 100 most common plants in there. Keep the "sorting by GBIF" and download the CSV file. You'll have to specify the name of your file in the SPECIE_LIST_PATH_IF_GBIF_METHOD variable in main.py. -- You can create your own list of plants you want to learn. In this case, please create a txt file with one specie by line. You'll have to specify the name of your file in the MY_OWN_LIST_PATH variable in main.py. +- You can use the default list of all species found in France (sorted by their frequence in this country). Its generation is included in main.py. +- You can go on GeoPl@ntNet (https://identify.plantnet.org/prediction) and select an area. An AI will list you the 100 most common plants in there. Keep the "sorting by GBIF" and download the CSV file. You'll have to specify the name of your file in the SPECIE_LIST_PATH_IF_GBIF_METHOD variable in main.py. France_GBIF.csv is an example of file you may obtain. +- You can create your own list of plants you want to learn. In this case, please create a txt file with one specie by line. You'll have to specify the name of your file in the MY_OWN_LIST_PATH variable in main.py. You can take Species_list.txt as a template. 4- Change parameters of main.py. Everything is written in the comments. -5- If all the files are downloaded, put them in the same directory and then run the code to obtain AnkIdentification.apkg. +5- Install the genanki module by writting "pip install genanki" in your terminal. It allows you to create Anki decks and cards with Python, further information here: https://github.com/kerrickstaley/genanki. + +6- If all the files are downloaded, put them in the same directory and then run the code to obtain AnkIdentification.apkg. The output with the 200 most common plants according to the default list is given. ### 2 Use Anki If you don't know Anki, here are the steps to use your output file.