fix_viewer (#8)

- rename potential test set folder & README (4444025aa49dc2b0b5d046195e169f0384c4410c)

README.md

@@ -87,7 +87,7 @@ English, Latin
         lilabc_test-<dataset_name>.ipynb
         lilabc_test-filter.ipynb
         lilabc_test-filter.py
-    potential-test-sets/
+    potential-sets/
         lila-taxonomy-mapping_release.csv
         lila_image_urls_and_labels.csv
         <dataset_name>_image_urls_and_labels.csv
@@ -95,9 +95,9 @@ English, Latin
 
 ### Data Instances
 
-**potential-test-sets/lila_image_urls_and_labels.csv:** Reduced down to the datasets of interest listed below (from [potential-test-sets/lila_image_urls_and_labels.csv](https://huggingface.co/datasets/imageomics/IDLE-OO-Camera-Traps/blob/37b93ddf25c63bc30d8488ef78c1a53b9c4a3115/data/potential-test-sets/lila_image_urls_and_labels.csv) (sha256:3fdf87ceea75f8720208a95350c3c70831a6c1c745a92bb68c7f2c3239e4c455)); all those with `original_label` "empty" or null `scientific_name` (these had non-taxa labels) were removed. 
+**potential-sets/lila_image_urls_and_labels.csv:** Reduced down to the datasets of interest listed below (from [potential-sets/lila_image_urls_and_labels.csv](https://huggingface.co/datasets/imageomics/IDLE-OO-Camera-Traps/blob/37b93ddf25c63bc30d8488ef78c1a53b9c4a3115/data/potential-sets/lila_image_urls_and_labels.csv) (sha256:3fdf87ceea75f8720208a95350c3c70831a6c1c745a92bb68c7f2c3239e4c455)); all those with `original_label` "empty" or null `scientific_name` (these had non-taxa labels) were removed. 
 Additionally, we added a `multi_species` column (boolean to indicate multiple species are present in the image--it gets listed once for each species in the image) and a count of how many different species are in each of those images (`num_species` column).
-This was then subdivided into CSVs for each of the target datasets (`potential-test-sets/<dataset_name>_image_urls_and_labels.csv`) in `notebooks/lilabc_test-filter.ipynb`. Each dataset was evaluated and sampled in its associated notebook (`notebooks/lilabc_test-<dataset_name>.ipynb`).
+This was then subdivided into CSVs for each of the target datasets (`potential-sets/<dataset_name>_image_urls_and_labels.csv`) in `notebooks/lilabc_test-filter.ipynb`. Each dataset was evaluated and sampled in its associated notebook (`notebooks/lilabc_test-<dataset_name>.ipynb`).
 
 There are 184 unique scientific names in this subset (180 by full 7-rank) of those labeled at the image-level (as indicated by the CSV). This was then subdivided into CSVs for each of the target datasets (`<dataset_name>-balanced.csv`).
 These were initially identified as image-level labeled datasets and those that are a meaningful measure of our biodiversity-focused model (e.g., includes rare species--those less-commonly seen, targeting areas with greater biodiversity). The balanced datasets for each are described below.