diff --git a/README.md b/README.md
index 0339379a9d5c4197372eb224bf4b83bf971f3a11..c6176fe973d45451456bf46a8cd44f77a96b9ff9 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,13 @@ tags:
- fish
- bird
- butterfly
+- image classification
+- zero-shot
+- traits
+- trait-detection
+- vlms
+- benchmarks
+- CV
language:
- en
pretty_name: VLM4Bio
@@ -52,11 +59,38 @@ configs:
# Dataset Card for VLM4Bio
+## **Instructions for downloading the dataset**
+
+* Install [Git LFS](https://docs.github.com/en/repositories/working-with-files/managing-large-files/installing-git-large-file-storage)
+* Git clone the VLM4Bio repository to download all metadata and associated files
+ * Run the following commands in a **terminal**:
+```bash
+git clone https://huggingface.co/datasets/imageomics/VLM4Bio
+cd VLM4Bio
+```
+
+**Downloading and processing bird images**
+* To download the bird images, run the following command:
+```bash
+bash download_bird_images.sh
+```
+* This should download the bird images inside `datasets/Bird/images`
+
+**Processing fish and butterfly images**:
+* Run the following command:
+```bash
+bash process_fish_butterfly_images.sh
+```
+* This should process fish and butterfly images inside `datasets/Fish/images` and `datasets/Butterfly/images` respectively.
+
## Dataset Details
VLM4Bio is a benchmark dataset of scientific question-answer pairs used to evaluate pretrained VLMs for trait discovery from biological images. VLM4Bio consists of images of three taxonomic groups of organisms: fish, birds, and butterflies, each containing around 10k images.
+- **Repository:** [VLM4Bio GitHub](https://github.com/Imageomics/VLM4Bio)
+- **Paper:** [arXiv](https://arxiv.org/pdf/2408.16176)
+
### Dataset Description
VLM4Bio is a large, annotated dataset, consisting of 469K question-answer pairs involving around 30K images from three groups of organisms: fish, birds, and butterflies, covering five biologically relevant tasks.
The scientifically relevant tasks in organismal biology includes species classification, trait identification, trait grounding, trait referring, and trait counting.
@@ -76,33 +110,143 @@ The following table demonstrates the leaderboard of the VLM baselines in terms o
English, Latin
## Dataset Structure
+After downloading and processing the dataset, VLM4Bio should have the following structure:
-**Instructions for downloading the dataset**
+```
+VLM4Bio/
+ └── datasets/
+ ├── Fish/
+ │ ├── images/
+ │ │ ├── INHS_FISH_58870.jpg
+ │ │ ├── INHS_FISH_58819.jpg
+ │ │ └── ...
+ │ └── metadata/
+ │ ├── metadata_10k.csv
+ │ ├── metadata_500.csv
+ │ └── ...
+ ├── Bird/
+ │ ├── images/
+ │ │ ├── Ivory_Gull_0117_49227.jpg
+ │ │ ├── Yellow_Warbler_0026_176337.jpg
+ │ │ └── ...
+ │ └── metadata/
+ │ ├── bird_metadata_10k.csv
+ │ ├── identification.csv
+ │ └── ...
+ └── Butterfly/
+ ├── images/
+ │ ├── butterfly_train_heliconius_sara_0007.jpg
+ │ ├── butterfly_val_pyrrhogyra_cramen_0001.jpg
+ │ └── ...
+ └── metadata/
+ ├── metadata.csv
+ └── imagelist.csv
+```
### Data Instances
+
+
### Data Fields
+**Fish Files:**
+- `identification_imagelist_10k.txt`:
+- `identification_matrix.csv`:
+- `imagelist_10k.txt`: List of image filenames for species classification and trait identification.
+- `imagelist_500.txt`: 500 image subset of `imagelist_10k.txt` for trait detection and counting.
+- `metadata_10k.csv`: Image filenames (`fileNameAsDelivered`, unique identifier) paired with their respective scientific names (`scientificName`).
+- `metadata_500.csv`: 500 image subset of `metadata_10k.csv` for trait detection and counting. `ARKID` is unique identifier from Fish-AIR, links to full metadata information in `full_fish_metadata.csv`.
+- `processed_identification_imagelist_10k.txt`: List of images included in the `processed_identification_matrix.csv`.
+- `processed_identification_matrix.csv`: Presence/Absence indicator for 10 external (visible) traits: `eye`, `head`, `mouth`, `barbel`, `dorsal fin`, `two dorsal fins`, `adipose fin`, `pectoral fin`, `pelvic fin`, `anal fin`. Unique identifier is the `fileNameAsDelivered`, and scientific name is indicated (`scientificName`).
+
+**Bird Files:**
+- `bird_imagelist_10k.txt`: List of image filenames for species classification and trait identification.
+- `bird_metadata_10k.csv`: Image filenames (`fileNameAsDelivered`, unique identifier) paired with their respective scientific names (`scientificName`).
+- `identification.csv`:
+- `processed_identification.csv`:
+- `trait_category_map.pkl`:
+
+**Butterfly Files:**
+- `imagelist.txt`: List of image filenames for species classification.
+- `metadata.csv`: Image filenames (`fileNameAsDelivered`, unique identifier) paired with their respective scientific names (`scientificName`).
+
+VLM Prompts are determined through code available in the [GitHub Repository](https://github.com/Imageomics/VLM4Bio); they are summarized in the task diagram above.
+
### Data Splits
+These images were all used for benchmarking current state-of-the-art VLMs on biological tasks.
+
### Curation Rationale
+
-### Source Data
-#### Data Collection and Processing
+### Source Data
We collected images of three taxonomic groups of organisms: fish, birds, and butterflies, each containing around 10k images.
-Images for fish (Fish-10k) were curated from the larger image collection, FishAIR, which contains images from the Great Lakes Invasive Network Project (GLIN) and Integrated Digitized Biocollections (iDigBio).
-These images originate from various museum collections such as INHS, FMNH, OSUM, JFBM, UMMZ and UWZM. We created the Fish-10k dataset by randomly sampling 10K images and preprocessing the images to crop and remove the background. For consistency, we leverage GroundingDINO to crop the fish body from the background and Segment Anything Model (SAM) to remove the background.
-We curated the images for butterflies (Butterfly-10k) from the Jiggins Heliconius Collection dataset, which has images collected from various sources.
-We carefully sampled 10K images for Butterfly-10K from the entire collection to ensure the images capture unique specimens and represent a diverse set of species by adopting the following two steps. First, we filter out images with more than one image from the same view (i.e., dorsal or ventral).
-Second, we ensure each species has a minimum of 20 images and no more than 2,000 images. The images for birds (Bird-10k) are obtained from the CUB-200-2011 dataset by taking 190 species for which the common name to scientific name mapping is available. This results in a fairly balanced dataset with around 11K images in total.
+
+#### Fish
+
+Images for fish (Fish-10k) were curated from the larger image collection, [Fish-AIR](https://fishair.org/), which contains images from the [Great Lakes Invasives Network (GLIN)](https://greatlakesinvasives.org/portal/index.php) and [Integrated Digitized Biocollections (iDigBio)](https://www.idigbio.org/).
+
+These images originate from various museum collections, including the following:
+
+- [Illinois Natural History Survey (INHS)](https://biocoll.inhs.illinois.edu/portal/index.php)
+- [Minnesota Biodiversity Atlas, Bell Museum](https://bellatlas.umn.edu/index.php)
+- [University of Michigan Museum of Zoology (UMMZ), Division of Fishes](https://ipt.lsa.umich.edu/resource?r=ummz\_fish)
+- [University of Wisconsin-Madison Zoological Museum - Fish](http://zoology.wisc.edu/uwzm/)
+- [Field Museum of Natural History (Zoology, FMNH) Fish Collection](https://fmipt.fieldmuseum.org/ipt/resource?r=fmnh_fishes)
+- [The Ohio State University Fish Division, Museum of Biological Diversity (OSUM), Occurrence dataset](https://doi.org/10.15468/subsl8)
+
+[Phenoscape](https://kb.phenoscape.org/about/phenoscape/kb) and [FishBase](https://www.fishbase.se/search.php) were used to obtain the information on traits.
+
+- **Data Processing:**
+
+ We created the Fish-10k dataset by randomly sampling 10K images and preprocessing the images to crop and remove the background. For consistency, we leverage [GroundingDINO](https://arxiv.org/abs/2303.05499) to crop the fish body from the background and [Segment Anything Model (SAM)](https://arxiv.org/abs/2304.02643) to remove the background.
+ This is the same processing done in [Fish-Vista](https://huggingface.co/datasets/imageomics/fish-vista), more details and the code is available [here](https://github.com/sajeedmehrab/Fish-Vista/tree/main/code/processing).
+
+
+#### Bird
+
+We create the Bird-10k dataset from the [CUB-200-2011 dataset](https://www.vision.caltech.edu/datasets/cub_200_2011/). We obtain the scientific names from the [iNatLoc dataset](https://data.caltech.edu/records/ts54e-1jr46).
+
+- **Data Processing:**
+
+ For Bird-10k, we take 190 species for which the common name to scientific name mapping is available. This results in a fairly balanced dataset. Please download the images following the directions under [Dataset Structure](#dataset-structure).
+
+
+#### Butterflies
+
+We created the Butterfly-10k dataset from the [Heliconius Collection (Cambridege Butterfly) dataset](https://huggingface.co/datasets/imageomics/Heliconius-Collection_Cambridge-Butterfly).
+
+- **Data Processing:**
+
+ For the Butterfly-10k, we carefully sampled 10K images from the Heliconius Collection dataset to ensure the images capture unique specimens and represent a diverse set of species. We adopt the following steps:
+
+ - We filter out images with more than one image from the same view (i.e., dorsal or ventral).
+ - We ensure each species has a minimum of 20 images and no more than 2,000 images.
+
### Annotations
-The scientific names for the images of Fish-10k and Butterfly-10k were obtained directly from their respective sources.
-For Bird-10k, we obtained the scientific names from the iNatLoc500 dataset. We curated around 31K question-answer pairs in both open and multiple-choice (MC) question-formats for evaluating species classification tasks.
-The species-level trait presence/absence matrix for Fish-10k was manually curated with the help of biological experts co-authored in this paper. We leveraged the Phenoscape knowledge base with manual annotations to procure the presence-absence trait matrix.
-For Bird-10k, we obtained the trait matrix from the attribute annotations provided along with CUB-200-2011. We constructed approximately 380K question-answer pairs for trait identification tasks.
+
+##### Scientific Names
+The scientific names for the images of **Fish-10k** and **Butterfly-10k** were obtained directly from their respective sources.
+
+For **Bird-10k**, we obtained the scientific names from the [iNatLoc dataset](https://data.caltech.edu/records/ts54e-1jr46).
+
+In total, we curated around 31K question-answer pairs in both open and multiple-choice (MC) question-formats for evaluating species classification tasks.
+
+##### Trait information
+The species-level trait presence/absence matrix for Fish-10k was manually curated with the help of biological experts co-authored in this paper. We leveraged the [Phenoscape knowledge base](https://kb.phenoscape.org/about/phenoscape/kb) and [FishBase](https://www.fishbase.se/search.php) along with manual annotations to procure the presence-absence trait information. We constructed approximately xK question-answer pairs for Fish-10k
+
+For Bird-10k, we obtained the trait matrix from the attribute annotations provided along with CUB-200-2011.
+
+In total, we constructed approximately 380K question-answer pairs for trait identification tasks.
+
+##### Grounding and referring
For grounding and referring VQA tasks, the ground truths were manually annotated with the help of expert biologists on our team. We manually annotated bounding boxes corresponding to the traits of 500 fish specimens and 500 bird specimens, which are subsets of the larger Fish-10k and Bird-10k datasets, respectively.
We used the CVAT tool for annotation.
@@ -114,14 +258,20 @@ None
The fish-10 K and Butterfly-10K datasets are not balanced for the species classification task, while the bird-10 K dataset is balanced. Since the fish images are collected from different museums, they may inherit a small bias.
-## Licensing Information
-The data (images) contain a variety of licensing restrictions ranging from [CC0](https://creativecommons.org/publicdomain/zero/1.0/) to [CC BY-NC](https://creativecommons.org/licenses/by-nc/4.0/). Each image in this dataset is provided under the least restrictive terms allowed by its licensing requirements as provided to us (i.e., we impose no additional restrictions past those specified by licenses in the license file).
+## Licensing Information
+
+This dataset (the compilation) has been licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0). However, images may be licensed under different terms (as noted above). For license and citation information by image, see our [license file](https://huggingface.co/datasets/sammarfy/VLM4Bio/blob/main/licenses.csv).
-This dataset (the compilation) has been licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0). However, images may be licensed under different terms (as noted above). For license and citation information by image, see our [license file](https://huggingface.co/datasets/sammarfy/VLM4Bio/blob/main/licenses.csv)