R: A Collection of ML Tools for Species Detection and Classification in Camera Trap Images and Videos

# A Collection of ML Tools for Species Detection and Classification in Camera Trap Images and Videos

## Documentation for package ‘animl’ version 3.3.1

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

active_times | Get start and stop dates for each camera folder.
animl_install | Load animl-py if available
animl_install_instructions | Installation Instructions for animl-r Python dependencies
build_file_manifest | File Management Module
check_animl_py | Check if animl-py can connect to exiftool and CUDA
check_file | Check for files existence and prompt user if they want to load
check_python | Check that the python version is compatible with the current version of animl-py
classify | Infer Species for Given Detections
compute_batched_distance_matrix | Computes the distance matrix in a batched manner to save memory.
compute_distance_matrix | A wrapper function for computing distance matrix.
cosine_distance | Computes cosine distance of two sets of matrices
create_pyenv | Install python if necessary and create the environment animl_env
delete_pyenv | Delete the animl_env environment
detect | Apply MegaDetector to a Given Batch of Images
download_model | Download specified model to the given directory.
euclidean_squared_distance | Computes euclidean squared distance of two sets of matrices
export_camptrapdp | Export a manifest to camtrapdp format
export_camtrapR | Export data into sorted folders organized by station
export_coco | Converts the .csv file to a COCO-formatted .json file.
export_folders | Create SymLink Directories and Sort Classified Images
export_megadetector | Converts the .csv file to the MD-formatted .json file.
export_timelapse | Converts the Manifests to a csv file that contains columns needed for TimeLapse conversion in later step
export_train_val_test | Splits the manifest into training validation and test datasets for training
export_yolo | Export a manifest to YOLO format for model training
extract_frames | Extract frames from video for classification
extract_major_minor | Compare to Animl-Py version, ignoring patch number
extract_miew_embeddings | Extract Embeddings from MiewID
get_animals | Return a dataframe of only MD animals
get_empty | Return MD empty, vehicle and human images in a dataframe
get_frame_as_image | Given a video path, return a specific frame as an RGB image
list_models | List available models for download.
load_animl | Load animl-py if available
load_classifier | Load a Classifier Model and Class_list
load_class_list | Load class list .csv file
load_data | Load .csv or .Rdata file
load_detector | Load an Object Detector
load_json | Load data from a JSON file.
load_miew | Load MiewID model
load_yaml | Load data from a YAML file.
parse_detections | Parse MD results into a simple dataframe
plot_all_bounding_boxes | Plot all bounding boxes in a manifest
plot_box | Plot bounding boxes on image from md results
remove_diagonal | Removes the diagonal elements from a square matrix.
remove_link | Remove Sorted Links
save_classifier | Save model state weights
save_data | Save Data to Given File
save_json | Save data to a JSON file.
save_yaml | Save data to a YAML file
sequence_calculation | Calculate sequence from timestamps
sequence_classification | Leverage sequences to classify images
single_classification | Get Maximum likelihood label for each Detection
test_classifier | Test a model with a Config file
train_classifier | Model Training
update_animl_py | Update animl-py version for the given environment
update_labels_from_folders | Udate Results from File Browser
WorkingDirectory | Set Working Directory and Save File Global Variables