CameraTrapDetectoR Family Model

This dataset contains the model weights, architecture, and class label dictionary for CameraTrapDetectoR family model version 1. The model architecture is a FasterRCNN object detection model with a ResNet50 backbone. This model identifies and counts animals from 33 North American taxonomic families in camera trap images, including humans vehicles and a background class. Additional information about the R package and the training data can be found in the package's Github repository: https://github.com/CameraTrapDetectoR/CameraTrapDetectoR

Resources in this dataset:

• family_v1.zip is a folder containing the model architecture, model weights, and class label dictionary required to deploy the first generation family model in CameraTrapDetectoR

• family_v2.zip is a folder containing the model architecture, model weights, and class label dictionary required to deploy the family model version 2 in CameraTrapDetectoR

• family_v2_cl.zip is a folder containing the all information to deploy the family v2 model via Python script from the command line. Full instructions for set up and use may be found at https://github.com/CameraTrapDetectoR/model_training