This data set was used to train tick models version B. It contains images of 2 tick types, Rhipicephalus and Hyalomma, as well as some control images of spiders and other objects. The accompanying models are here for review. Model Code. This version is different, there are 7 total classes. They include the positions of the images the ticks were taken at, either their centershot, headshot or cornershot.The dataset was really large to upload as one zip file. It is spread out into separate zip files. You need all the files to decompress them, ensure they are all in the same place and then let it decompress the images.The final folder structure should bedata/|___train/|___dev/|___test/ and inside each folder, there should be 7 folders for each subclass.

This data set was used to train tick models version B. It contains images of 2 tick types, Rhipicephalus and Hyalomma, as well as some control images of spiders and other objects. The accompanying models are here for review. Model Code. This version is different, there are 7 total classes. They include the positions of the images the ticks were taken at, either their centershot, headshot or cornershot.The dataset was really large to upload as one zip file. It is spread out into separate zip files. You need all the files to decompress them, ensure they are all in the same place and then let it decompress the images.The final folder structure should bedata/|___train/|___dev/|___test/ and inside each folder, there should be 7 folders for each subclass.

This dataset is the one used for training on the UTI classification app. It contains 3 subclasses for UTI and a UTI no UTI dataset. The ratio split is 65% for training, 25%  validation and 10% Testing. The zip files come as multiple parts, most unizipping software ( Keka Unzip MacOS ) will unzip the dataset as long as all parts are all together. By clicking any one of them, it will unzip.Structured without splitting and original datasets are available as well athttps://zenodo.org/records/17449974https://zenodo.org/records/17449876

This dataset is the one used for training on the UTI classification app. It contains 3 subclasses for UTI and a UTI no UTI dataset. The ratio split is 65% for training, 25%  validation and 10% Testing. The zip files come as multiple parts, most unizipping software ( Keka Unzip MacOS ) will unzip the dataset as long as all parts are all together. By clicking any one of them, it will unzip.Structured without splitting and original datasets are available as well athttps://zenodo.org/records/17449974https://zenodo.org/records/17449876

This data set was used to train tick models. It contains images of 2 tick types, Rhipicephalus and Hyalomma, as well as some control images of spiders and other objects. The total size of the images should be around 5.4GB. The accompanying models are here for review. Model CodeThe dataset was really large to upload as one zip file. It is spread out into separate zip files. You need all the files to decompress them, ensure they are all in the same place and then let it decompress the images.The final folder structure should bedata/|___train/|___dev/|___test/ Here is a link for decompression if you need some guidance https://www.toolfarm.com/knowledge-base/licensing/how-to-extract-multi-part-archive-files/

This data set was used to train tick models. It contains images of 2 tick types, Rhipicephalus and Hyalomma, as well as some control images of spiders and other objects. The total size of the images should be around 5.4GB. The accompanying models are here for review. Model CodeThe dataset was really large to upload as one zip file. It is spread out into separate zip files. You need all the files to decompress them, ensure they are all in the same place and then let it decompress the images.The final folder structure should bedata/|___train/|___dev/|___test/ Here is a link for decompression if you need some guidance https://www.toolfarm.com/knowledge-base/licensing/how-to-extract-multi-part-archive-files/