ifcb_save_classification: Classify an IFCB Sample and Save Results

In iRfcb: Tools for Managing Imaging FlowCytobot (IFCB) Data

Classify an IFCB Sample and Save Results

Description

Extracts PNG images from an IFCB .roi file, classifies each image via the Gradio API predict_scores endpoint (returning all class scores), fetches per-class thresholds, and writes the results in the specified format.

Usage

ifcb_save_classification(
  roi_file,
  output_folder,
  format = c("h5", "mat", "csv"),
  gradio_url = "https://irfcb-classify.hf.space",
  model_name = "SMHI NIVA ResNet50 V5",
  verbose = TRUE,
  ...
)

Arguments

roi_file	A character string specifying the path to the .roi file.
output_folder	A character string specifying the directory where the output file will be saved. The file is named automatically based on the sample name (e.g. D20220522T003051_IFCB134_class.h5, D20220522T003051_IFCB134_class_v1.mat, or D20220522T003051_IFCB134.csv).
format	A character string specifying the output format. One of "h5" (default), "mat", or "csv".
gradio_url	A character string specifying the base URL of the Gradio application. Default is "https://irfcb-classify.hf.space", which is an example Hugging Face Space with limited resources intended for testing and demonstration. For large-scale classification, deploy your own instance of the classification app (source code: https://github.com/EuropeanIFCBGroup/ifcb-inference-app) and pass its URL here.
model_name	A character string specifying the name of the CNN model to use for classification. Default is "SMHI NIVA ResNet50 V5". Use ifcb_classify_models() to list all available models.
verbose	A logical value indicating whether to print progress messages. Default is TRUE.
...	Additional arguments passed to ifcb_extract_pngs() (e.g. ROInumbers, gamma).

Details

Three output formats are supported:

"h5"

IFCB Dashboard class_scores v3 HDF5 format. Contains output_scores, class_labels, roi_numbers (Dashboard-required), plus classifier_name, class_name, class_name_auto, and thresholds. Requires the hdf5r package.

"mat"

IFCB Dashboard class_scores v1 MATLAB format. Contains class2useTB, TBscores, roinum, TBclass, TBclass_above_threshold, and classifierName. Requires Python with scipy and numpy.

"csv"

ClassiPyR-compatible CSV format with columns file_name, class_name (threshold-applied), class_name_auto (winning class without threshold), and score (winning class confidence). See https://github.com/EuropeanIFCBGroup/ClassiPyR for details.

Value

The path to the saved file (invisibly).

See Also

ifcb_classify_images(), ifcb_classify_sample(), ifcb_classify_models()

Examples

## Not run: 
# Classify a sample and save as HDF5 (default)
ifcb_save_classification(
  "path/to/D20220522T003051_IFCB134.roi",
  output_folder = "output"
)

# Save as Dashboard v1 .mat format
ifcb_save_classification(
  "path/to/D20220522T003051_IFCB134.roi",
  output_folder = "output",
  format = "mat"
)

# Save as CSV
ifcb_save_classification(
  "path/to/D20220522T003051_IFCB134.roi",
  output_folder = "output",
  format = "csv"
)

## End(Not run)

iRfcb documentation built on March 1, 2026, 5:06 p.m.