Image Classification as Model Training and Model Evaluation to Identify and Classify the Protozoan Trypanosome Species

To begin, navigate to the plugin toolbar. Then drag and drop the EvaluateClassif function onto the screen. Click on the evaluate button located within the EvaluateClassif tool.

Click the load folder image button to import test images, and load config to import the trained weight file from the directory. Then click the start button to evaluate the classification model. After evaluation, click the export to CSV button to save the results as a CSV file in the directory.

To evaluate data at every threshold, click on the start all threshold to save the CSV file in the directory with class names, including parameters such as recall, true positive rate, false positive rate, and precision for each class. To plot the receiver operating characteristics curve, click on the plot ROC button located within the EvaluateClassif tool. Click on the browse button and import the CSV files from the directory.

Inspect the imported class list and select each class label to plot the ROC curve. Next, to visualize the ROC curve, click on the plot button. Make any desired adjustments to the image properties, such as font size, font colors, rounding decimals, line styles, and line colors.

Finally, click the save button to save the ROC curve image with the AUC values in the required image format in the directory.