Model_maker_training¶
- class Model_maker_training.DataLoader(csv_file_path, images_dir)¶
- load_data()¶
Loads data from the csv file. :param csv_file_path: The file path to the csv file. :param images_dir: The directory that contains images.
Returns: A Dataloader containing the data of training, validation and test set
- class Model_maker_training.ModelTrainer(train_data, validation_data)¶
A class to train the model on the given dataset and evaluate it.
- train_data¶
Training dataset, in the form of Dataloader.
- validation_data¶
Validation dataset, in the form of Dataloader.
- eval¶
The evaluation result.
- model¶
The trained model.
- train_model()¶
Fine tunes the EfficientDet-Lite0 model on the given dataset.
- Parameters:
train_data – Training dataset, in the form of Dataloader.
validation_data – Validation dataset, in the form of Dataloader.
- Returns:
A trained model.
- evaluate_and_export(test_data)¶
Evaluates the model and exports it to the export directory.
- Parameters:
test_data – Test dataset, in the form of Dataloader.
- class Model_maker_training.ObjectDetector(model, model_path, classes)¶
A class to perform object detection with a given model.
- model¶
The trained model.
- model_path¶
The file path to the trained model.
- classes¶
A list of class labels.
- colors¶
A list of colors for visualization.
- interpreter¶
The TensorFlow Lite interpreter.
- preprocess_image(image_path, input_size)¶
- detect_objects(image, threshold=0.5)¶
- run_odt_and_draw_results(image_path, interpreter, threshold=0.5)¶
Run object detection on the input image and draw the results.
- Parameters:
image_path – The file path to the input image.
interpreter – The TensorFlow Lite interpreter.
threshold – The minimum confidence score for detected objects.
- Returns:
A NumPy array of the input image with the detection results.