This library provides a simple interface for image classification using TensorFlow Lite models. It's designed to work with pre-trained models and can process both single images and directories of images.
pip install imBroker- Single image classification
- Batch classification for directories
- Support for custom TFLite models
- Handles any type of image shapes
from imBroker import tflBroker
# Define your TFlite model's path
model_path = "path/to/your/model.tflite"
# Define your output labels
output_labels = {
0: 'Label 1',
1: 'Label 2',
...
}
# Initialize the broker
broker = tflBroker(model_path, output_labels)result = broker.predict_single_image("path/to/image.jpg")
print(result)results = broker.predict_image_directory("path/to/image/directory")
print(results)