ResNetPredict.py

# importing all required package library
from keras.applications import ResNet50
from keras.preprocessing.image import img_to_array
from keras.applications import imagenet_utils
import numpy as np


# A class for image prediction based on ResNet pre-trained model
class ResNetPredict:
    def __init__(self):
        self.image = None
        self.model = None
        self.result_value = None

    def load_model(self):
        self.model = ResNet50(weights="imagenet")

    def prepare_image(self, image, target):
        if image.mode != "RGB":
            image = image.convert("RGB")
        image = image.resize(target)
        image = img_to_array(image)
        image = np.expand_dims(image, axis=0)
        image = imagenet_utils.preprocess_input(image)
        return image

    def predict(self, image):
        prediction = self.model.predict(image)
        results = imagenet_utils.decode_predictions(prediction)
        return results