inference.py

import matplotlib.pyplot as plt
import numpy as np
import os
import cv2
from keras.optimizers import Adam
from segmentation_models.losses import bce_dice_loss
from segmentation_models.metrics import dice_score, jaccard_score
from keras.models import model_from_json

HEIGHT, WIDTH, DEPTH = 224, 224, 3

if __name__ == '__main__':
    json = 'models/linknet_layers_3_classes.json'
    weight = 'models/linknet_layers_3_classes.h5'

    json = open(json, 'r')

    model = model_from_json(json.read())
    model.load_weights(weight)

    model.compile(optimizer=Adam(1e-3), loss=bce_dice_loss, metrics=[dice_score, jaccard_score])

    model.summary()

    image = cv2.imread('161.jpg', cv2.IMREAD_UNCHANGED)
    original = cv2.resize(image, (HEIGHT, WIDTH))
    image = original.reshape(1, HEIGHT, WIDTH, DEPTH)

    predict = model.predict(image)

    fig, axes = plt.subplots(2, 2)
    axes[0, 0].imshow(original)
    axes[0, 1].imshow(predict[0, :, :, 0])
    axes[1, 0].imshow(predict[0, :, :, 1])
    axes[1, 1].imshow(predict[0, :, :, 2])
    plt.show()