#-*- coding: utf-8 -*-

from keras.applications.resnet50 import preprocess_input

import numpy as np

import cv2

from src.model_builder import CamModelBuilder

from src.utils import plot_img, list_files

if __name__ == "__main__":

detector = CamModelBuilder().get_cam_model()

detector.load_weights("weights.h5", by_name=True)

detector.summary()

imgs = list_files("dataset//train//text")

for i, img_path in enumerate(imgs):

original_img = cv2.cvtColor(cv2.imread(img_path), cv2.COLOR_BGR2RGB)

img = cv2.resize(original_img, (224, 224))

img = np.expand_dims(img, 0).astype(np.float64)

cam_map = detector.predict(preprocess_input(img))

cam_map = cam_map[0, :, :, 1]

cam_map = cv2.resize(cam_map, (original_img.shape[1], original_img.shape[0]))

plot_img(original_img, cam_map, show=False, save_filename="{}.png".format(i+1))