# Import required libraries. print("Loading the required Python modules ...\n") import os import cv2 as cv import glob from utils import get_predict_api, plot_bw_color_comparison, IMG_PATH # Load model print("Loading the model ...") predict, _ = get_predict_api() cwd = os.getcwd() print("Demonstrate colorization using images found in\n", os.path.join(cwd, IMG_PATH), "\n") print("Please close each image (Ctrl-w) to proceed through the demonstration.\n") if __name__ == '__main__': image_folder = 'images' images = glob.glob(os.path.join(IMG_PATH, "*_bw.png")) images.sort() for image in images: print("Colorize " + os.path.basename(image)) gray = cv.imread(image, 0) out = predict(gray) plot_bw_color_comparison(gray, cv.cvtColor(out, cv.COLOR_BGR2RGB))
print("Loading required Python modules ...") from keras.utils import plot_model import subprocess from utils import get_predict_api print("\nLoading model ...") graph_file = "cache/model_graph.png" _, model = get_predict_api() plot_model(model, to_file=graph_file) subprocess.Popen("xdg-open " + graph_file, shell=True, stderr=subprocess.PIPE)