aww_solver.py

import time 
import sys
import os

import numpy as np

from keras.models import load_model
from keras.preprocessing import image

data_path = "../data/"
picture_path = data_path + "{}.jpg"

CLASSES = [1, 0]

def run(model_path):
	pictures_names = os.listdir(data_path)
	pic_num = len(pictures_names)	

	model = load_model(model_path)
		
	res = []
	for pic in range(pic_num):
		img = image.load_img(picture_path.format(pic), target_size=(224,224))
		x = image.img_to_array(img)
		x = np.expand_dims(x, axis=0)
		preds = model.predict(x)
		
		y_classes = preds.argmax(axis=-1)
		res.append(CLASSES[y_classes[0]])
	
	res = ''.join(map(str, res))

	n = int("0b" + res, 2)
	text = n.to_bytes((n.bit_length() + 7) // 8, 'big').decode()
	
	print(text)


if __name__ == '__main__':
	if len(sys.argv) < 2:
		print("path to the model expected")
		exit(1)

	run(sys.argv[1])