quick2.py

import numpy as np 
import loader

train_features, train_labels, test_features, test_labels = loader.load_images('TrainImages')
train_features = np.reshape(train_features,(500, 4000))
train_labels = np.reshape(train_labels, (500, 2))
test_features = np.reshape(test_features, (550, 4000))
test_labels = np.reshape(test_labels, (550, 2))

train_data = zip(train_features, train_labels)
test_data = zip(test_features, test_labels)

def get_index(labels):
	if labels[0] == 1: return 0 
	else: return 1

def l1_distance(img1, img2):
	return np.sum(np.abs(img1.ravel() - img2.ravel()))

def nearest_neighbor(img):
	all_dists = {l1_distance(img, each[0]):get_index(each[1]) for each in train_data} 
	return min(all_dists), all_dists[min(all_dists)] # ValueErro: min(arg), arg is an empty sequence error

def run_model(test):
	classification = []
	for entry in test:
		label = nearest_neighbor(entry[0])
		classification.append((label[1], entry[1]))
	return sum(i == j for i, j in classification)

result = run_model(test_data)
print(result)