Delete hw3(1).py

hw3 (1).py

@@ -1,62 +0,0 @@
-# -*- coding: utf-8 -*-
-"""HW3.ipynb
-
-Automatically generated by Colaboratory.
-
-Original file is located at
-    https://colab.research.google.com/drive/1H-R9L74rpYOoQJOnTLLbUpcNpd9Tty_D
-"""
-
-!wget http://vis-www.cs.umass.edu/lfw/lfw.tgz
-!tar -xvf /content/lfw.tgz
-import tensorflow as tf
-from sklearn.datasets import load_sample_image
-import os
-import tensorflow.keras.applications.resnet50 as resnet50
-from tensorflow.keras.applications.resnet50 import ResNet50, preprocess_input
-from tensorflow.keras.preprocessing.image import load_img, img_to_array
-import numpy as np
-from PIL import Image
-from sklearn.neighbors import NearestNeighbors
-
-directory = '/content/lfw'
-model = resnet50.ResNet50(weights='imagenet', include_top=False, pooling='avg')
-feature_dict = {}
-image_files = []
-target_size = (224, 224)
-i = 0
-
-# Sample at most 2000 images because the whole entire dataset 
-# costs too much cpu power and ram
-
-def preprocess_image(image_path, target_size):
-    img = load_img(os.path.join(directory,image_path),target_size=target_size)
-    x = img_to_array(img)
-    x = tf.expand_dims(x, axis = 0)
-    x = preprocess_input(x)
-    features = model.predict(x)
-    return features
-
-for dir in os.listdir(directory):
-    i += 1
-    new_dir = '/content/lfw/'+dir
-    if os.path.isdir(new_dir):
-        for files in os.listdir(new_dir):
-            feature_dict[new_dir+'/'+files] = preprocess_image(new_dir+'/'+files, target_size).flatten()
-    if i >= 100:
-        break
-
-for file, features in feature_dict.items():
-    print(file, features)
-
-feature_map = np.array(list(feature_dict.values()))
-
-NearNeigh = NearestNeighbors(n_neighbors=10,algorithm='auto').fit(feature_map)
-
-for image_path in feature_dict:
-  img = feature_dict[image_path].reshape(1,-1)
-  distance,indices = NearNeigh.kneighbors(img)
-  print('Similar images for', image_path)
-  for i, index in enumerate(indices[0]):
-    similar_img_path = list(feature_dict.keys())[index]
-    print(i+1,similar_img_path)