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This file is used to extract features from dataset and save it on disc

inputs:

outputs:

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import os import random

import numpy as np import tensorflow as tf

Just disables the warning, doesn't enable AVX/FMA

os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' import pickle

os._warn_preinit_stderr = 0

BOTTLENECK_TENSOR_NAME = 'pool_3/_reshape:0' BOTTLENECK_TENSOR_SIZE = 2048 MODEL_INPUT_WIDTH = 299 MODEL_INPUT_HEIGHT = 299 MODEL_INPUT_DEPTH = 3 JPEG_DATA_TENSOR_NAME = 'DecodeJpeg/contents:0' RESIZED_INPUT_TENSOR_NAME = 'ResizeBilinear:0' MAX_NUM_IMAGES_PER_CLASS = 2 ** 27 - 1 # ~134M

def create_inception_graph(): """"Creates a graph from saved GraphDef file and returns a Graph object.

Returns: Graph holding the trained Inception network, and various tensors we'll be manipulating. """ with tf.compat.v1.Session() as sess: model_filename = os.path.join( 'imagenet', 'classify_image_graph_def.pb') with tf.gfile.FastGFile("imagenet/classify_image_graph_def.pb", 'rb') as f: graph_def = tf.compat.v1.GraphDef() graph_def.ParseFromString(f.read()) bottleneck_tensor, jpeg_data_tensor, resized_input_tensor = ( tf.import_graph_def(graph_def, name='', return_elements=[ BOTTLENECK_TENSOR_NAME, JPEG_DATA_TENSOR_NAME, RESIZED_INPUT_TENSOR_NAME])) return sess.graph, bottleneck_tensor, jpeg_data_tensor, resized_input_tensor

def run_bottleneck_on_image(sess, image_data, image_data_tensor, bottleneck_tensor): bottleneck_values = sess.run( bottleneck_tensor, {image_data_tensor: image_data}) bottleneck_values = np.squeeze(bottleneck_values) return bottleneck_values

Get outputs from second-to-last layer in pre-built model

boots_files = [ 'uploads/dogs_and_cats/Boots/' + f for f in os.listdir('uploads/dogs_and_cats/Boots') ] sandals_files = [ 'uploads/dogs_and_cats/Sandals/' + f for f in os.listdir('uploads/dogs_and_cats/Sandals') ] shoes_files = [ 'uploads/dogs_and_cats/Shoes/' + f for f in os.listdir('uploads/dogs_and_cats/Shoes') ] slippers_files = [ 'uploads/dogs_and_cats/Slippers/' + f for f in os.listdir('uploads/dogs_and_cats/Slippers') ] apparel_files = [ 'uploads/dogs_and_cats/apparel/' + f for f in os.listdir('uploads/dogs_and_cats/apparel') ]

all_files = boots_files + shoes_files + slippers_files + sandals_files + apparel_files

random.shuffle(all_files)

num_images = 10000 neighbor_list = all_files[:num_images] with open('neighbor_list_recom.pickle', 'wb') as f: pickle.dump(neighbor_list, f) print("saved neighbour list")

extracted_features = np.ndarray((num_images, 2048)) sess = tf.compat.v1.Session() graph, bottleneck_tensor, jpeg_data_tensor, resized_image_tensor = (create_inception_graph())

for i, filename in enumerate(neighbor_list):

image_data = tf.io.gfile.GFile(filename, 'rb').read()
features = run_bottleneck_on_image(sess, image_data, jpeg_data_tensor, bottleneck_tensor)

extracted_features[i:i + 1] = features

if i % 250 == 0:
    print(i)

np.savetxt("saved_features_recom.txt", extracted_features) print("saved exttracted features")

========== Output Error

"C:\Users\Muhammad Khalid\Anaconda3\python.exe" "C:/Users/Muhammad Khalid/Desktop/Recommendation systems using image similarity powered by deep learning/Deeplearning_Image_Similarity-master/server/image_vectorizer.py"

WARNING: Logging before flag parsing goes to stderr. W0823 21:18:45.101209 20020 init.py:308] Limited tf.compat.v2.summary API due to missing TensorBoard installation. saved neighbour list

W0823 21:18:45.223723 20020 deprecation.py:323] From C:/Users/Muhammad Khalid/Desktop/Recommendation systems using image similarity powered by deep learning/Deeplearning_Image_Similarity-master/server/image_vectorizer.py:39: FastGFile.init (from tensorflow.python.platform.gfile) is deprecated and will be removed in a future version. Instructions for updating: Use tf.gfile.GFile.

Traceback (most recent call last): File "C:/Users/Muhammad Khalid/Desktop/Recommendation systems using image similarity powered by deep learning/Deeplearning_Image_Similarity-master/server/image_vectorizer.py", line 113, in image_data = tf.io.gfile.GFile(filename, 'rb').read()

File "C:\Users\Muhammad Khalid\Anaconda3\lib\site-packages\tensorflow\python\lib\io\file_io.py", line 122, in read self._preread_check()

File "C:\Users\Muhammad Khalid\Anaconda3\lib\site-packages\tensorflow\python\lib\io\file_io.py", line 84, in _preread_check compat.as_bytes(self.__name), 1024 * 512)

tensorflow.python.framework.errors_impl.UnknownError: NewRandomAccessFile failed to Create/Open: uploads/dogs_and_cats/Sandals/Athletic : Access is denied. ; Input/output error

Process finished with exit code 1

vinayakarannil / Deeplearning_Image_Similarity