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retrieval_ebay.py
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retrieval_ebay.py
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import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
import scipy.io
import random
import time
image_path = 'data/ebay/Stanfor_Online_Products/'
file_object = open('data/ebay/Ebay_test.txt')
try:
all_the_text = file_object.read().split()
finally:
file_object.close()
image_names = []
image_labels = {}
count = 1
for i,s in enumerate(all_the_text):
if((i+1)%4==0):
image_names.append(s)
if((i+1)%4==2):
if (int(s)-11318) not in image_labels.keys():
l = []
l.append(count)
image_labels[int(s)-11318] = l
else:
image_labels[int(s)-11318].append(count)
count += 1
features = scipy.io.loadmat('embeddings/ebay/embed128_multiloss_with_hsv.mat')
features = features['fc_embedding_cls'][:len(image_names)]
fd = np.zeros((features.shape[0],features.shape[1])).astype('float')
retrive_result = []
show_num_images = 30
seq = [i for i in range(len(image_names))]
img_id = random.sample(seq,show_num_images)
start = time.time()
for i,f in enumerate(img_id):
for j in range(len(image_names)):
fd[j,:] = features[f]
idx = np.argsort(np.sqrt(np.sum(np.square(fd - features),axis=1)))
retrive_result.append(idx[:show_num_images]+1)
if(i==show_num_images):
break
elapsed = time.time()-start
print 'avg-time:{}ms'.format(elapsed*1000/show_num_images)
image_width = 200
read_rect = int(image_width/20)
merged_width = int(np.ceil((show_num_images)*image_width))
merged_image = np.zeros((merged_width,merged_width,3),dtype='uint8')+255
for counter1,index1 in enumerate(retrive_result):
st = 0
for i, d in enumerate(image_labels.keys()):
for j, q in enumerate(image_labels[d]):
if q == img_id[counter1]+1:
st = d
break
if st > 0:
break
for counter2,index2 in enumerate(retrive_result[counter1]):
image_address = image_path+image_names[retrive_result[counter1][counter2]-1]
img = np.asarray(Image.open(image_address).resize((image_width,image_width)))
a = int(np.ceil(counter1 * image_width))
b = int(np.ceil(counter2 * image_width))
if img.ndim==3:
merged_image[a:a+image_width,b:b+image_width,:] = img[:,:,:3]
flag = False
for i, d in enumerate(image_labels[st]):
if(retrive_result[counter1][counter2] == d and counter2 >= 0):
merged_image[a:a+read_rect,b:b+image_width,0] = 255
merged_image[a:a+image_width,b:b+read_rect, 0] = 255
merged_image[a+image_width-read_rect:a+image_width,b:b+image_width, 0] = 255
merged_image[a:a+image_width,b+image_width-read_rect:b+image_width, 0] = 255
merged_image[a:a + read_rect, b:b + image_width, 1:] = 0
merged_image[a:a + image_width, b:b + read_rect, 1:] = 0
merged_image[a + image_width - read_rect:a + image_width, b:b + image_width, 1:] = 0
merged_image[a:a + image_width, b + image_width - read_rect:b + image_width, 1:] = 0
flag = True
break
if (not flag):
merged_image[a:a + read_rect, b:b + image_width, 1] = 255
merged_image[a:a + image_width, b:b + read_rect, 1] = 255
merged_image[a + image_width - read_rect:a + image_width, b:b + image_width, 1] = 255
merged_image[a:a + image_width, b + image_width - read_rect:b + image_width, 1] = 255
merged_image[a:a + read_rect, b:b + image_width, 0] = 0
merged_image[a:a + image_width, b:b + read_rect, 0] = 0
merged_image[a + image_width - read_rect:a + image_width, b:b + image_width, 0] = 0
merged_image[a:a + image_width, b + image_width - read_rect:b + image_width, 0] = 0
merged_image[a:a + read_rect, b:b + image_width, 2] = 0
merged_image[a:a + image_width, b:b + read_rect, 2] = 0
merged_image[a + image_width - read_rect:a + image_width, b:b + image_width, 2] = 0
merged_image[a:a + image_width, b + image_width - read_rect:b + image_width, 2] = 0
plt.imshow(merged_image)
plt.show()
merged_image = Image.fromarray(merged_image)
merged_image.save('vis-result/ebay/retrieval_embed128-multiloss-with-hsv.png')