Cloth Parsing¶
In [ ]:
from scipy.io import loadmat
from matplotlib import pyplot as plt
import numpy as np
from os.path import basename
import shutil
import random
import os
import h5py
from PIL import Image
import pandas as pd
from glob import glob
import pickle
!apt install -y caffe-cuda
!pip install pydensecrf
import caffe
from pydensecrf import densecrf as dcrf
from pydensecrf.utils import compute_unary, create_pairwise_bilateral, create_pairwise_gaussian, softmax_to_unary
import skimage.io as io
import warnings
warnings.filterwarnings('ignore')
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!git clone https://github.com/bearpaw/clothing-co-parsing.git
data_path = '/content/clothing-co-parsing/'
Cloning into 'clothing-co-parsing'... remote: Enumerating objects: 4234, done. remote: Total 4234 (delta 0), reused 0 (delta 0), pack-reused 4234 Receiving objects: 100% (4234/4234), 124.59 MiB | 12.20 MiB/s, done. Resolving deltas: 100% (1100/1100), done.
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loadmat(data_path+'annotations/pixel-level/0001.mat')
Out[ ]:
{'__globals__': [],
'__header__': b'MATLAB 5.0 MAT-file, Platform: PCWIN64, Created on: Tue Aug 19 15:20:27 2014',
'__version__': '1.0',
'groundtruth': array([[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
...,
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0]], dtype=uint8)}
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plt.figure(figsize=(12, 8))
plt.subplot(1, 2, 1)
img1 = Image.open(data_path+'photos/0001.jpg')
plt.imshow(img1)
plt.subplot(1, 2, 2)
mask1 = loadmat(data_path+'annotations/pixel-level/0001.mat')['groundtruth']
plt.imshow(mask1)
plt.show()
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# reading names of categories in the ccp dataset and saving it as csv
labels = loadmat(data_path+'label_list.mat')
ccp_categories = []
for i in labels['label_list'][0]:
ccp_categories.append(str(i[0]))
color_map = pd.Series(ccp_categories)
color_map
Out[ ]:
0 null 1 accessories 2 bag 3 belt 4 blazer 5 blouse 6 bodysuit 7 boots 8 bra 9 bracelet 10 cape 11 cardigan 12 clogs 13 coat 14 dress 15 earrings 16 flats 17 glasses 18 gloves 19 hair 20 hat 21 heels 22 hoodie 23 intimate 24 jacket 25 jeans 26 jumper 27 leggings 28 loafers 29 necklace 30 panties 31 pants 32 pumps 33 purse 34 ring 35 romper 36 sandals 37 scarf 38 shirt 39 shoes 40 shorts 41 skin 42 skirt 43 sneakers 44 socks 45 stockings 46 suit 47 sunglasses 48 sweater 49 sweatshirt 50 swimwear 51 t-shirt 52 tie 53 tights 54 top 55 vest 56 wallet 57 watch 58 wedges dtype: object