Justin Donaldson
commited on
Commit
•
fe3bafe
1
Parent(s):
5a04737
add code
Browse files- .gitattributes +1 -0
- .gitignore +2 -0
- Create Embedding Pickle.ipynb +2894 -0
- README.md +2 -0
- Scrape LV.ipynb +292 -0
- Untitled.ipynb +88 -0
- app.py +23 -15
- crawl_lv.py +117 -0
.gitattributes
CHANGED
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@@ -1 +1,2 @@
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| 1 |
unsplash-25k-photos-embeddings.pkl filter=lfs diff=lfs merge=lfs -text
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| 1 |
unsplash-25k-photos-embeddings.pkl filter=lfs diff=lfs merge=lfs -text
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+
lv-handbags.pkl filter=lfs diff=lfs merge=lfs -text
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.gitignore
CHANGED
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@@ -2,6 +2,8 @@
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| 2 |
__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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__pycache__/
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*.py[cod]
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*$py.class
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.DS_Store
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images/*.png
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# C extensions
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| 9 |
*.so
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Create Embedding Pickle.ipynb
ADDED
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@@ -0,0 +1,2894 @@
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|
| 1 |
+
{
|
| 2 |
+
"cells": [
|
| 3 |
+
{
|
| 4 |
+
"cell_type": "code",
|
| 5 |
+
"execution_count": 1,
|
| 6 |
+
"id": "ab9c916b",
|
| 7 |
+
"metadata": {},
|
| 8 |
+
"outputs": [],
|
| 9 |
+
"source": [
|
| 10 |
+
"import pickle\n",
|
| 11 |
+
"import json"
|
| 12 |
+
]
|
| 13 |
+
},
|
| 14 |
+
{
|
| 15 |
+
"cell_type": "code",
|
| 16 |
+
"execution_count": 2,
|
| 17 |
+
"id": "55716a60",
|
| 18 |
+
"metadata": {},
|
| 19 |
+
"outputs": [],
|
| 20 |
+
"source": [
|
| 21 |
+
"# emb = None\n",
|
| 22 |
+
"# with open(\"unsplash-25k-photos-embeddings.pkl\", 'rb') as f:\n",
|
| 23 |
+
"# emb = pickle.load(f)\n",
|
| 24 |
+
"# emb[1].shape "
|
| 25 |
+
]
|
| 26 |
+
},
|
| 27 |
+
{
|
| 28 |
+
"cell_type": "code",
|
| 29 |
+
"execution_count": 3,
|
| 30 |
+
"id": "efb5a6c2",
|
| 31 |
+
"metadata": {},
|
| 32 |
+
"outputs": [],
|
| 33 |
+
"source": [
|
| 34 |
+
"# emb = None\n",
|
| 35 |
+
"# with open(\"lv-handbags.pkl\", 'rb') as f:\n",
|
| 36 |
+
"# emb = pickle.load(f)\n",
|
| 37 |
+
"# emb[1].shape"
|
| 38 |
+
]
|
| 39 |
+
},
|
| 40 |
+
{
|
| 41 |
+
"cell_type": "code",
|
| 42 |
+
"execution_count": 4,
|
| 43 |
+
"id": "b5007694",
|
| 44 |
+
"metadata": {
|
| 45 |
+
"scrolled": true
|
| 46 |
+
},
|
| 47 |
+
"outputs": [
|
| 48 |
+
{
|
| 49 |
+
"name": "stdout",
|
| 50 |
+
"output_type": "stream",
|
| 51 |
+
"text": [
|
| 52 |
+
"nvprod4330126v.jpg\n",
|
| 53 |
+
"nvprod3400031v.jpg\n",
|
| 54 |
+
"nvprod4380096v.jpg\n",
|
| 55 |
+
"nvprod4320126v.jpg\n",
|
| 56 |
+
"nvprod2400130v.jpg\n",
|
| 57 |
+
"015577.jpg\n",
|
| 58 |
+
"nvprod2130120v.jpg\n",
|
| 59 |
+
"nvprod4460046v.jpg\n",
|
| 60 |
+
"nvprod4020036v.jpg\n",
|
| 61 |
+
"nvprod4240003v.jpg\n",
|
| 62 |
+
"009162.jpg\n",
|
| 63 |
+
"nvprod2350050v.jpg\n",
|
| 64 |
+
"nvprod4350048v.jpg\n",
|
| 65 |
+
"nvprod3440013v.jpg\n",
|
| 66 |
+
"nvprod4430121v.jpg\n",
|
| 67 |
+
"nvprod4340048v.jpg\n",
|
| 68 |
+
"nvprod2010027v.jpg\n",
|
| 69 |
+
"nvprod2750002v.jpg\n",
|
| 70 |
+
"nvprod2260012v.jpg\n",
|
| 71 |
+
"nvprod4370041v.jpg\n",
|
| 72 |
+
"nvprod4400082v.jpg\n",
|
| 73 |
+
"nvprod4060014v.jpg\n",
|
| 74 |
+
"nvprod2530037v.jpg\n",
|
| 75 |
+
"011261.jpg\n",
|
| 76 |
+
"nvprod4440018v.jpg\n",
|
| 77 |
+
"nvprod4140001v.jpg\n",
|
| 78 |
+
"nvprod3660116v.jpg\n",
|
| 79 |
+
"nvprod4460011v.jpg\n",
|
| 80 |
+
"nvprod3190129v.jpg\n",
|
| 81 |
+
"nvprod1770356v.jpg\n",
|
| 82 |
+
"nvprod4210099v.jpg\n",
|
| 83 |
+
"nvprod4280065v.jpg\n",
|
| 84 |
+
"nvprod3770018v.jpg\n",
|
| 85 |
+
"nvprod3950048v.jpg\n",
|
| 86 |
+
"nvprod4420033v.jpg\n",
|
| 87 |
+
"nvprod4110023v.jpg\n",
|
| 88 |
+
"nvprod4060043v.jpg\n",
|
| 89 |
+
"000387.jpg\n",
|
| 90 |
+
"nvprod4070043v.jpg\n",
|
| 91 |
+
"nvprod4330258v.jpg\n",
|
| 92 |
+
"nvprod3930075v.jpg\n",
|
| 93 |
+
"nvprod4240107v.jpg\n",
|
| 94 |
+
"nvprod4250107v.jpg\n",
|
| 95 |
+
"nvprod4320167v.jpg\n",
|
| 96 |
+
"nvprod4350265v.jpg\n",
|
| 97 |
+
"nvprod3190095v.jpg\n",
|
| 98 |
+
"nvprod3950398v.jpg\n",
|
| 99 |
+
"nvprod4150017v.jpg\n",
|
| 100 |
+
"nvprod4350009v.jpg\n",
|
| 101 |
+
"nvprod3630067v.jpg\n",
|
| 102 |
+
"nvprod3750007v.jpg\n",
|
| 103 |
+
"nvprod3160042v.jpg\n",
|
| 104 |
+
"nvprod1000229v.jpg\n",
|
| 105 |
+
"nvprod1490004v.jpg\n",
|
| 106 |
+
"nvprod990096v.jpg\n",
|
| 107 |
+
"nvprod4420025v.jpg\n",
|
| 108 |
+
"nvprod3740142v.jpg\n",
|
| 109 |
+
"nvprod4450059v.jpg\n",
|
| 110 |
+
"nvprod4320130v.jpg\n",
|
| 111 |
+
"nvprod4140105v.jpg\n",
|
| 112 |
+
"001310.jpg\n",
|
| 113 |
+
"nvprod4240015v.jpg\n",
|
| 114 |
+
"nvprod4020020v.jpg\n",
|
| 115 |
+
"nvprod3490034v.jpg\n",
|
| 116 |
+
"nvprod4430137v.jpg\n",
|
| 117 |
+
"nvprod3440005v.jpg\n",
|
| 118 |
+
"nvprod4480087v.jpg\n",
|
| 119 |
+
"nvprod2880037v.jpg\n",
|
| 120 |
+
"nvprod3170150v.jpg\n",
|
| 121 |
+
"nvprod4060002v.jpg\n",
|
| 122 |
+
"nvprod3660086v.jpg\n",
|
| 123 |
+
"nvprod4090041v.jpg\n",
|
| 124 |
+
"nvprod1970159v.jpg\n",
|
| 125 |
+
"nvprod4260067v.jpg\n",
|
| 126 |
+
"nvprod4350249v.jpg\n",
|
| 127 |
+
"nvprod4160032v.jpg\n",
|
| 128 |
+
"nvprod3980043v.jpg\n",
|
| 129 |
+
"nvprod4440022v.jpg\n",
|
| 130 |
+
"nvprod4300007v.jpg\n",
|
| 131 |
+
"nvprod4230229v.jpg\n",
|
| 132 |
+
"nvprod3950072v.jpg\n",
|
| 133 |
+
"nvprod3880008v.jpg\n",
|
| 134 |
+
"nvprod4060079v.jpg\n",
|
| 135 |
+
"nvprod4550069v.jpg\n",
|
| 136 |
+
"nvprod2450190v.jpg\n",
|
| 137 |
+
"nvprod3020007v.jpg\n",
|
| 138 |
+
"nvprod4330262v.jpg\n",
|
| 139 |
+
"nvprod4340025v.jpg\n",
|
| 140 |
+
"nvprod1420177v.jpg\n",
|
| 141 |
+
"nvprod4060096v.jpg\n",
|
| 142 |
+
"nvprod2330016v.jpg\n",
|
| 143 |
+
"nvprod3950567v.jpg\n",
|
| 144 |
+
"nvprod4120010v.jpg\n",
|
| 145 |
+
"nvprod3950619v.jpg\n",
|
| 146 |
+
"nvprod4160120v.jpg\n",
|
| 147 |
+
"nvprod4380043v.jpg\n",
|
| 148 |
+
"nvprod4230291v.jpg\n",
|
| 149 |
+
"nvprod1470047v.jpg\n",
|
| 150 |
+
"nvprod3900007v.jpg\n",
|
| 151 |
+
"nvprod4000005v.jpg\n",
|
| 152 |
+
"nvprod4300050v.jpg\n",
|
| 153 |
+
"nvprod2370063v.jpg\n",
|
| 154 |
+
"nvprod2540026v.jpg\n",
|
| 155 |
+
"nvprod4380106v.jpg\n",
|
| 156 |
+
"nvprod4010005v.jpg\n",
|
| 157 |
+
"nvprod4260030v.jpg\n",
|
| 158 |
+
"nvprod4160065v.jpg\n",
|
| 159 |
+
"nvprod2220266v.jpg\n",
|
| 160 |
+
"nvprod4330235v.jpg\n",
|
| 161 |
+
"nvprod1000317v.jpg\n",
|
| 162 |
+
"nvprod3630159v.jpg\n",
|
| 163 |
+
"nvprod3950025v.jpg\n",
|
| 164 |
+
"nvprod4120047v.jpg\n",
|
| 165 |
+
"nvprod3950530v.jpg\n",
|
| 166 |
+
"nvprod2330041v.jpg\n",
|
| 167 |
+
"nvprod3690006v.jpg\n",
|
| 168 |
+
"nvprod1420120v.jpg\n",
|
| 169 |
+
"nvprod1770291v.jpg\n",
|
| 170 |
+
"nvprod3160039v.jpg\n",
|
| 171 |
+
"nvprod3760130v.jpg\n",
|
| 172 |
+
"000386.jpg\n",
|
| 173 |
+
"nvprod3570138v.jpg\n",
|
| 174 |
+
"nvprod4010013v.jpg\n",
|
| 175 |
+
"nvprod4380110v.jpg\n",
|
| 176 |
+
"nvprod4300046v.jpg\n",
|
| 177 |
+
"nvprod3660182v.jpg\n",
|
| 178 |
+
"nvprod4170073v.jpg\n",
|
| 179 |
+
"nvprod3990002v.jpg\n",
|
| 180 |
+
"nvprod1600121v.jpg\n",
|
| 181 |
+
"nvprod4070038v.jpg\n",
|
| 182 |
+
"nvprod4330223v.jpg\n",
|
| 183 |
+
"nvprod4230141v.jpg\n",
|
| 184 |
+
"nvprod4130051v.jpg\n",
|
| 185 |
+
"nvprod3430043v.jpg\n",
|
| 186 |
+
"nvprod3980110v.jpg\n",
|
| 187 |
+
"nvprod2290051v.jpg\n",
|
| 188 |
+
"nvprod2190004v.jpg\n",
|
| 189 |
+
"nvprod4250078v.jpg\n",
|
| 190 |
+
"nvprod4320018v.jpg\n",
|
| 191 |
+
"nvprod4090057v.jpg\n",
|
| 192 |
+
"nvprod4240097v.jpg\n",
|
| 193 |
+
"nvprod3980055v.jpg\n",
|
| 194 |
+
"009188.jpg\n",
|
| 195 |
+
"nvprod4250097v.jpg\n",
|
| 196 |
+
"nvprod4310011v.jpg\n",
|
| 197 |
+
"nvprod4450034v.jpg\n",
|
| 198 |
+
"nvprod4260071v.jpg\n",
|
| 199 |
+
"nvprod4400153v.jpg\n",
|
| 200 |
+
"nvprod3580157v.jpg\n",
|
| 201 |
+
"nvprod3440087v.jpg\n",
|
| 202 |
+
"nvprod4050089v.jpg\n",
|
| 203 |
+
"nvprod3600054v.jpg\n",
|
| 204 |
+
"015238.jpg\n",
|
| 205 |
+
"nvprod4350033v.jpg\n",
|
| 206 |
+
"nvprod4220053v.jpg\n",
|
| 207 |
+
"nvprod3950121v.jpg\n",
|
| 208 |
+
"nvprod4060080v.jpg\n",
|
| 209 |
+
"nvprod4340033v.jpg\n",
|
| 210 |
+
"nvprod4340044v.jpg\n",
|
| 211 |
+
"012569.jpg\n",
|
| 212 |
+
"nvprod4350044v.jpg\n",
|
| 213 |
+
"009149.jpg\n",
|
| 214 |
+
"nvprod4220024v.jpg\n",
|
| 215 |
+
"nvprod3880069v.jpg\n",
|
| 216 |
+
"009161.jpg\n",
|
| 217 |
+
"nvprod4160053v.jpg\n",
|
| 218 |
+
"nvprod3930038v.jpg\n",
|
| 219 |
+
"nvprod4080020v.jpg\n",
|
| 220 |
+
"nvprod3430034v.jpg\n",
|
| 221 |
+
"nvprod4120026v.jpg\n",
|
| 222 |
+
"nvprod4210095v.jpg\n",
|
| 223 |
+
"nvprod4130026v.jpg\n",
|
| 224 |
+
"nvprod4340013v.jpg\n",
|
| 225 |
+
"nvprod2970009v.jpg\n",
|
| 226 |
+
"nvprod4230136v.jpg\n",
|
| 227 |
+
"nvprod4330254v.jpg\n",
|
| 228 |
+
"nvprod3020031v.jpg\n",
|
| 229 |
+
"nvprod2630039v.jpg\n",
|
| 230 |
+
"nvprod1900001v.jpg\n",
|
| 231 |
+
"nvprod3600074v.jpg\n",
|
| 232 |
+
"nvprod3770014v.jpg\n",
|
| 233 |
+
"nvprod4440014v.jpg\n",
|
| 234 |
+
"nvprod4300031v.jpg\n",
|
| 235 |
+
"nvprod3190060v.jpg\n",
|
| 236 |
+
"nvprod4260051v.jpg\n",
|
| 237 |
+
"nvprod3430063v.jpg\n",
|
| 238 |
+
"002593.jpg\n",
|
| 239 |
+
"nvprod4250058v.jpg\n",
|
| 240 |
+
"nvprod4240058v.jpg\n",
|
| 241 |
+
"nvprod3940117v.jpg\n",
|
| 242 |
+
"nvprod2680170v.jpg\n",
|
| 243 |
+
"nvprod2330036v.jpg\n",
|
| 244 |
+
"nvprod4120030v.jpg\n",
|
| 245 |
+
"nvprod3950052v.jpg\n",
|
| 246 |
+
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|
| 247 |
+
"nvprod4420029v.jpg\n",
|
| 248 |
+
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|
| 249 |
+
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|
| 250 |
+
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|
| 251 |
+
"nvprod4040115v.jpg\n",
|
| 252 |
+
"nvprod4230120v.jpg\n",
|
| 253 |
+
"nvprod4350269v.jpg\n",
|
| 254 |
+
"nvprod4160012v.jpg\n",
|
| 255 |
+
"nvprod3740267v.jpg\n",
|
| 256 |
+
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|
| 257 |
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|
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|
| 259 |
+
"nvprod4260102v.jpg\n",
|
| 260 |
+
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| 2006 |
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| 2007 |
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| 2008 |
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| 2009 |
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| 2010 |
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| 2011 |
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| 2012 |
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| 2013 |
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| 2014 |
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| 2015 |
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| 2016 |
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| 2017 |
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| 2018 |
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| 2019 |
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| 2020 |
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"013790.jpg\n",
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| 2021 |
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| 2022 |
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| 2023 |
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| 2024 |
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| 2025 |
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| 2026 |
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| 2027 |
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| 2028 |
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| 2029 |
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|
| 2030 |
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| 2031 |
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| 2032 |
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| 2033 |
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|
| 2034 |
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| 2035 |
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| 2036 |
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| 2037 |
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| 2038 |
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| 2039 |
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| 2040 |
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| 2041 |
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| 2042 |
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| 2043 |
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| 2044 |
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| 2045 |
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| 2048 |
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| 2049 |
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| 2050 |
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| 2051 |
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| 2053 |
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| 2054 |
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| 2058 |
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| 2059 |
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| 2060 |
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| 2063 |
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| 2064 |
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| 2066 |
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| 2067 |
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| 2068 |
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| 2069 |
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| 2070 |
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| 2080 |
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| 2090 |
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| 2098 |
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| 2100 |
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| 2101 |
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| 2110 |
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]
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},
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{
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| 2776 |
+
"name": "stdout",
|
| 2777 |
+
"output_type": "stream",
|
| 2778 |
+
"text": [
|
| 2779 |
+
"nvprod4350122v.jpg\n",
|
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"015591.jpg\n",
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| 2800 |
+
]
|
| 2801 |
+
}
|
| 2802 |
+
],
|
| 2803 |
+
"source": [
|
| 2804 |
+
"import torch\n",
|
| 2805 |
+
"from PIL import Image\n",
|
| 2806 |
+
"import os, glob\n",
|
| 2807 |
+
"import requests\n",
|
| 2808 |
+
"import numpy\n",
|
| 2809 |
+
"from transformers import CLIPProcessor, CLIPModel, CLIPImageProcessor\n",
|
| 2810 |
+
"import numpy as np\n",
|
| 2811 |
+
"\n",
|
| 2812 |
+
"device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
|
| 2813 |
+
"\n",
|
| 2814 |
+
"model = CLIPModel.from_pretrained(\"openai/clip-vit-base-patch32\")\n",
|
| 2815 |
+
"processor = CLIPProcessor.from_pretrained(\"openai/clip-vit-base-patch32\")\n",
|
| 2816 |
+
"\n",
|
| 2817 |
+
"\n",
|
| 2818 |
+
"os.chdir('/Users/jdonaldson/Projects/hushh/lvphotos')\n",
|
| 2819 |
+
"files = glob.glob(f'*.jpg')\n",
|
| 2820 |
+
"encodings = []\n",
|
| 2821 |
+
"for file in files:\n",
|
| 2822 |
+
" print(file)\n",
|
| 2823 |
+
" image = Image.open(file)\n",
|
| 2824 |
+
"# image = processor.image_processor.preprocess(images = image) \n",
|
| 2825 |
+
" with torch.no_grad():\n",
|
| 2826 |
+
" photo_preprocessed = processor(text=None, images=image, return_tensors=\"pt\", padding=True)[\"pixel_values\"]\n",
|
| 2827 |
+
" search_photo_feature = model.get_image_features(photo_preprocessed.to(device))\n",
|
| 2828 |
+
" search_photo_feature /= search_photo_feature.norm(dim=-1, keepdim=True)\n",
|
| 2829 |
+
" \n",
|
| 2830 |
+
" image_encoded = search_photo_feature.cpu().numpy()\n",
|
| 2831 |
+
" encodings.append(image_encoded)\n",
|
| 2832 |
+
" \n",
|
| 2833 |
+
" \n",
|
| 2834 |
+
"os.chdir('/Users/jdonaldson/Projects/hushh')\n",
|
| 2835 |
+
"with open(\"lv-handbags.pkl\", 'wb') as f:\n",
|
| 2836 |
+
" pickle.dump((files, np.concatenate(encodings)), f) \n",
|
| 2837 |
+
"\n",
|
| 2838 |
+
"# with open(\"lv-handbags.json\", \"w\") as f:\n",
|
| 2839 |
+
"# enc_list = np.concatenate(encodings).tolist()\n",
|
| 2840 |
+
"# json.dump({\"files\" : files, \"encodings\" : enc_list}, f)\n"
|
| 2841 |
+
]
|
| 2842 |
+
},
|
| 2843 |
+
{
|
| 2844 |
+
"cell_type": "code",
|
| 2845 |
+
"execution_count": 8,
|
| 2846 |
+
"id": "7af97c83",
|
| 2847 |
+
"metadata": {},
|
| 2848 |
+
"outputs": [
|
| 2849 |
+
{
|
| 2850 |
+
"data": {
|
| 2851 |
+
"text/plain": [
|
| 2852 |
+
"'nvprod2400042v'"
|
| 2853 |
+
]
|
| 2854 |
+
},
|
| 2855 |
+
"execution_count": 8,
|
| 2856 |
+
"metadata": {},
|
| 2857 |
+
"output_type": "execute_result"
|
| 2858 |
+
}
|
| 2859 |
+
],
|
| 2860 |
+
"source": [
|
| 2861 |
+
"file[:-4]"
|
| 2862 |
+
]
|
| 2863 |
+
},
|
| 2864 |
+
{
|
| 2865 |
+
"cell_type": "code",
|
| 2866 |
+
"execution_count": null,
|
| 2867 |
+
"id": "f3a331d7",
|
| 2868 |
+
"metadata": {},
|
| 2869 |
+
"outputs": [],
|
| 2870 |
+
"source": []
|
| 2871 |
+
}
|
| 2872 |
+
],
|
| 2873 |
+
"metadata": {
|
| 2874 |
+
"kernelspec": {
|
| 2875 |
+
"display_name": "Python 3 (ipykernel)",
|
| 2876 |
+
"language": "python",
|
| 2877 |
+
"name": "python3"
|
| 2878 |
+
},
|
| 2879 |
+
"language_info": {
|
| 2880 |
+
"codemirror_mode": {
|
| 2881 |
+
"name": "ipython",
|
| 2882 |
+
"version": 3
|
| 2883 |
+
},
|
| 2884 |
+
"file_extension": ".py",
|
| 2885 |
+
"mimetype": "text/x-python",
|
| 2886 |
+
"name": "python",
|
| 2887 |
+
"nbconvert_exporter": "python",
|
| 2888 |
+
"pygments_lexer": "ipython3",
|
| 2889 |
+
"version": "3.10.11"
|
| 2890 |
+
}
|
| 2891 |
+
},
|
| 2892 |
+
"nbformat": 4,
|
| 2893 |
+
"nbformat_minor": 5
|
| 2894 |
+
}
|
README.md
CHANGED
|
@@ -10,6 +10,8 @@ python_version: 3.10.10
|
|
| 10 |
duplicated_from: marcelcastrobr/CLIP-image-search
|
| 11 |
---
|
| 12 |
|
|
|
|
|
|
|
| 13 |
# Configuration
|
| 14 |
|
| 15 |
`title`: _string_
|
|
|
|
| 10 |
duplicated_from: marcelcastrobr/CLIP-image-search
|
| 11 |
---
|
| 12 |
|
| 13 |
+
TEST
|
| 14 |
+
|
| 15 |
# Configuration
|
| 16 |
|
| 17 |
`title`: _string_
|
Scrape LV.ipynb
ADDED
|
@@ -0,0 +1,292 @@
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|
|
|
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|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"cells": [
|
| 3 |
+
{
|
| 4 |
+
"cell_type": "code",
|
| 5 |
+
"execution_count": null,
|
| 6 |
+
"id": "9e7cae4a",
|
| 7 |
+
"metadata": {},
|
| 8 |
+
"outputs": [],
|
| 9 |
+
"source": [
|
| 10 |
+
"from lxml import html\n",
|
| 11 |
+
"import requests\n",
|
| 12 |
+
"import os\n",
|
| 13 |
+
"import pandas as pd\n"
|
| 14 |
+
]
|
| 15 |
+
},
|
| 16 |
+
{
|
| 17 |
+
"cell_type": "code",
|
| 18 |
+
"execution_count": null,
|
| 19 |
+
"id": "c88b9ce9",
|
| 20 |
+
"metadata": {},
|
| 21 |
+
"outputs": [],
|
| 22 |
+
"source": [
|
| 23 |
+
"client_id = os.environ['LV_CLIENT_ID']\n",
|
| 24 |
+
"client_secret = os.environ['LV_CLIENT_SECRET']\n",
|
| 25 |
+
"headers = {\n",
|
| 26 |
+
" 'Content-Type':'application/json',\n",
|
| 27 |
+
" 'authority':'api.louisvuitton.com',\n",
|
| 28 |
+
" 'accept':'application/json, text/plain, */*',\n",
|
| 29 |
+
" 'accept-language':'en-US,en;q=0.6',\n",
|
| 30 |
+
" 'client_id':client_id,\n",
|
| 31 |
+
" 'client_secret':client_secret,\n",
|
| 32 |
+
" 'cookie':'ak_cc=US; OPTOUTMULTI=0:0%7Cc1:0%7Cc2:1%7Cc4:1%7Cc3:1; ATGID=anonymous; SGID=sb.springboot41-prd; SGID=.springboot41-prd; prevURL=; currentURL=https://www.louisvuitton.com/ajax/productsearch; storeLangCommerceHeader=eng-e1; geolocUserZone=eng-us; AKA_A2=A; _abck=94026E30A1FABEBFA844CBD6388965B8~0~YAAQnr8mF5/FGIeIAQAAjjKPkgpw8D5r3zC2HFECV0EQXRXPCoAQ+gYSqR/Sut2w/03toFhfVT9Yda45yFwqUGKStpIxbZAwPw0ooQplfv9eymgzFxyoYjEcqrD6rV/4OEgdCIov1wE0On3Z71z1v9UoZOisQgAlBEKsV0dYi02t6vutjUwi6f5T6N+h6SWX1l62T/QGwvxI13WHrWAOIsNJ1VJd/N3FiC/cKxVKskc3YPJf8tFZ25jOs2cUin5GUXWA7HuLb7dpffVxE0wp5vcOes47KXi9be6zRpbtfF+aHEjVkgPsOjznAFhN/X6FCHBTuJ5UvY2vHlWEIR8kW/pEW4zHm5bfQyaKKiBWQvHTXkeKRyhCnUSoRx9wZPB2dIcdY2igDmG06NT+NWYDPJtLoIU1I14uXhn+p8/w~-1~-1~-1; bm_sz=A8530E728A25BB2F984ED31AD5DF00A6~YAAQnr8mF6LFGIeIAQAAjjKPkhQ72plnxNz48wepUXjRYRETUBQ1oWkIiS8E0wS/+9NHmJzh9bagubSRjmSbTkSEEzyIbBsWTowVRBJBCiW6xO9lhJT/vmSLZtosV4g0eTOhRFoFwRrorwWUjGarPRTLozlk+KpZppYbt+EbdcyCdZNb95EUr6Za65FUi8FRSH02djUkhL5XlC3aebrVqtHfnG7uCJsWYBo+fnDJU1+mxQ8e1J+iTdq4ZdXsYuUuXZz3A0OJMy1JP5M/kKV4JKmIO89y3rgqZZB+xxNLbY+Su4yH7c/q2+s=~3556656~3686978; lv-dispatch=eng-us; consent_ecom_us=functional:1|analytics:0|customization:0|advertising:0; qb_dnt=2; ak_bmsc=589EDDF01ED59E65EA72F7393A895F31~000000000000000000000000000000~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; ATG_SESSION_ID=GCUqx-HVSh3KVpIaIX+L30So.front41-prd; _dynSessConf=-86995900442046424; JSESSIONID=GCUqx-HVSh3KVpIaIX+L30So.front41-prd; PIM-SESSION-ID=HBqQRDXDzoWH4e2V; bm_sv=CF0A04BDB7486115978F40C364AB5E38~YAAQnr8mF1opHYeIAQAAT1G5khS7D+LGov3Y87+pRE+B0F86Y3tJjyDrwszLeFA06ZC1s/so8vDcDtmB0VrCDU1N+jlXvFNpGfEkhJTiyQrFAkZq2i57xih3Y4Oe7kDnWY6TqYj05c7rqHmBOUw8+XtLNLJAzSPx+0cKcLqujkgpHiI1xPuO1N27mPXK0SMc2DLsF9MJZa0EqlH8YtoHBgDTz/q2R9Q5g28FJHVuw3SqLHdFDaHO2dML6P/eVsRDeYR3XTd8OQ==~1; lv-dispatch-url=https://us.louisvuitton.com/eng-us/women/handbags/all-handbags/_/N-tfr7qdp; utag_main=_sn:6$_se:25$_ss:0$_st:1686090605436$dc_visit:2$v_id:01884a527895001827510ebf5e3504075002b06d00a61$ses_id:1686086038612%3Bexp-session$_pn:10%3Bexp-session',\n",
|
| 33 |
+
" 'origin':'https://us.louisvuitton.com',\n",
|
| 34 |
+
" 'referer':'https://us.louisvuitton.com/',\n",
|
| 35 |
+
" 'sec-ch-ua':'\"Brave\";v=\"113\", \"Chromium\";v=\"113\", \"Not-A.Brand\";v=\"24\"',\n",
|
| 36 |
+
" 'sec-ch-ua-mobile':'?0',\n",
|
| 37 |
+
" 'sec-ch-ua-platform':'\"macOS\"',\n",
|
| 38 |
+
" 'sec-fetch-dest':'empty',\n",
|
| 39 |
+
" 'sec-fetch-mode':'cors',\n",
|
| 40 |
+
" 'sec-fetch-site':'same-site',\n",
|
| 41 |
+
" 'sec-gpc':'1',\n",
|
| 42 |
+
" 'user-agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0',\n",
|
| 43 |
+
"}\n"
|
| 44 |
+
]
|
| 45 |
+
},
|
| 46 |
+
{
|
| 47 |
+
"cell_type": "code",
|
| 48 |
+
"execution_count": null,
|
| 49 |
+
"id": "78440fbc",
|
| 50 |
+
"metadata": {},
|
| 51 |
+
"outputs": [],
|
| 52 |
+
"source": [
|
| 53 |
+
"url = 'https://us.louisvuitton.com/eng-us/homepage'\n",
|
| 54 |
+
"response = requests.get(url, headers=headers)\n",
|
| 55 |
+
"print(len(response.text))\n",
|
| 56 |
+
"tree = html.fromstring(response.text)\n"
|
| 57 |
+
]
|
| 58 |
+
},
|
| 59 |
+
{
|
| 60 |
+
"cell_type": "code",
|
| 61 |
+
"execution_count": null,
|
| 62 |
+
"id": "f91b5ee1",
|
| 63 |
+
"metadata": {},
|
| 64 |
+
"outputs": [],
|
| 65 |
+
"source": [
|
| 66 |
+
"sitemap_paths = tree.xpath('//*[@id=\"header\"]//a/@href')\n",
|
| 67 |
+
"\n",
|
| 68 |
+
"categories = {}\n",
|
| 69 |
+
"for p in sitemap_paths:\n",
|
| 70 |
+
" parts = p.split(\"/\")\n",
|
| 71 |
+
" if parts[-1].startswith(\"N-\") :\n",
|
| 72 |
+
" categories[parts[-3]]= {\"code\":parts[-1][2:]}\n",
|
| 73 |
+
"len(categories)"
|
| 74 |
+
]
|
| 75 |
+
},
|
| 76 |
+
{
|
| 77 |
+
"cell_type": "code",
|
| 78 |
+
"execution_count": null,
|
| 79 |
+
"id": "429ba6c0",
|
| 80 |
+
"metadata": {
|
| 81 |
+
"scrolled": false
|
| 82 |
+
},
|
| 83 |
+
"outputs": [],
|
| 84 |
+
"source": [
|
| 85 |
+
"for cat_key in categories.keys():\n",
|
| 86 |
+
" print(cat_key)\n",
|
| 87 |
+
" code = categories[cat_key][\"code\"]\n",
|
| 88 |
+
"\n",
|
| 89 |
+
" url = f'https://api.louisvuitton.com/eco-eu/search-merch-eapi/v1/eng-us/plp/products/{code}-ay1ygzo25?page='\n",
|
| 90 |
+
" print(url)\n",
|
| 91 |
+
" nbPages = 100\n",
|
| 92 |
+
" page = 0\n",
|
| 93 |
+
" all_hits = []\n",
|
| 94 |
+
"\n",
|
| 95 |
+
" while page < nbPages:\n",
|
| 96 |
+
" response = requests.get(url + str(page), headers=headers)\n",
|
| 97 |
+
" res = response.json()\n",
|
| 98 |
+
" if \"nbPages\" in res:\n",
|
| 99 |
+
" nbPages = res[\"nbPages\"]\n",
|
| 100 |
+
" all_hits.extend(res[\"hits\"])\n",
|
| 101 |
+
" print(res[\"page\"], len(all_hits))\n",
|
| 102 |
+
" page = page + 1\n",
|
| 103 |
+
"\n",
|
| 104 |
+
"\n",
|
| 105 |
+
" recs = []\n",
|
| 106 |
+
" misses = []\n",
|
| 107 |
+
" for hit in all_hits:\n",
|
| 108 |
+
" try:\n",
|
| 109 |
+
" rec = {}\n",
|
| 110 |
+
" for key in [\"productId\", \"name\", \"url\", \"disambiguatingDescription\"]:\n",
|
| 111 |
+
" rec[key] = hit[key]\n",
|
| 112 |
+
" rec[\"image\"] = hit[\"image\"][0][\"contentUrl\"]\n",
|
| 113 |
+
" recs.append(rec)\n",
|
| 114 |
+
" except:\n",
|
| 115 |
+
" misses.append(rec)\n",
|
| 116 |
+
" print(hit)\n",
|
| 117 |
+
" categories[cat_key][\"urls\"] = recs\n",
|
| 118 |
+
" categories[cat_key][\"misses\"] = misses\n"
|
| 119 |
+
]
|
| 120 |
+
},
|
| 121 |
+
{
|
| 122 |
+
"cell_type": "code",
|
| 123 |
+
"execution_count": null,
|
| 124 |
+
"id": "1bd2372a",
|
| 125 |
+
"metadata": {},
|
| 126 |
+
"outputs": [],
|
| 127 |
+
"source": [
|
| 128 |
+
"flatten = []\n",
|
| 129 |
+
"for cat in categories.keys():\n",
|
| 130 |
+
" info = categories[cat]\n",
|
| 131 |
+
" for rec in categories[cat][\"urls\"]:\n",
|
| 132 |
+
" doc = {}\n",
|
| 133 |
+
" doc[\"productId\"] = rec[\"productId\"]\n",
|
| 134 |
+
" doc[\"category\"] = cat\n",
|
| 135 |
+
" doc[\"category_code\"] = info[\"code\"]\n",
|
| 136 |
+
" doc[\"name\"] = rec[\"name\"]\n",
|
| 137 |
+
" doc[\"url\"] = rec[\"url\"]\n",
|
| 138 |
+
" doc[\"image\"] = rec[\"image\"]\n",
|
| 139 |
+
" doc[\"disambiguatingDescription\"] = rec[\"disambiguatingDescription\"]\n",
|
| 140 |
+
" flatten.append(doc)\n"
|
| 141 |
+
]
|
| 142 |
+
},
|
| 143 |
+
{
|
| 144 |
+
"cell_type": "code",
|
| 145 |
+
"execution_count": null,
|
| 146 |
+
"id": "9df3b289",
|
| 147 |
+
"metadata": {},
|
| 148 |
+
"outputs": [],
|
| 149 |
+
"source": [
|
| 150 |
+
"\n",
|
| 151 |
+
"dat = pd.DataFrame(flatten)\n",
|
| 152 |
+
"size = str(400)\n",
|
| 153 |
+
"dat['image_fix'] = dat['image'].str.replace(\"{IMG_HEIGHT}\", size).str.replace(\"{IMG_WIDTH}\", size).str.replace(\" \", \"%20\")\n"
|
| 154 |
+
]
|
| 155 |
+
},
|
| 156 |
+
{
|
| 157 |
+
"cell_type": "code",
|
| 158 |
+
"execution_count": null,
|
| 159 |
+
"id": "e19f1375",
|
| 160 |
+
"metadata": {},
|
| 161 |
+
"outputs": [],
|
| 162 |
+
"source": [
|
| 163 |
+
"dat"
|
| 164 |
+
]
|
| 165 |
+
},
|
| 166 |
+
{
|
| 167 |
+
"cell_type": "code",
|
| 168 |
+
"execution_count": null,
|
| 169 |
+
"id": "f08df1f2",
|
| 170 |
+
"metadata": {
|
| 171 |
+
"scrolled": false
|
| 172 |
+
},
|
| 173 |
+
"outputs": [],
|
| 174 |
+
"source": [
|
| 175 |
+
"import os\n",
|
| 176 |
+
"for rec in dat.itertuples():\n",
|
| 177 |
+
" \n",
|
| 178 |
+
" print(rec.image_fix)\n",
|
| 179 |
+
" os.system(f\"\"\"\n",
|
| 180 |
+
" curl '{rec.image_fix}'\\\n",
|
| 181 |
+
" -H 'authority: us.louisvuitton.com' \\\n",
|
| 182 |
+
" -H 'accept: image/avif,image/webp,image/apng,image/svg+xml,image/*,*/*;q=0.8' \\\n",
|
| 183 |
+
" -H 'accept-language: en-US,en;q=0.9' \\\n",
|
| 184 |
+
" -H 'cache-control: no-cache' \\\n",
|
| 185 |
+
" -H 'cookie: ak_cc=US; OPTOUTMULTI=0:0%7Cc1:0%7Cc2:1%7Cc4:1%7Cc3:1; ATGID=anonymous; SGID=sb.springboot41-prd; prevURL=; currentURL=https://www.louisvuitton.com/ajax/productsearch; storeLangCommerceHeader=eng-e1; geolocUserZone=eng-us; AKA_A2=A; _abck=94026E30A1FABEBFA844CBD6388965B8~0~YAAQnr8mF5/FGIeIAQAAjjKPkgpw8D5r3zC2HFECV0EQXRXPCoAQ+gYSqR/Sut2w/03toFhfVT9Yda45yFwqUGKStpIxbZAwPw0ooQplfv9eymgzFxyoYjEcqrD6rV/4OEgdCIov1wE0On3Z71z1v9UoZOisQgAlBEKsV0dYi02t6vutjUwi6f5T6N+h6SWX1l62T/QGwvxI13WHrWAOIsNJ1VJd/N3FiC/cKxVKskc3YPJf8tFZ25jOs2cUin5GUXWA7HuLb7dpffVxE0wp5vcOes47KXi9be6zRpbtfF+aHEjVkgPsOjznAFhN/X6FCHBTuJ5UvY2vHlWEIR8kW/pEW4zHm5bfQyaKKiBWQvHTXkeKRyhCnUSoRx9wZPB2dIcdY2igDmG06NT+NWYDPJtLoIU1I14uXhn+p8/w~-1~-1~-1; bm_sz=A8530E728A25BB2F984ED31AD5DF00A6~YAAQnr8mF6LFGIeIAQAAjjKPkhQ72plnxNz48wepUXjRYRETUBQ1oWkIiS8E0wS/+9NHmJzh9bagubSRjmSbTkSEEzyIbBsWTowVRBJBCiW6xO9lhJT/vmSLZtosV4g0eTOhRFoFwRrorwWUjGarPRTLozlk+KpZppYbt+EbdcyCdZNb95EUr6Za65FUi8FRSH02djUkhL5XlC3aebrVqtHfnG7uCJsWYBo+fnDJU1+mxQ8e1J+iTdq4ZdXsYuUuXZz3A0OJMy1JP5M/kKV4JKmIO89y3rgqZZB+xxNLbY+Su4yH7c/q2+s=~3556656~3686978; lv-dispatch=eng-us; consent_ecom_us=functional:1|analytics:0|customization:0|advertising:0; qb_dnt=2; ak_bmsc=589EDDF01ED59E65EA72F7393A895F31~000000000000000000000000000000~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; PIM-SESSION-ID=HBqQRDXDzoWH4e2V; lv-dispatch-url=https://us.louisvuitton.com/eng-us/women/handbags/all-handbags/_/N-tfr7qdp; utag_main=_sn:6$_se:28$_ss:0$_st:1686090718084$dc_visit:2$v_id:01884a527895001827510ebf5e3504075002b06d00a61$ses_id:1686086038612%3Bexp-session$_pn:11%3Bexp-session; anonymous_session=true; ATG_SESSION_ID=B-8233ZEyNVjFobJCNa+2INd.front41-prd; _dynSessConf=2255588875954406228; JSESSIONID=B-8233ZEyNVjFobJCNa+2INd.front41-prd; bm_sv=CF0A04BDB7486115978F40C364AB5E38~YAAQnr8mF1xwHYeIAQAAlSm7khS9xE3iX2eAH+anrXfnlQ7v8oUsEA0z/MTkPXZnzBAvGACc64Rw7A1Y5WpGYwhqMubbtv5eueVsxuxlhE/aJNZtgpkk/epZage/P7W27HdoknmpCXGdYaFsYNTqrcCrNXOS/DUkUdvE6OjHGDg6c+05MfuLiHR+zMzGM/mZzxWzV3ruLRv6toIGPskD/LkRrOU0j8B7alLLaAhQKTvZVFPlcgbho2BHD8rHcNL0E7h2pvdGvA==~1' \\\n",
|
| 186 |
+
" -H 'pragma: no-cache' \\\n",
|
| 187 |
+
" -H 'referer: https://us.louisvuitton.com/eng-us/products/twist-belt-chain-wallet-epi-nvprod1740047v/M68560' \\\n",
|
| 188 |
+
" -H 'sec-ch-ua: \"Not.A/Brand\";v=\"8\", \"Chromium\";v=\"114\", \"Brave\";v=\"114\"' \\\n",
|
| 189 |
+
" -H 'sec-ch-ua-mobile: ?0' \\\n",
|
| 190 |
+
" -H 'sec-ch-ua-platform: \"macOS\"' \\\n",
|
| 191 |
+
" -H 'sec-fetch-dest: image' \\\n",
|
| 192 |
+
" -H 'sec-fetch-mode: no-cors' \\\n",
|
| 193 |
+
" -H 'sec-fetch-site: same-origin' \\\n",
|
| 194 |
+
" -H 'sec-gpc: 1' \\\n",
|
| 195 |
+
" -H 'user-agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36' \\\n",
|
| 196 |
+
" --compressed --output 'lvphotos/{rec.productId}.png'\n",
|
| 197 |
+
" \"\"\")\n"
|
| 198 |
+
]
|
| 199 |
+
},
|
| 200 |
+
{
|
| 201 |
+
"cell_type": "code",
|
| 202 |
+
"execution_count": 16,
|
| 203 |
+
"id": "a8ab57be",
|
| 204 |
+
"metadata": {
|
| 205 |
+
"scrolled": false
|
| 206 |
+
},
|
| 207 |
+
"outputs": [
|
| 208 |
+
{
|
| 209 |
+
"ename": "UnidentifiedImageError",
|
| 210 |
+
"evalue": "cannot identify image file '/Users/jdonaldson/Projects/hushh/lvphotos/nvprod4280065v.png'",
|
| 211 |
+
"output_type": "error",
|
| 212 |
+
"traceback": [
|
| 213 |
+
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
| 214 |
+
"\u001b[0;31mUnidentifiedImageError\u001b[0m Traceback (most recent call last)",
|
| 215 |
+
"Cell \u001b[0;32mIn[16], line 10\u001b[0m\n\u001b[1;32m 8\u001b[0m encodings \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m file \u001b[38;5;129;01min\u001b[39;00m files:\n\u001b[0;32m---> 10\u001b[0m image \u001b[38;5;241m=\u001b[39m \u001b[43mImage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43md\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m/\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mfile\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
|
| 216 |
+
"File \u001b[0;32m/opt/homebrew/anaconda3/envs/lv/lib/python3.10/site-packages/PIL/Image.py:3283\u001b[0m, in \u001b[0;36mopen\u001b[0;34m(fp, mode, formats)\u001b[0m\n\u001b[1;32m 3281\u001b[0m warnings\u001b[38;5;241m.\u001b[39mwarn(message)\n\u001b[1;32m 3282\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcannot identify image file \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m (filename \u001b[38;5;28;01mif\u001b[39;00m filename \u001b[38;5;28;01melse\u001b[39;00m fp)\n\u001b[0;32m-> 3283\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m UnidentifiedImageError(msg)\n",
|
| 217 |
+
"\u001b[0;31mUnidentifiedImageError\u001b[0m: cannot identify image file '/Users/jdonaldson/Projects/hushh/lvphotos/nvprod4280065v.png'"
|
| 218 |
+
]
|
| 219 |
+
}
|
| 220 |
+
],
|
| 221 |
+
"source": [
|
| 222 |
+
"import os\n",
|
| 223 |
+
"import glob\n",
|
| 224 |
+
"import sys\n",
|
| 225 |
+
"from PIL import Image\n",
|
| 226 |
+
"d = '/Users/jdonaldson/Projects/hushh/lvphotos'\n",
|
| 227 |
+
"os.chdir(d)\n",
|
| 228 |
+
"files = glob.glob(f'*.png')\n",
|
| 229 |
+
"encodings = []\n",
|
| 230 |
+
"for file in files:\n",
|
| 231 |
+
" image = Image.open(f\"{d}/{file}\")\n"
|
| 232 |
+
]
|
| 233 |
+
},
|
| 234 |
+
{
|
| 235 |
+
"cell_type": "code",
|
| 236 |
+
"execution_count": 24,
|
| 237 |
+
"id": "1de4037f",
|
| 238 |
+
"metadata": {},
|
| 239 |
+
"outputs": [],
|
| 240 |
+
"source": [
|
| 241 |
+
"!mogrify -format jpg *.png"
|
| 242 |
+
]
|
| 243 |
+
},
|
| 244 |
+
{
|
| 245 |
+
"cell_type": "code",
|
| 246 |
+
"execution_count": 22,
|
| 247 |
+
"id": "191cd02a",
|
| 248 |
+
"metadata": {},
|
| 249 |
+
"outputs": [
|
| 250 |
+
{
|
| 251 |
+
"name": "stdout",
|
| 252 |
+
"output_type": "stream",
|
| 253 |
+
"text": [
|
| 254 |
+
"/Users/jdonaldson/Projects/hushh/lvphotos\r\n"
|
| 255 |
+
]
|
| 256 |
+
}
|
| 257 |
+
],
|
| 258 |
+
"source": [
|
| 259 |
+
"!pwd"
|
| 260 |
+
]
|
| 261 |
+
},
|
| 262 |
+
{
|
| 263 |
+
"cell_type": "code",
|
| 264 |
+
"execution_count": null,
|
| 265 |
+
"id": "dac99f1c",
|
| 266 |
+
"metadata": {},
|
| 267 |
+
"outputs": [],
|
| 268 |
+
"source": []
|
| 269 |
+
}
|
| 270 |
+
],
|
| 271 |
+
"metadata": {
|
| 272 |
+
"kernelspec": {
|
| 273 |
+
"display_name": "Python 3 (ipykernel)",
|
| 274 |
+
"language": "python",
|
| 275 |
+
"name": "python3"
|
| 276 |
+
},
|
| 277 |
+
"language_info": {
|
| 278 |
+
"codemirror_mode": {
|
| 279 |
+
"name": "ipython",
|
| 280 |
+
"version": 3
|
| 281 |
+
},
|
| 282 |
+
"file_extension": ".py",
|
| 283 |
+
"mimetype": "text/x-python",
|
| 284 |
+
"name": "python",
|
| 285 |
+
"nbconvert_exporter": "python",
|
| 286 |
+
"pygments_lexer": "ipython3",
|
| 287 |
+
"version": "3.10.11"
|
| 288 |
+
}
|
| 289 |
+
},
|
| 290 |
+
"nbformat": 4,
|
| 291 |
+
"nbformat_minor": 5
|
| 292 |
+
}
|
Untitled.ipynb
ADDED
|
@@ -0,0 +1,88 @@
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|
|
|
| 1 |
+
{
|
| 2 |
+
"cells": [
|
| 3 |
+
{
|
| 4 |
+
"cell_type": "code",
|
| 5 |
+
"execution_count": 1,
|
| 6 |
+
"id": "8d3b2225",
|
| 7 |
+
"metadata": {},
|
| 8 |
+
"outputs": [],
|
| 9 |
+
"source": [
|
| 10 |
+
"from lxml import html\n",
|
| 11 |
+
"import requests\n",
|
| 12 |
+
"import os\n"
|
| 13 |
+
]
|
| 14 |
+
},
|
| 15 |
+
{
|
| 16 |
+
"cell_type": "code",
|
| 17 |
+
"execution_count": 2,
|
| 18 |
+
"id": "1bf289a8",
|
| 19 |
+
"metadata": {},
|
| 20 |
+
"outputs": [
|
| 21 |
+
{
|
| 22 |
+
"ename": "KeyError",
|
| 23 |
+
"evalue": "'LV_CLIENT_ID'",
|
| 24 |
+
"output_type": "error",
|
| 25 |
+
"traceback": [
|
| 26 |
+
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
| 27 |
+
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
|
| 28 |
+
"Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m client_id \u001b[38;5;241m=\u001b[39m \u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43menviron\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mLV_CLIENT_ID\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 2\u001b[0m client_secret \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39menviron[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mLV_CLIENT_SECRET\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m 3\u001b[0m headers \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 4\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mContent-Type\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mapplication/json\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m 5\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mauthority\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mapi.louisvuitton.com\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124muser-agent\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m 21\u001b[0m }\n",
|
| 29 |
+
"File \u001b[0;32m/opt/homebrew/anaconda3/envs/lv/lib/python3.10/os.py:680\u001b[0m, in \u001b[0;36m_Environ.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 677\u001b[0m value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_data[\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mencodekey(key)]\n\u001b[1;32m 678\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n\u001b[1;32m 679\u001b[0m \u001b[38;5;66;03m# raise KeyError with the original key value\u001b[39;00m\n\u001b[0;32m--> 680\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 681\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdecodevalue(value)\n",
|
| 30 |
+
"\u001b[0;31mKeyError\u001b[0m: 'LV_CLIENT_ID'"
|
| 31 |
+
]
|
| 32 |
+
}
|
| 33 |
+
],
|
| 34 |
+
"source": [
|
| 35 |
+
"client_id = os.environ['LV_CLIENT_ID']\n",
|
| 36 |
+
"client_secret = os.environ['LV_CLIENT_SECRET']\n",
|
| 37 |
+
"headers = {\n",
|
| 38 |
+
" 'Content-Type':'application/json',\n",
|
| 39 |
+
" 'authority':'api.louisvuitton.com',\n",
|
| 40 |
+
" 'accept':'application/json, text/plain, */*',\n",
|
| 41 |
+
" 'accept-language':'en-US,en;q=0.6',\n",
|
| 42 |
+
" 'client_id':client_id,\n",
|
| 43 |
+
" 'client_secret':client_secret,\n",
|
| 44 |
+
" 'cookie':'ak_cc=US; OPTOUTMULTI=0:0%7Cc1:0%7Cc2:1%7Cc4:1%7Cc3:1; ATGID=anonymous; SGID=sb.springboot41-prd; SGID=.springboot41-prd; prevURL=; currentURL=https://www.louisvuitton.com/ajax/productsearch; storeLangCommerceHeader=eng-e1; geolocUserZone=eng-us; AKA_A2=A; _abck=94026E30A1FABEBFA844CBD6388965B8~0~YAAQnr8mF5/FGIeIAQAAjjKPkgpw8D5r3zC2HFECV0EQXRXPCoAQ+gYSqR/Sut2w/03toFhfVT9Yda45yFwqUGKStpIxbZAwPw0ooQplfv9eymgzFxyoYjEcqrD6rV/4OEgdCIov1wE0On3Z71z1v9UoZOisQgAlBEKsV0dYi02t6vutjUwi6f5T6N+h6SWX1l62T/QGwvxI13WHrWAOIsNJ1VJd/N3FiC/cKxVKskc3YPJf8tFZ25jOs2cUin5GUXWA7HuLb7dpffVxE0wp5vcOes47KXi9be6zRpbtfF+aHEjVkgPsOjznAFhN/X6FCHBTuJ5UvY2vHlWEIR8kW/pEW4zHm5bfQyaKKiBWQvHTXkeKRyhCnUSoRx9wZPB2dIcdY2igDmG06NT+NWYDPJtLoIU1I14uXhn+p8/w~-1~-1~-1; bm_sz=A8530E728A25BB2F984ED31AD5DF00A6~YAAQnr8mF6LFGIeIAQAAjjKPkhQ72plnxNz48wepUXjRYRETUBQ1oWkIiS8E0wS/+9NHmJzh9bagubSRjmSbTkSEEzyIbBsWTowVRBJBCiW6xO9lhJT/vmSLZtosV4g0eTOhRFoFwRrorwWUjGarPRTLozlk+KpZppYbt+EbdcyCdZNb95EUr6Za65FUi8FRSH02djUkhL5XlC3aebrVqtHfnG7uCJsWYBo+fnDJU1+mxQ8e1J+iTdq4ZdXsYuUuXZz3A0OJMy1JP5M/kKV4JKmIO89y3rgqZZB+xxNLbY+Su4yH7c/q2+s=~3556656~3686978; lv-dispatch=eng-us; consent_ecom_us=functional:1|analytics:0|customization:0|advertising:0; qb_dnt=2; ak_bmsc=589EDDF01ED59E65EA72F7393A895F31~000000000000000000000000000000~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; ATG_SESSION_ID=GCUqx-HVSh3KVpIaIX+L30So.front41-prd; _dynSessConf=-86995900442046424; JSESSIONID=GCUqx-HVSh3KVpIaIX+L30So.front41-prd; PIM-SESSION-ID=HBqQRDXDzoWH4e2V; bm_sv=CF0A04BDB7486115978F40C364AB5E38~YAAQnr8mF1opHYeIAQAAT1G5khS7D+LGov3Y87+pRE+B0F86Y3tJjyDrwszLeFA06ZC1s/so8vDcDtmB0VrCDU1N+jlXvFNpGfEkhJTiyQrFAkZq2i57xih3Y4Oe7kDnWY6TqYj05c7rqHmBOUw8+XtLNLJAzSPx+0cKcLqujkgpHiI1xPuO1N27mPXK0SMc2DLsF9MJZa0EqlH8YtoHBgDTz/q2R9Q5g28FJHVuw3SqLHdFDaHO2dML6P/eVsRDeYR3XTd8OQ==~1; lv-dispatch-url=https://us.louisvuitton.com/eng-us/women/handbags/all-handbags/_/N-tfr7qdp; utag_main=_sn:6$_se:25$_ss:0$_st:1686090605436$dc_visit:2$v_id:01884a527895001827510ebf5e3504075002b06d00a61$ses_id:1686086038612%3Bexp-session$_pn:10%3Bexp-session',\n",
|
| 45 |
+
" 'origin':'https://us.louisvuitton.com',\n",
|
| 46 |
+
" 'referer':'https://us.louisvuitton.com/',\n",
|
| 47 |
+
" 'sec-ch-ua':'\"Brave\";v=\"113\", \"Chromium\";v=\"113\", \"Not-A.Brand\";v=\"24\"',\n",
|
| 48 |
+
" 'sec-ch-ua-mobile':'?0',\n",
|
| 49 |
+
" 'sec-ch-ua-platform':'\"macOS\"',\n",
|
| 50 |
+
" 'sec-fetch-dest':'empty',\n",
|
| 51 |
+
" 'sec-fetch-mode':'cors',\n",
|
| 52 |
+
" 'sec-fetch-site':'same-site',\n",
|
| 53 |
+
" 'sec-gpc':'1',\n",
|
| 54 |
+
" 'user-agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0',\n",
|
| 55 |
+
"}\n"
|
| 56 |
+
]
|
| 57 |
+
},
|
| 58 |
+
{
|
| 59 |
+
"cell_type": "code",
|
| 60 |
+
"execution_count": null,
|
| 61 |
+
"id": "e4282087",
|
| 62 |
+
"metadata": {},
|
| 63 |
+
"outputs": [],
|
| 64 |
+
"source": []
|
| 65 |
+
}
|
| 66 |
+
],
|
| 67 |
+
"metadata": {
|
| 68 |
+
"kernelspec": {
|
| 69 |
+
"display_name": "Python 3 (ipykernel)",
|
| 70 |
+
"language": "python",
|
| 71 |
+
"name": "python3"
|
| 72 |
+
},
|
| 73 |
+
"language_info": {
|
| 74 |
+
"codemirror_mode": {
|
| 75 |
+
"name": "ipython",
|
| 76 |
+
"version": 3
|
| 77 |
+
},
|
| 78 |
+
"file_extension": ".py",
|
| 79 |
+
"mimetype": "text/x-python",
|
| 80 |
+
"name": "python",
|
| 81 |
+
"nbconvert_exporter": "python",
|
| 82 |
+
"pygments_lexer": "ipython3",
|
| 83 |
+
"version": "3.10.11"
|
| 84 |
+
}
|
| 85 |
+
},
|
| 86 |
+
"nbformat": 4,
|
| 87 |
+
"nbformat_minor": 5
|
| 88 |
+
}
|
app.py
CHANGED
|
@@ -6,6 +6,12 @@ import pickle
|
|
| 6 |
from PIL import Image
|
| 7 |
import os
|
| 8 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 9 |
|
| 10 |
## Define model
|
| 11 |
model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
|
|
@@ -13,14 +19,16 @@ processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch32")
|
|
| 13 |
tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-base-patch32")
|
| 14 |
|
| 15 |
#Open the precomputed embeddings
|
| 16 |
-
emb_filename = '
|
|
|
|
|
|
|
| 17 |
with open(emb_filename, 'rb') as fIn:
|
| 18 |
img_names, img_emb = pickle.load(fIn)
|
| 19 |
#print(f'img_emb: {print(img_emb)}')
|
| 20 |
#print(f'img_names: {print(img_names)}')
|
| 21 |
|
| 22 |
|
| 23 |
-
def search_text(query, top_k=
|
| 24 |
"""" Search an image based on the text query.
|
| 25 |
|
| 26 |
Args:
|
|
@@ -33,6 +41,8 @@ def search_text(query, top_k=1):
|
|
| 33 |
# First, we encode the query.
|
| 34 |
inputs = tokenizer([query], padding=True, return_tensors="pt")
|
| 35 |
query_emb = model.get_text_features(**inputs)
|
|
|
|
|
|
|
| 36 |
|
| 37 |
# Then, we use the util.semantic_search function, which computes the cosine-similarity
|
| 38 |
# between the query embedding and all image embeddings.
|
|
@@ -42,7 +52,8 @@ def search_text(query, top_k=1):
|
|
| 42 |
image=[]
|
| 43 |
for hit in hits:
|
| 44 |
#print(img_names[hit['corpus_id']])
|
| 45 |
-
object = Image.open(os.path.join("photos/", img_names[hit['corpus_id']]))
|
|
|
|
| 46 |
image.append(object)
|
| 47 |
#print(f'array length is: {len(image)}')
|
| 48 |
|
|
@@ -50,21 +61,18 @@ def search_text(query, top_k=1):
|
|
| 50 |
|
| 51 |
|
| 52 |
iface = gr.Interface(
|
| 53 |
-
title = "Text to Image using CLIP Model
|
| 54 |
-
description = "
|
| 55 |
-
article = "
|
| 56 |
fn=search_text,
|
| 57 |
inputs=[gr.Textbox(lines=4,
|
| 58 |
label="Write what you are looking for in an image...",
|
| 59 |
-
placeholder="Text Here..."),
|
| 60 |
-
gr.Slider(0, 5, step=1)],
|
| 61 |
outputs=[gr.Gallery(
|
| 62 |
label="Generated images", show_label=False, elem_id="gallery"
|
| 63 |
).style(grid=[2], height="auto")]
|
| 64 |
-
,examples=[
|
| 65 |
-
[("
|
| 66 |
-
[("
|
| 67 |
-
|
| 68 |
-
|
| 69 |
-
[("et høyt fjell"), 2]]
|
| 70 |
-
).launch(debug=True)
|
|
|
|
| 6 |
from PIL import Image
|
| 7 |
import os
|
| 8 |
|
| 9 |
+
# (Pdb) query_emb.shape
|
| 10 |
+
# torch.Size([1, 512])
|
| 11 |
+
# (Pdb) img_emb.shape
|
| 12 |
+
# (24996, 512)
|
| 13 |
+
|
| 14 |
+
|
| 15 |
|
| 16 |
## Define model
|
| 17 |
model = CLIPModel.from_pretrained("openai/clip-vit-base-patch32")
|
|
|
|
| 19 |
tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-base-patch32")
|
| 20 |
|
| 21 |
#Open the precomputed embeddings
|
| 22 |
+
emb_filename = 'lv-handbags.pkl'
|
| 23 |
+
# emb_filename = 'unsplash-25k-photos-embeddings.pkl'
|
| 24 |
+
|
| 25 |
with open(emb_filename, 'rb') as fIn:
|
| 26 |
img_names, img_emb = pickle.load(fIn)
|
| 27 |
#print(f'img_emb: {print(img_emb)}')
|
| 28 |
#print(f'img_names: {print(img_names)}')
|
| 29 |
|
| 30 |
|
| 31 |
+
def search_text(query, top_k=4):
|
| 32 |
"""" Search an image based on the text query.
|
| 33 |
|
| 34 |
Args:
|
|
|
|
| 41 |
# First, we encode the query.
|
| 42 |
inputs = tokenizer([query], padding=True, return_tensors="pt")
|
| 43 |
query_emb = model.get_text_features(**inputs)
|
| 44 |
+
|
| 45 |
+
# import pdb; pdb.set_trace()
|
| 46 |
|
| 47 |
# Then, we use the util.semantic_search function, which computes the cosine-similarity
|
| 48 |
# between the query embedding and all image embeddings.
|
|
|
|
| 52 |
image=[]
|
| 53 |
for hit in hits:
|
| 54 |
#print(img_names[hit['corpus_id']])
|
| 55 |
+
# object = Image.open(os.path.join("photos/", img_names[hit['corpus_id']]))
|
| 56 |
+
object = Image.open(os.path.join("lvphotos/", img_names[hit['corpus_id']]))
|
| 57 |
image.append(object)
|
| 58 |
#print(f'array length is: {len(image)}')
|
| 59 |
|
|
|
|
| 61 |
|
| 62 |
|
| 63 |
iface = gr.Interface(
|
| 64 |
+
title = "Hushh Text to Image using CLIP Model on Louis Vuitton API",
|
| 65 |
+
description = "Quick demo of using text to perform vector search on an image collection",
|
| 66 |
+
article = "TBD",
|
| 67 |
fn=search_text,
|
| 68 |
inputs=[gr.Textbox(lines=4,
|
| 69 |
label="Write what you are looking for in an image...",
|
| 70 |
+
placeholder="Text Here...")],
|
|
|
|
| 71 |
outputs=[gr.Gallery(
|
| 72 |
label="Generated images", show_label=False, elem_id="gallery"
|
| 73 |
).style(grid=[2], height="auto")]
|
| 74 |
+
,examples=[
|
| 75 |
+
[("Small Purse")],
|
| 76 |
+
[("Big Bag")],
|
| 77 |
+
]
|
| 78 |
+
).launch(debug=True)
|
|
|
|
|
|
crawl_lv.py
ADDED
|
@@ -0,0 +1,117 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from lxml import html
|
| 2 |
+
import requests
|
| 3 |
+
import os
|
| 4 |
+
|
| 5 |
+
client_id = os.environ['LV_CLIENT_ID']
|
| 6 |
+
client_secret = os.environ['LV_CLIENT_SECRET']
|
| 7 |
+
headers = {
|
| 8 |
+
'Content-Type':'application/json',
|
| 9 |
+
'authority':'api.louisvuitton.com',
|
| 10 |
+
'accept':'application/json, text/plain, */*',
|
| 11 |
+
'accept-language':'en-US,en;q=0.6',
|
| 12 |
+
'client_id':client_id,
|
| 13 |
+
'client_secret':client_secret,
|
| 14 |
+
'cookie':'ak_cc=US; OPTOUTMULTI=0:0%7Cc1:0%7Cc2:1%7Cc4:1%7Cc3:1; ATGID=anonymous; SGID=sb.springboot41-prd; SGID=.springboot41-prd; prevURL=; currentURL=https://www.louisvuitton.com/ajax/productsearch; storeLangCommerceHeader=eng-e1; geolocUserZone=eng-us; AKA_A2=A; _abck=94026E30A1FABEBFA844CBD6388965B8~0~YAAQnr8mF5/FGIeIAQAAjjKPkgpw8D5r3zC2HFECV0EQXRXPCoAQ+gYSqR/Sut2w/03toFhfVT9Yda45yFwqUGKStpIxbZAwPw0ooQplfv9eymgzFxyoYjEcqrD6rV/4OEgdCIov1wE0On3Z71z1v9UoZOisQgAlBEKsV0dYi02t6vutjUwi6f5T6N+h6SWX1l62T/QGwvxI13WHrWAOIsNJ1VJd/N3FiC/cKxVKskc3YPJf8tFZ25jOs2cUin5GUXWA7HuLb7dpffVxE0wp5vcOes47KXi9be6zRpbtfF+aHEjVkgPsOjznAFhN/X6FCHBTuJ5UvY2vHlWEIR8kW/pEW4zHm5bfQyaKKiBWQvHTXkeKRyhCnUSoRx9wZPB2dIcdY2igDmG06NT+NWYDPJtLoIU1I14uXhn+p8/w~-1~-1~-1; bm_sz=A8530E728A25BB2F984ED31AD5DF00A6~YAAQnr8mF6LFGIeIAQAAjjKPkhQ72plnxNz48wepUXjRYRETUBQ1oWkIiS8E0wS/+9NHmJzh9bagubSRjmSbTkSEEzyIbBsWTowVRBJBCiW6xO9lhJT/vmSLZtosV4g0eTOhRFoFwRrorwWUjGarPRTLozlk+KpZppYbt+EbdcyCdZNb95EUr6Za65FUi8FRSH02djUkhL5XlC3aebrVqtHfnG7uCJsWYBo+fnDJU1+mxQ8e1J+iTdq4ZdXsYuUuXZz3A0OJMy1JP5M/kKV4JKmIO89y3rgqZZB+xxNLbY+Su4yH7c/q2+s=~3556656~3686978; lv-dispatch=eng-us; consent_ecom_us=functional:1|analytics:0|customization:0|advertising:0; qb_dnt=2; ak_bmsc=589EDDF01ED59E65EA72F7393A895F31~000000000000000000000000000000~YAAQnr8mFxbGGIeIAQAATzaPkhR5K7vu8hiBPm/G/uXQB2vcY/Q4eGJWL+r7GNyViebDR/5XNvUSus0l/5Uhpgq+sHzuQR7L7aYzbFREYRNqvAZ0ngto1AvbYgwL8xA7OJM+D03m8i/BMKZHk++/aC3UFmk/RYNOKIv8p4HjlGM22auYotHx2mlWq8DTZPj1z77noO3WrzpYdEirg6xSV8havW9BHABzNmP3Cfnt3xxVq3y3bMNDcpiXy2+eAJ7eX5UNVa/Rj+P75LGxaPAv4AsXiphTgX6rMKt5T6OAvLMX6vdLLCpZYvDxvtctIZ1o7p1kgBdympPZFvVTPcmDtKrzh9sABV0v2Lls8NzLbbdf2k4B5uyUfy0fQL60zUUZgrlSOoFzgJgQviOHvoVQbqFdXCFyiH+fBjKltnlQXKJ9f0Y5JOjnBIkUHCJ9fUHINiwqt9h2cw5daORuAKdfQpsi3Z3cSVM7cIdb/Dfu0f2vu+K1GOxNv1+NH0KlwbAxMA==; ATG_SESSION_ID=GCUqx-HVSh3KVpIaIX+L30So.front41-prd; _dynSessConf=-86995900442046424; JSESSIONID=GCUqx-HVSh3KVpIaIX+L30So.front41-prd; PIM-SESSION-ID=HBqQRDXDzoWH4e2V; bm_sv=CF0A04BDB7486115978F40C364AB5E38~YAAQnr8mF1opHYeIAQAAT1G5khS7D+LGov3Y87+pRE+B0F86Y3tJjyDrwszLeFA06ZC1s/so8vDcDtmB0VrCDU1N+jlXvFNpGfEkhJTiyQrFAkZq2i57xih3Y4Oe7kDnWY6TqYj05c7rqHmBOUw8+XtLNLJAzSPx+0cKcLqujkgpHiI1xPuO1N27mPXK0SMc2DLsF9MJZa0EqlH8YtoHBgDTz/q2R9Q5g28FJHVuw3SqLHdFDaHO2dML6P/eVsRDeYR3XTd8OQ==~1; lv-dispatch-url=https://us.louisvuitton.com/eng-us/women/handbags/all-handbags/_/N-tfr7qdp; utag_main=_sn:6$_se:25$_ss:0$_st:1686090605436$dc_visit:2$v_id:01884a527895001827510ebf5e3504075002b06d00a61$ses_id:1686086038612%3Bexp-session$_pn:10%3Bexp-session',
|
| 15 |
+
'origin':'https://us.louisvuitton.com',
|
| 16 |
+
'referer':'https://us.louisvuitton.com/',
|
| 17 |
+
'sec-ch-ua':'"Brave";v="113", "Chromium";v="113", "Not-A.Brand";v="24"',
|
| 18 |
+
'sec-ch-ua-mobile':'?0',
|
| 19 |
+
'sec-ch-ua-platform':'"macOS"',
|
| 20 |
+
'sec-fetch-dest':'empty',
|
| 21 |
+
'sec-fetch-mode':'cors',
|
| 22 |
+
'sec-fetch-site':'same-site',
|
| 23 |
+
'sec-gpc':'1',
|
| 24 |
+
'user-agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0',
|
| 25 |
+
}
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
url = 'https://us.louisvuitton.com/eng-us/homepage'
|
| 29 |
+
response = requests.get(url, headers=headers)
|
| 30 |
+
print(len(response.text))
|
| 31 |
+
tree = html.fromstring(response.text)
|
| 32 |
+
|
| 33 |
+
|
| 34 |
+
sitemap_paths = tree.xpath('//*[@id="header"]//a/@href')
|
| 35 |
+
|
| 36 |
+
categories = {}
|
| 37 |
+
for p in sitemap_paths:
|
| 38 |
+
parts = p.split("/")
|
| 39 |
+
if parts[-1].startswith("N-") :
|
| 40 |
+
categories[parts[-3]]= {"code":parts[-1][2:]}
|
| 41 |
+
|
| 42 |
+
|
| 43 |
+
import requests
|
| 44 |
+
for cat_key in categories.keys():
|
| 45 |
+
print(cat_key)
|
| 46 |
+
code = categories[cat_key]["code"]
|
| 47 |
+
|
| 48 |
+
url = f'https://api.louisvuitton.com/eco-eu/search-merch-eapi/v1/eng-us/plp/products/{code}-ay1ygzo25?page='
|
| 49 |
+
print(url)
|
| 50 |
+
nbPages = 100
|
| 51 |
+
page = 0
|
| 52 |
+
all_hits = []
|
| 53 |
+
|
| 54 |
+
while page < nbPages:
|
| 55 |
+
response = requests.get(url + str(page), headers=headers)
|
| 56 |
+
res = response.json()
|
| 57 |
+
if "nbPages" in res:
|
| 58 |
+
nbPages = res["nbPages"]
|
| 59 |
+
all_hits.extend(res["hits"])
|
| 60 |
+
print(res["page"], len(all_hits))
|
| 61 |
+
page = page + 1
|
| 62 |
+
|
| 63 |
+
|
| 64 |
+
recs = []
|
| 65 |
+
misses = []
|
| 66 |
+
for hit in all_hits:
|
| 67 |
+
try:
|
| 68 |
+
rec = {}
|
| 69 |
+
for key in ["productId", "name", "url", "disambiguatingDescription"]:
|
| 70 |
+
rec[key] = hit[key]
|
| 71 |
+
rec["image"] = hit["image"][0]["contentUrl"]
|
| 72 |
+
recs.append(rec)
|
| 73 |
+
except:
|
| 74 |
+
misses.append(rec)
|
| 75 |
+
print(hit)
|
| 76 |
+
categories[cat_key]["urls"] = recs
|
| 77 |
+
categories[cat_key]["misses"] = misses
|
| 78 |
+
|
| 79 |
+
flatten = []
|
| 80 |
+
for cat in categories.keys():
|
| 81 |
+
info = categories[cat]
|
| 82 |
+
for rec in categories[cat]["urls"]:
|
| 83 |
+
doc = {}
|
| 84 |
+
doc["productId"] = rec["productId"]
|
| 85 |
+
doc["category"] = cat
|
| 86 |
+
doc["category_code"] = info["code"]
|
| 87 |
+
doc["name"] = rec["name"]
|
| 88 |
+
doc["url"] = rec["url"]
|
| 89 |
+
doc["disambiguatingDescription"] = rec["disambiguatingDescription"]
|
| 90 |
+
flatten.append(doc)
|
| 91 |
+
|
| 92 |
+
import pandas as pd
|
| 93 |
+
dat = pd.DataFrame(flatten)
|
| 94 |
+
size = str(400)
|
| 95 |
+
dat['image_fix'] = dat['url'].str.replace("{IMG_HEIGHT}", size).str.replace("{IMG_WIDTH}", size)
|
| 96 |
+
|
| 97 |
+
import os
|
| 98 |
+
for rec in dat.itertuples():
|
| 99 |
+
os.system(f"""
|
| 100 |
+
curl '{rec.image_fix}'\
|
| 101 |
+
-H 'authority: us.louisvuitton.com' \
|
| 102 |
+
-H 'accept: image/avif,image/webp,image/apng,image/svg+xml,image/*,*/*;q=0.8' \
|
| 103 |
+
-H 'accept-language: en-US,en;q=0.9' \
|
| 104 |
+
-H 'cache-control: no-cache' \
|
| 105 |
+
-H 'cookie: ak_cc=US; OPTOUTMULTI=0:0%7Cc1:0%7Cc2:1%7Cc4:1%7Cc3:1; ATGID=anonymous; SGID=sb.springboot41-prd; prevURL=; currentURL=https://www.louisvuitton.com/ajax/productsearch; storeLangCommerceHeader=eng-e1; geolocUserZone=eng-us; AKA_A2=A; _abck=94026E30A1FABEBFA844CBD6388965B8~0~YAAQnr8mF5/FGIeIAQAAjjKPkgpw8D5r3zC2HFECV0EQXRXPCoAQ+gYSqR/Sut2w/03toFhfVT9Yda45yFwqUGKStpIxbZAwPw0ooQplfv9eymgzFxyoYjEcqrD6rV/4OEgdCIov1wE0On3Z71z1v9UoZOisQgAlBEKsV0dYi02t6vutjUwi6f5T6N+h6SWX1l62T/QGwvxI13WHrWAOIsNJ1VJd/N3FiC/cKxVKskc3YPJf8tFZ25jOs2cUin5GUXWA7HuLb7dpffVxE0wp5vcOes47KXi9be6zRpbtfF+aHEjVkgPsOjznAFhN/X6FCHBTuJ5UvY2vHlWEIR8kW/pEW4zHm5bfQyaKKiBWQvHTXkeKRyhCnUSoRx9wZPB2dIcdY2igDmG06NT+NWYDPJtLoIU1I14uXhn+p8/w~-1~-1~-1; bm_sz=A8530E728A25BB2F984ED31AD5DF00A6~YAAQnr8mF6LFGIeIAQAAjjKPkhQ72plnxNz48wepUXjRYRETUBQ1oWkIiS8E0wS/+9NHmJzh9bagubSRjmSbTkSEEzyIbBsWTowVRBJBCiW6xO9lhJT/vmSLZtosV4g0eTOhRFoFwRrorwWUjGarPRTLozlk+KpZppYbt+EbdcyCdZNb95EUr6Za65FUi8FRSH02djUkhL5XlC3aebrVqtHfnG7uCJsWYBo+fnDJU1+mxQ8e1J+iTdq4ZdXsYuUuXZz3A0OJMy1JP5M/kKV4JKmIO89y3rgqZZB+xxNLbY+Su4yH7c/q2+s=~3556656~3686978; lv-dispatch=eng-us; consent_ecom_us=functional:1|analytics:0|customization:0|advertising:0; qb_dnt=2; ak_bmsc=589EDDF01ED59E65EA72F7393A895F31~000000000000000000000000000000~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; PIM-SESSION-ID=HBqQRDXDzoWH4e2V; lv-dispatch-url=https://us.louisvuitton.com/eng-us/women/handbags/all-handbags/_/N-tfr7qdp; utag_main=_sn:6$_se:28$_ss:0$_st:1686090718084$dc_visit:2$v_id:01884a527895001827510ebf5e3504075002b06d00a61$ses_id:1686086038612%3Bexp-session$_pn:11%3Bexp-session; anonymous_session=true; ATG_SESSION_ID=B-8233ZEyNVjFobJCNa+2INd.front41-prd; _dynSessConf=2255588875954406228; JSESSIONID=B-8233ZEyNVjFobJCNa+2INd.front41-prd; bm_sv=CF0A04BDB7486115978F40C364AB5E38~YAAQnr8mF1xwHYeIAQAAlSm7khS9xE3iX2eAH+anrXfnlQ7v8oUsEA0z/MTkPXZnzBAvGACc64Rw7A1Y5WpGYwhqMubbtv5eueVsxuxlhE/aJNZtgpkk/epZage/P7W27HdoknmpCXGdYaFsYNTqrcCrNXOS/DUkUdvE6OjHGDg6c+05MfuLiHR+zMzGM/mZzxWzV3ruLRv6toIGPskD/LkRrOU0j8B7alLLaAhQKTvZVFPlcgbho2BHD8rHcNL0E7h2pvdGvA==~1' \
|
| 106 |
+
-H 'pragma: no-cache' \
|
| 107 |
+
-H 'referer: https://us.louisvuitton.com/eng-us/products/twist-belt-chain-wallet-epi-nvprod1740047v/M68560' \
|
| 108 |
+
-H 'sec-ch-ua: "Not.A/Brand";v="8", "Chromium";v="114", "Brave";v="114"' \
|
| 109 |
+
-H 'sec-ch-ua-mobile: ?0' \
|
| 110 |
+
-H 'sec-ch-ua-platform: "macOS"' \
|
| 111 |
+
-H 'sec-fetch-dest: image' \
|
| 112 |
+
-H 'sec-fetch-mode: no-cors' \
|
| 113 |
+
-H 'sec-fetch-site: same-origin' \
|
| 114 |
+
-H 'sec-gpc: 1' \
|
| 115 |
+
-H 'user-agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36' \
|
| 116 |
+
--compressed --output 'images/{rec.productId}.png'
|
| 117 |
+
""")
|