├── db.sqlite3 ├── firstApp ├── __init__.py ├── __pycache__ │ ├── __init__.cpython-36.pyc │ ├── admin.cpython-36.pyc │ ├── models.cpython-36.pyc │ └── views.cpython-36.pyc ├── admin.py ├── apps.py ├── migrations │ ├── __init__.py │ └── __pycache__ │ │ └── __init__.cpython-36.pyc ├── models.py ├── static │ ├── css │ │ ├── animate.css │ │ ├── bootstrap.min.css │ │ ├── font-awesome.min.css │ │ ├── owl.carousel.css │ │ ├── owl.theme.default.min.css │ │ └── tooplate-style.css │ └── js │ │ ├── bootstrap.min.js │ │ ├── custom.js │ │ ├── jquery.js │ │ ├── jquery.stellar.min.js │ │ ├── jquery.sticky.js │ │ ├── owl.carousel.min.js │ │ ├── smoothscroll.js │ │ └── wow.min.js ├── tests.py └── views.py ├── imageNetProj ├── __init__.py ├── __pycache__ │ ├── __init__.cpython-36.pyc │ ├── settings.cpython-36.pyc │ ├── urls.cpython-36.pyc │ └── wsgi.cpython-36.pyc ├── asgi.py ├── settings.py ├── urls.py └── wsgi.py ├── manage.py ├── media ├── bird-article-s.png ├── bird-article-s_5I9dh1o.png ├── bird-article-s_90vhIi8.png ├── bird-article-s_Zabcwp9.png ├── bird-article-s_baZJLJf.png ├── sumatran-tiger-wz-gsmp-m.jpg ├── sumatran-tiger-wz-gsmp-m_NT1LDhb.jpg └── sumatran-tiger-wz-gsmp-m_dD2aCPU.jpg ├── models ├── MobileNetModelImagenet.h5 └── imagenet_classes.json ├── notebook ├── .ipynb_checkpoints │ ├── dummy model for MPG-checkpoint.ipynb │ ├── mobilenet Model-checkpoint.ipynb │ └── mongodb connection-checkpoint.ipynb ├── bird-article-s.png ├── imagenet_classes.json ├── mobilenet Model.ipynb └── sumatran-tiger-wz-gsmp-m.jpg ├── req,txt └── template ├── headerPage.html ├── index.html └── viewDB.html /db.sqlite3: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/db.sqlite3 -------------------------------------------------------------------------------- /firstApp/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/firstApp/__init__.py -------------------------------------------------------------------------------- /firstApp/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/firstApp/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /firstApp/__pycache__/admin.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/firstApp/__pycache__/admin.cpython-36.pyc -------------------------------------------------------------------------------- /firstApp/__pycache__/models.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/firstApp/__pycache__/models.cpython-36.pyc -------------------------------------------------------------------------------- /firstApp/__pycache__/views.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/firstApp/__pycache__/views.cpython-36.pyc -------------------------------------------------------------------------------- /firstApp/admin.py: -------------------------------------------------------------------------------- 1 | from django.contrib import admin 2 | 3 | # Register your models here. 4 | -------------------------------------------------------------------------------- /firstApp/apps.py: -------------------------------------------------------------------------------- 1 | from django.apps import AppConfig 2 | 3 | 4 | class FirstappConfig(AppConfig): 5 | name = 'firstApp' 6 | -------------------------------------------------------------------------------- /firstApp/migrations/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/firstApp/migrations/__init__.py -------------------------------------------------------------------------------- /firstApp/migrations/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/firstApp/migrations/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /firstApp/models.py: -------------------------------------------------------------------------------- 1 | from django.db import models 2 | 3 | # Create your models here. 4 | -------------------------------------------------------------------------------- /firstApp/static/css/font-awesome.min.css: -------------------------------------------------------------------------------- 1 | /*! 2 | * Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome 3 | * License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License) 4 | */@font-face{font-family:'FontAwesome';src:url('../fonts/fontawesome-webfont.eot?v=4.7.0');src:url('../fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') 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0, 0, 0);border:0}.sr-only-focusable:active,.sr-only-focusable:focus{position:static;width:auto;height:auto;margin:0;overflow:visible;clip:auto} 5 | -------------------------------------------------------------------------------- /firstApp/static/css/owl.carousel.css: -------------------------------------------------------------------------------- 1 | /** 2 | * Owl Carousel v2.2.1 3 | * Copyright 2013-2017 David Deutsch 4 | * Licensed under () 5 | */ 6 | /* 7 | * Owl Carousel - Core 8 | */ 9 | .owl-carousel { 10 | display: none; 11 | width: 100%; 12 | -webkit-tap-highlight-color: transparent; 13 | /* position relative and z-index fix webkit rendering fonts issue */ 14 | position: relative; 15 | z-index: 1; } 16 | .owl-carousel .owl-stage { 17 | position: relative; 18 | -ms-touch-action: pan-Y; 19 | -moz-backface-visibility: hidden; 20 | /* fix firefox animation glitch */ } 21 | .owl-carousel .owl-stage:after { 22 | content: "."; 23 | display: block; 24 | clear: both; 25 | visibility: hidden; 26 | line-height: 0; 27 | height: 0; } 28 | .owl-carousel .owl-stage-outer { 29 | position: relative; 30 | overflow: hidden; 31 | /* fix for flashing background */ 32 | -webkit-transform: translate3d(0px, 0px, 0px); } 33 | .owl-carousel .owl-wrapper, 34 | .owl-carousel .owl-item { 35 | -webkit-backface-visibility: hidden; 36 | -moz-backface-visibility: hidden; 37 | -ms-backface-visibility: hidden; 38 | -webkit-transform: translate3d(0, 0, 0); 39 | -moz-transform: translate3d(0, 0, 0); 40 | -ms-transform: translate3d(0, 0, 0); } 41 | .owl-carousel .owl-item { 42 | position: relative; 43 | min-height: 1px; 44 | float: left; 45 | -webkit-backface-visibility: hidden; 46 | -webkit-tap-highlight-color: transparent; 47 | -webkit-touch-callout: none; } 48 | .owl-carousel .owl-item img { 49 | display: block; 50 | width: 100%; } 51 | .owl-carousel .owl-nav.disabled, 52 | .owl-carousel .owl-dots.disabled { 53 | display: none; } 54 | .owl-carousel .owl-nav .owl-prev, 55 | .owl-carousel .owl-nav .owl-next, 56 | .owl-carousel .owl-dot { 57 | cursor: pointer; 58 | cursor: hand; 59 | -webkit-user-select: none; 60 | -khtml-user-select: none; 61 | -moz-user-select: none; 62 | -ms-user-select: none; 63 | user-select: none; } 64 | .owl-carousel.owl-loaded { 65 | display: block; } 66 | .owl-carousel.owl-loading { 67 | opacity: 0; 68 | display: block; } 69 | .owl-carousel.owl-hidden { 70 | opacity: 0; } 71 | .owl-carousel.owl-refresh .owl-item { 72 | visibility: hidden; } 73 | .owl-carousel.owl-drag .owl-item { 74 | -webkit-user-select: none; 75 | -moz-user-select: none; 76 | -ms-user-select: none; 77 | user-select: none; } 78 | .owl-carousel.owl-grab { 79 | cursor: move; 80 | cursor: grab; } 81 | .owl-carousel.owl-rtl { 82 | direction: rtl; } 83 | .owl-carousel.owl-rtl .owl-item { 84 | float: right; } 85 | 86 | /* No Js */ 87 | .no-js .owl-carousel { 88 | display: block; } 89 | 90 | /* 91 | * Owl Carousel - Animate Plugin 92 | */ 93 | .owl-carousel .animated { 94 | animation-duration: 1000ms; 95 | animation-fill-mode: both; } 96 | 97 | .owl-carousel .owl-animated-in { 98 | z-index: 0; } 99 | 100 | .owl-carousel .owl-animated-out { 101 | z-index: 1; } 102 | 103 | .owl-carousel .fadeOut { 104 | animation-name: fadeOut; } 105 | 106 | @keyframes fadeOut { 107 | 0% { 108 | opacity: 1; } 109 | 100% { 110 | opacity: 0; } } 111 | 112 | /* 113 | * Owl Carousel - Auto Height Plugin 114 | */ 115 | .owl-height { 116 | transition: height 500ms ease-in-out; } 117 | 118 | /* 119 | * Owl Carousel - Lazy Load Plugin 120 | */ 121 | .owl-carousel .owl-item .owl-lazy { 122 | opacity: 0; 123 | transition: opacity 400ms ease; } 124 | 125 | .owl-carousel .owl-item img.owl-lazy { 126 | transform-style: preserve-3d; } 127 | 128 | /* 129 | * Owl Carousel - Video Plugin 130 | */ 131 | .owl-carousel .owl-video-wrapper { 132 | position: relative; 133 | height: 100%; 134 | background: #000; } 135 | 136 | .owl-carousel .owl-video-play-icon { 137 | position: absolute; 138 | height: 80px; 139 | width: 80px; 140 | left: 50%; 141 | top: 50%; 142 | margin-left: -40px; 143 | margin-top: -40px; 144 | background: url("owl.video.play.png") no-repeat; 145 | cursor: pointer; 146 | z-index: 1; 147 | -webkit-backface-visibility: hidden; 148 | transition: transform 100ms ease; } 149 | 150 | .owl-carousel .owl-video-play-icon:hover { 151 | -ms-transform: scale(1.3, 1.3); 152 | transform: scale(1.3, 1.3); } 153 | 154 | .owl-carousel .owl-video-playing .owl-video-tn, 155 | .owl-carousel .owl-video-playing .owl-video-play-icon { 156 | display: none; } 157 | 158 | .owl-carousel .owl-video-tn { 159 | opacity: 0; 160 | height: 100%; 161 | background-position: center center; 162 | background-repeat: no-repeat; 163 | background-size: contain; 164 | transition: opacity 400ms ease; } 165 | 166 | .owl-carousel .owl-video-frame { 167 | position: relative; 168 | z-index: 1; 169 | height: 100%; 170 | width: 100%; } 171 | -------------------------------------------------------------------------------- /firstApp/static/css/owl.theme.default.min.css: -------------------------------------------------------------------------------- 1 | /** 2 | * Owl Carousel v2.2.1 3 | * Copyright 2013-2017 David Deutsch 4 | * Licensed under () 5 | */ 6 | .owl-theme .owl-dots,.owl-theme .owl-nav{text-align:center;-webkit-tap-highlight-color:transparent}.owl-theme .owl-nav{margin-top:10px}.owl-theme .owl-nav [class*=owl-]{color:#FFF;font-size:14px;margin:5px;padding:4px 7px;background:#D6D6D6;display:inline-block;cursor:pointer;border-radius:3px}.owl-theme .owl-nav [class*=owl-]:hover{background:#869791;color:#FFF;text-decoration:none}.owl-theme .owl-nav .disabled{opacity:.5;cursor:default}.owl-theme .owl-nav.disabled+.owl-dots{margin-top:10px}.owl-theme .owl-dots .owl-dot{display:inline-block;zoom:1}.owl-theme .owl-dots .owl-dot span{width:10px;height:10px;margin:5px 7px;background:#D6D6D6;display:block;-webkit-backface-visibility:visible;transition:opacity .2s ease;border-radius:30px}.owl-theme .owl-dots .owl-dot.active span,.owl-theme .owl-dots .owl-dot:hover span{background:#869791} -------------------------------------------------------------------------------- /firstApp/static/css/tooplate-style.css: -------------------------------------------------------------------------------- 1 | /* 2 | 3 | Template 2098 Health 4 | 5 | http://www.tooplate.com/view/2098-health 6 | 7 | */ 8 | 9 | @import url('https://fonts.googleapis.com/css?family=Poppins:400,500,600'); 10 | 11 | body { 12 | background: #ffffff; 13 | font-family: 'Poppins', sans-serif; 14 | overflow-x: hidden; 15 | } 16 | 17 | 18 | /*--------------------------------------- 19 | TYPOGRAPHY 20 | -----------------------------------------*/ 21 | 22 | h1,h2,h3,h4,h5,h6 { 23 | font-weight: 600; 24 | line-height: inherit; 25 | } 26 | 27 | h1,h2,h3,h4 { 28 | letter-spacing: -1px; 29 | } 30 | 31 | h5 { 32 | font-weight: 500; 33 | } 34 | 35 | h1 { 36 | color: #252525; 37 | font-size: 5em; 38 | } 39 | 40 | h2 { 41 | color: #272727; 42 | font-size: 3em; 43 | padding-bottom: 10px; 44 | } 45 | 46 | h3 { 47 | font-size: 1.8em; 48 | line-height: 1.2em; 49 | margin-bottom: 0; 50 | } 51 | 52 | h4 { 53 | color: #454545; 54 | font-size: 1.8em; 55 | padding-bottom: 2px; 56 | } 57 | 58 | h6 { 59 | letter-spacing: 0; 60 | font-weight: normal; 61 | } 62 | 63 | p { 64 | color: #757575; 65 | font-size: 14px; 66 | font-weight: normal; 67 | line-height: 24px; 68 | } 69 | 70 | 71 | /*--------------------------------------- 72 | GENERAL 73 | -----------------------------------------*/ 74 | 75 | html{ 76 | -webkit-font-smoothing: antialiased; 77 | } 78 | 79 | a { 80 | color: #252525; 81 | -webkit-transition: 0.5s; 82 | transition: 0.5s; 83 | text-decoration: none !important; 84 | } 85 | 86 | a:hover, a:active, a:focus { 87 | color: #a5c422; 88 | outline: none; 89 | } 90 | 91 | ::-webkit-scrollbar{ 92 | width: 8px; 93 | height: 8px; 94 | } 95 | 96 | ::-webkit-scrollbar-thumb { 97 | cursor: pointer; 98 | background: #000000; 99 | } 100 | 101 | .section-title { 102 | padding-bottom: 20px; 103 | } 104 | 105 | .section-title h2 { 106 | margin-top: 0; 107 | } 108 | 109 | .section-btn { 110 | background: #a5c422; 111 | border: 0; 112 | border-radius: 3px; 113 | color: #ffffff; 114 | font-size: inherit; 115 | font-weight: 500; 116 | padding: 14px 20px; 117 | transition: transform 0.1s ease-in; 118 | transform: translateX(0); 119 | } 120 | 121 | .section-btn:hover { 122 | transform: translateY(-5px); 123 | } 124 | 125 | .text-align-right { 126 | text-align: right; 127 | } 128 | 129 | .text-align-center { 130 | text-align: center; 131 | } 132 | 133 | .border-top { 134 | border-top: 1px solid #f2f2f2; 135 | margin-top: 4em; 136 | padding-top: 2.5em; 137 | } 138 | 139 | .btn-gray { 140 | background: #393939; 141 | } 142 | 143 | .btn-blue { 144 | background: #4267b2; 145 | } 146 | 147 | .news-thumb { 148 | background: #ffffff; 149 | border-radius: 10px; 150 | } 151 | .news-thumb img { 152 | border-radius: 10px 10px 0 0; 153 | } 154 | 155 | .news-info { 156 | padding: 30px; 157 | text-align: left; 158 | } 159 | .news-info span { 160 | display: block; 161 | letter-spacing: 0.5px; 162 | } 163 | .news-info h3 { 164 | margin-top: 10px; 165 | margin-bottom: 10px; 166 | } 167 | 168 | .author { 169 | border-top: 1px solid #f0f0f0; 170 | padding-top: 1.5em; 171 | margin-top: 2em; 172 | } 173 | .author img, 174 | .author .author-info { 175 | display: inline-block; 176 | vertical-align: top; 177 | } 178 | .author-info h5 { 179 | margin-bottom: 0; 180 | } 181 | .author img { 182 | border-radius: 100%; 183 | width: 50px; 184 | height: 50px; 185 | margin-right: 10px; 186 | } 187 | 188 | 189 | #about, #team, #news, 190 | #news-detail { 191 | position: relative; 192 | padding-top: 100px; 193 | padding-bottom: 100px; 194 | } 195 | 196 | #news, #service { 197 | text-align: center; 198 | } 199 | 200 | #google-map { 201 | line-height: 0; 202 | margin: 0; 203 | padding: 0; 204 | } 205 | 206 | 207 | /*--------------------------------------- 208 | PRE LOADER 209 | -----------------------------------------*/ 210 | 211 | .preloader { 212 | position: fixed; 213 | top: 0; 214 | left: 0; 215 | width: 100%; 216 | height: 100%; 217 | z-index: 99999; 218 | display: flex; 219 | flex-flow: row nowrap; 220 | justify-content: center; 221 | align-items: center; 222 | background: none repeat scroll 0 0 #ffffff; 223 | } 224 | 225 | .spinner { 226 | border: 1px solid transparent; 227 | border-radius: 3px; 228 | position: relative; 229 | } 230 | 231 | .spinner:before { 232 | content: ''; 233 | box-sizing: border-box; 234 | position: absolute; 235 | top: 50%; 236 | left: 50%; 237 | width: 45px; 238 | height: 45px; 239 | margin-top: -10px; 240 | margin-left: -10px; 241 | border-radius: 50%; 242 | border: 1px solid #575757; 243 | border-top-color: #ffffff; 244 | animation: spinner .9s linear infinite; 245 | } 246 | 247 | @-webkit-@keyframes spinner { 248 | to {transform: rotate(360deg);} 249 | } 250 | 251 | @keyframes spinner { 252 | to {transform: rotate(360deg);} 253 | } 254 | 255 | 256 | 257 | /*--------------------------------------- 258 | MENU 259 | -----------------------------------------*/ 260 | 261 | header { 262 | background: #ffffff; 263 | border-bottom: 1px solid #f2f2f2; 264 | display: flex; 265 | height: 45px; 266 | } 267 | 268 | header .col-md-8 { 269 | padding-right: 0; 270 | } 271 | 272 | header p, 273 | header span { 274 | font-size: 12px; 275 | line-height: 24px; 276 | padding-top: 12px; 277 | } 278 | 279 | header a, 280 | header span { 281 | color: #747474; 282 | } 283 | 284 | header span { 285 | font-weight: 500; 286 | display: inline-block; 287 | padding: 11px 15px; 288 | } 289 | 290 | header span.date-icon { 291 | border-left: 1px solid #f2f2f2; 292 | border-right: 1px solid #f2f2f2; 293 | padding-right: 19px; 294 | padding-left: 19px; 295 | } 296 | 297 | header span i { 298 | color: #a5c422; 299 | margin-right: 5px; 300 | } 301 | 302 | 303 | 304 | /*--------------------------------------- 305 | MENU 306 | -----------------------------------------*/ 307 | 308 | .navbar-default { 309 | background: #ffffff; 310 | box-shadow: 0 2px 8px rgba(0,0,0,.075); 311 | border: none; 312 | margin-bottom: 0; 313 | padding: 10px; 314 | } 315 | 316 | .navbar-default .navbar-brand { 317 | color: #393939; 318 | font-weight: 500; 319 | } 320 | 321 | .navbar-default .navbar-brand .fa { 322 | color: #a5c422; 323 | } 324 | 325 | .navbar-default .navbar-nav li.appointment-btn { 326 | margin: 3px 0 0 20px; 327 | } 328 | 329 | .navbar-default .navbar-nav li.appointment-btn a { 330 | background: #a5c422; 331 | border-radius: 3px; 332 | color: #ffffff; 333 | font-weight: 600; 334 | padding-top: 12px; 335 | padding-bottom: 12px; 336 | } 337 | 338 | .navbar-default .navbar-nav li.appointment-btn a:hover { 339 | background: #4267b2; 340 | color: #ffffff !important; 341 | } 342 | 343 | .navbar-default .navbar-nav li a { 344 | color: #555555; 345 | font-size: 12px; 346 | font-weight: 500; 347 | padding-right: 20px; 348 | padding-left: 20px; 349 | -webkit-transition: all ease-in-out 0.4s; 350 | transition: all ease-in-out 0.4s; 351 | } 352 | 353 | .navbar-default .navbar-nav > li a:hover { 354 | color: #393939 !important; 355 | } 356 | 357 | .navbar-default .navbar-nav > li > a:hover, 358 | .navbar-default .navbar-nav > li > a:focus { 359 | color: #555555; 360 | background-color: transparent; 361 | } 362 | 363 | .navbar-default .navbar-nav > .active > a, 364 | .navbar-default .navbar-nav > .active > a:hover, 365 | .navbar-default .navbar-nav > .active > a:focus { 366 | color: #393939; 367 | background-color: transparent; 368 | } 369 | 370 | .navbar-default .navbar-toggle { 371 | border: none; 372 | padding-top: 10px; 373 | } 374 | 375 | .navbar-default .navbar-toggle .icon-bar { 376 | background: #393939; 377 | border-color: transparent; 378 | } 379 | 380 | .navbar-default .navbar-toggle:hover, 381 | .navbar-default .navbar-toggle:focus { 382 | background-color: transparent; 383 | } 384 | 385 | 386 | 387 | /*--------------------------------------- 388 | HOME 389 | -----------------------------------------*/ 390 | 391 | #home h1 { 392 | color: #ffffff; 393 | padding-bottom: 10px; 394 | margin-top: 0; 395 | } 396 | 397 | #home h3 { 398 | color: #ffffff; 399 | font-size: 14px; 400 | font-weight: normal; 401 | line-height: inherit; 402 | letter-spacing: 3px; 403 | text-transform: uppercase; 404 | margin: 0; 405 | } 406 | 407 | .slider .container { 408 | width: 100%; 409 | } 410 | 411 | .slider .owl-dots { 412 | position: absolute; 413 | top: 575px; 414 | width: 100%; 415 | justify-content: center; 416 | } 417 | 418 | .owl-theme .owl-dots .owl-dot span { 419 | width: 8px; 420 | height: 8px; 421 | margin: 5px 7px; 422 | border: 2px solid #d9d9d9; 423 | background: transparent; 424 | display: block; 425 | -webkit-backface-visibility: visible; 426 | transition: opacity 200ms ease; 427 | border-radius: 30px; 428 | } 429 | 430 | .owl-theme .owl-dots .owl-dot.active span, .owl-theme .owl-dots .owl-dot:hover span { 431 | background-color: #ffffff; 432 | border-color: transparent; 433 | } 434 | 435 | .slider .caption { 436 | display: flex; 437 | justify-content: center; 438 | flex-direction: column; 439 | text-align: center; 440 | background-color: rgba(20,20,20,0.2); 441 | height: 100%; 442 | color: #fff; 443 | cursor: e-resize; 444 | } 445 | 446 | .slider .item { 447 | background-position: inherit; 448 | background-repeat: no-repeat; 449 | background-attachment: local; 450 | background-size: cover; 451 | height: 650px; 452 | } 453 | 454 | .slider .item-first { 455 | background-image: url(../images/slider1.jpg); 456 | } 457 | 458 | .slider .item-second { 459 | background-image: url(../images/slider2.jpg); 460 | } 461 | 462 | .slider .item-third { 463 | background-image: url(../images/slider3.jpg); 464 | } 465 | 466 | 467 | /*--------------------------------------- 468 | ABOUT 469 | -----------------------------------------*/ 470 | 471 | #about { 472 | background: url('../images/about-bg.jpg') no-repeat top center; 473 | background-size: cover; 474 | padding-top: 150px; 475 | padding-bottom: 150px; 476 | } 477 | 478 | .profile img, 479 | .profile figcaption { 480 | display: inline-block; 481 | vertical-align: top; 482 | margin-top: 1em; 483 | } 484 | .profile img { 485 | border-radius: 100%; 486 | width: 65px; 487 | height: 65px; 488 | margin-right: 1em; 489 | } 490 | .profile figcaption h3 { 491 | margin-top: 0; 492 | } 493 | 494 | #about h6 { 495 | color: #858585; 496 | margin: 0; 497 | } 498 | 499 | 500 | 501 | /*--------------------------------------- 502 | TEAM MEMBERS 503 | -----------------------------------------*/ 504 | 505 | .team-thumb { 506 | background-color: #f9f9f9; 507 | border-radius: 0 0 10px 10px; 508 | position: relative; 509 | overflow: hidden; 510 | cursor: pointer; 511 | } 512 | 513 | .team-info { 514 | padding: 20px 30px 0 30px; 515 | } 516 | 517 | .team-contact-info { 518 | border-top: 1px solid #e9e9e9; 519 | padding-top: 1.2em; 520 | margin-top: 1.5em; 521 | } 522 | 523 | .team-contact-info .fa { 524 | margin-right: 5px; 525 | display: inline-block; 526 | } 527 | 528 | .team-contact-info p { 529 | margin-bottom: 2px; 530 | } 531 | 532 | .team-contact-info a { 533 | color: #757575; 534 | } 535 | 536 | .team-thumb .social-icon li { 537 | font-weight: 500; 538 | } 539 | 540 | .team-thumb .social-icon li a { 541 | background: #ffffff; 542 | border-radius: 100%; 543 | font-size: 20px; 544 | width: 50px; 545 | height: 50px; 546 | line-height: 50px; 547 | margin: 0 2px 0 2px; 548 | } 549 | 550 | .team-thumb .social-icon { 551 | opacity: 0; 552 | transform: translateY(100%); 553 | transition: 0.5s 0.2s; 554 | text-align: center; 555 | position: relative; 556 | top: 0; 557 | } 558 | 559 | .team-thumb:hover .social-icon { 560 | opacity: 1; 561 | transition-delay: 0.3s; 562 | transform: translateY(0px); 563 | top: -22em; 564 | } 565 | 566 | 567 | 568 | /*--------------------------------------- 569 | SERVICE 570 | -----------------------------------------*/ 571 | 572 | #service { 573 | background: #a5c422; 574 | } 575 | 576 | #service h2, 577 | #service h4 { 578 | color: #ffffff; 579 | } 580 | 581 | #service p { 582 | color: #d9d9d9; 583 | } 584 | 585 | #service .service-thumb { 586 | padding: 0 22px; 587 | } 588 | 589 | #service .fa { 590 | font-size: 50px; 591 | margin-bottom: 10px; 592 | background: #ffffff; 593 | color: #a5c422; 594 | width: 120px; 595 | height: 120px; 596 | line-height: 120px; 597 | border-radius: 100%; 598 | } 599 | 600 | 601 | /*--------------------------------------- 602 | NEWS 603 | -----------------------------------------*/ 604 | 605 | #news, #news-detail { 606 | background: #f9f9f9; 607 | } 608 | 609 | #news-detail blockquote { 610 | margin: 30px 0; 611 | } 612 | 613 | .news-detail-thumb .news-image img { 614 | border-radius: 10px; 615 | } 616 | 617 | .news-detail-thumb h3 { 618 | margin-bottom: 8px; 619 | } 620 | 621 | .news-image { 622 | margin-bottom: 30px; 623 | position: relative; 624 | } 625 | 626 | .news-image img { 627 | width: 100%; 628 | } 629 | 630 | .news-detail-thumb ul { 631 | margin: 32px 12px 22px 0px; 632 | } 633 | 634 | .news-detail-thumb ul li { 635 | list-style: circle; 636 | font-weight: normal; 637 | padding: 6px 12px 6px 0px; 638 | } 639 | 640 | .news-sidebar { 641 | margin-top: 16px; 642 | } 643 | 644 | .news-social-share { 645 | text-align: center; 646 | padding-top: 22px; 647 | } 648 | 649 | .news-social-share .btn { 650 | border-radius: 100px; 651 | border: none; 652 | font-size: 10px; 653 | font-weight: 600; 654 | margin: 2px 6px; 655 | padding: 8px 14px; 656 | } 657 | 658 | .news-social-share .btn-primary { 659 | background: #3b5998; 660 | } 661 | 662 | .news-social-share .btn-success { 663 | background: #1da1f2; 664 | } 665 | 666 | .news-social-share .btn-danger { 667 | background: #dd4b39; 668 | } 669 | 670 | .news-social-share a .fa { 671 | padding-right: 4px; 672 | } 673 | 674 | .recent-post { 675 | padding-top: 2px; 676 | padding-bottom: 18px; 677 | } 678 | 679 | .recent-post .media img { 680 | border-radius: 100%; 681 | width: 80px; 682 | height: 80px; 683 | margin-right: 5px; 684 | } 685 | 686 | .recent-post .media-heading { 687 | font-size: 16px; 688 | font-weight: 500; 689 | line-height: inherit; 690 | margin-top: 5px; 691 | } 692 | 693 | .news-categories { 694 | margin-top: 8px; 695 | } 696 | 697 | .news-categories li a { 698 | color: #2b2b2b; 699 | } 700 | 701 | .news-ads { 702 | background: #ffffff; 703 | border-right: 4px solid #2b2b2b; 704 | padding: 42px; 705 | text-align: center; 706 | margin: 26px 0 26px 0; 707 | } 708 | 709 | .news-ads.sidebar-ads { 710 | border-left: 4px solid #2b2b2b; 711 | border-right: 0px; 712 | } 713 | 714 | .news-ads h4 { 715 | font-size: 18px; 716 | } 717 | 718 | .news-tags h4 { 719 | padding-bottom: 6px; 720 | } 721 | 722 | .news-categories li, 723 | .news-tags li { 724 | list-style: none; 725 | display: inline-block; 726 | margin: 4px; 727 | } 728 | 729 | .news-tags li a { 730 | background: #393939; 731 | border-radius: 50px; 732 | color: #ffffff; 733 | display: inline-block; 734 | font-size: 12px; 735 | font-weight: 500; 736 | text-decoration: none; 737 | float: left; 738 | min-width: 30px; 739 | padding: 6px 12px; 740 | -webkit-transition: all ease-in-out 0.4s; 741 | transition: all ease-in-out 0.4s; 742 | } 743 | 744 | .news-tags li a:hover { 745 | background: #4267b2; 746 | } 747 | 748 | 749 | 750 | /*--------------------------------------- 751 | APPOINTMENT 752 | -----------------------------------------*/ 753 | 754 | #appointment { 755 | padding-top: 100px; 756 | } 757 | 758 | #appointment label { 759 | color: #393939; 760 | font-weight: 500; 761 | } 762 | 763 | #appointment .form-control { 764 | background: #f9f9f9; 765 | border: none; 766 | border-radius: 3px; 767 | box-shadow: none; 768 | font-size: 14px; 769 | font-weight: normal; 770 | margin-bottom: 15px; 771 | transition: all ease-in-out 0.4s; 772 | } 773 | 774 | #appointment input, 775 | #appointment select { 776 | height: 45px; 777 | } 778 | 779 | #appointment button#cf-submit { 780 | background: #a5c422; 781 | color: #ffffff; 782 | font-weight: 600; 783 | height: 55px; 784 | } 785 | 786 | #appointment button#cf-submit:hover { 787 | background: #393939; 788 | color: #ffffff; 789 | } 790 | 791 | 792 | /*--------------------------------------- 793 | FOOTER 794 | -----------------------------------------*/ 795 | 796 | footer { 797 | padding-top: 80px; 798 | padding-bottom: 40px; 799 | } 800 | 801 | footer h4 { 802 | padding-bottom: 5px; 803 | } 804 | 805 | footer a { 806 | color: #757575; 807 | } 808 | 809 | footer a:hover { 810 | color: #4267b2; 811 | } 812 | 813 | .contact-info { 814 | padding-top: 10px; 815 | } 816 | 817 | .contact-info .fa { 818 | background: #393939; 819 | border-radius: 100%; 820 | color: #ffffff; 821 | font-size: 15px; 822 | width: 35px; 823 | height: 35px; 824 | line-height: 35px; 825 | text-align: center; 826 | margin-right: 5px; 827 | margin-bottom: 2px; 828 | } 829 | 830 | .latest-stories { 831 | margin-bottom: 20px; 832 | } 833 | 834 | .stories-image, 835 | .stories-info { 836 | display: inline-block; 837 | vertical-align: top; 838 | } 839 | 840 | .stories-image img { 841 | border-radius: 100%; 842 | width: 65px; 843 | height: 65px; 844 | } 845 | 846 | .stories-info { 847 | margin-left: 15px; 848 | } 849 | 850 | .stories-info h5 { 851 | margin-bottom: 2px; 852 | } 853 | 854 | .stories-info span { 855 | color: #858585; 856 | font-size: 12px; 857 | } 858 | 859 | .opening-hours p { 860 | line-height: 18px; 861 | } 862 | 863 | .opening-hours span { 864 | font-weight: 500; 865 | display: inline-block; 866 | padding-left: 10px; 867 | } 868 | 869 | .copyright-text p, 870 | .footer-link a { 871 | color: #858585; 872 | font-size: 12px; 873 | font-weight: 500; 874 | } 875 | 876 | .footer-link a { 877 | font-size: 12px; 878 | display: inline-block; 879 | padding: 0 10px; 880 | margin-top: 4px; 881 | } 882 | 883 | .angle-up-btn { 884 | position: relative; 885 | bottom: 4em; 886 | display: block; 887 | } 888 | 889 | .angle-up-btn a { 890 | background: #ffffff; 891 | border: 1px solid #f2f2f2; 892 | border-radius: 3px; 893 | font-size: 20px; 894 | color: #393939; 895 | display: inline-block; 896 | text-align: center; 897 | width: 40px; 898 | height: 40px; 899 | line-height: 38px; 900 | transition: transform 0.1s ease-in; 901 | transform: translateX(0); 902 | } 903 | 904 | .angle-up-btn a:hover { 905 | background: #4267b2; 906 | color: #ffffff; 907 | transform: translateY(-5px); 908 | } 909 | 910 | 911 | /*--------------------------------------- 912 | SOCIAL ICON 913 | -----------------------------------------*/ 914 | 915 | .social-icon { 916 | position: relative; 917 | padding: 0; 918 | margin: 0; 919 | } 920 | 921 | .social-icon li { 922 | display: inline-block; 923 | list-style: none; 924 | } 925 | 926 | .social-icon li a { 927 | border-radius: 100px; 928 | color: #464646; 929 | font-size: 15px; 930 | width: 35px; 931 | height: 35px; 932 | line-height: 35px; 933 | text-decoration: none; 934 | text-align: center; 935 | transition: all 0.4s ease-in-out; 936 | position: relative; 937 | } 938 | 939 | .social-icon li a:hover { 940 | background: #4267b2; 941 | color: #ffffff; 942 | } 943 | 944 | 945 | /*--------------------------------------- 946 | RESPONSIVE STYLES 947 | -----------------------------------------*/ 948 | 949 | @media only screen and (max-width: 1200px) { 950 | h1 { 951 | font-size: 4em; 952 | } 953 | h2 { 954 | font-size: 2.5em; 955 | } 956 | h3 { 957 | font-size: 1.5em; 958 | } 959 | 960 | header { 961 | height: inherit; 962 | } 963 | header span.date-icon { 964 | border: 0; 965 | padding-right: 0; 966 | padding-left: 0; 967 | } 968 | header span.email-icon { 969 | padding-top: 0; 970 | } 971 | 972 | .navbar-default .navbar-nav li a { 973 | padding-right: 15px; 974 | padding-left: 15px; 975 | } 976 | } 977 | 978 | @media only screen and (max-width: 992px) { 979 | .slider .item { 980 | background-position: center; 981 | } 982 | 983 | header { 984 | padding-bottom: 10px; 985 | } 986 | header .text-align-right { 987 | text-align: left; 988 | } 989 | header span { 990 | padding-top: 0; 991 | padding-left: 0; 992 | padding-bottom: 0; 993 | } 994 | } 995 | 996 | @media only screen and (max-width: 767px) { 997 | .navbar-default .navbar-collapse, .navbar-default .navbar-form { 998 | border-color: transparent; 999 | } 1000 | .navbar-default .navbar-nav li.appointment-btn { 1001 | margin-left: 15px; 1002 | } 1003 | .navbar-default .navbar-nav li a { 1004 | display: inline-block; 1005 | padding-top: 8px; 1006 | padding-bottom: 8px; 1007 | } 1008 | 1009 | .news-sidebar { 1010 | margin-top: 2em; 1011 | } 1012 | 1013 | #appointment-form { 1014 | padding-top: 4em; 1015 | padding-bottom: 4em; 1016 | } 1017 | 1018 | footer { 1019 | padding-top: 60px; 1020 | padding-bottom: 0; 1021 | } 1022 | .footer-thumb { 1023 | padding-bottom: 10px; 1024 | } 1025 | 1026 | .border-top { 1027 | text-align: center; 1028 | } 1029 | 1030 | .copyright-text { 1031 | margin-top: 10px; 1032 | } 1033 | 1034 | .angle-up-btn { 1035 | bottom: 10em; 1036 | } 1037 | } 1038 | 1039 | @media only screen and (max-width: 639px) { 1040 | h1 { 1041 | font-size: 3em; 1042 | line-height: 1.2em; 1043 | } 1044 | h2 { 1045 | font-size: 2.1em; 1046 | } 1047 | h4 { 1048 | font-size: 1.4em; 1049 | } 1050 | 1051 | #home h3 { 1052 | font-size: 11px; 1053 | letter-spacing: 1px; 1054 | } 1055 | 1056 | } 1057 | 1058 | -------------------------------------------------------------------------------- /firstApp/static/js/custom.js: -------------------------------------------------------------------------------- 1 | (function ($) { 2 | 3 | "use strict"; 4 | 5 | // PRE LOADER 6 | $(window).load(function(){ 7 | $('.preloader').fadeOut(1000); // set duration in brackets 8 | }); 9 | 10 | 11 | //Navigation Section 12 | $('.navbar-collapse a').on('click',function(){ 13 | $(".navbar-collapse").collapse('hide'); 14 | }); 15 | 16 | 17 | // Owl Carousel 18 | $('.owl-carousel').owlCarousel({ 19 | animateOut: 'fadeOut', 20 | items:1, 21 | loop:true, 22 | autoplay:true, 23 | }) 24 | 25 | 26 | // PARALLAX EFFECT 27 | $.stellar(); 28 | 29 | 30 | // SMOOTHSCROLL 31 | $(function() { 32 | $('.navbar-default a, #home a, footer a').on('click', function(event) { 33 | var $anchor = $(this); 34 | $('html, body').stop().animate({ 35 | scrollTop: $($anchor.attr('href')).offset().top - 49 36 | }, 1000); 37 | event.preventDefault(); 38 | }); 39 | }); 40 | 41 | 42 | // WOW ANIMATION 43 | new WOW({ mobile: false }).init(); 44 | 45 | })(jQuery); 46 | -------------------------------------------------------------------------------- /firstApp/static/js/jquery.stellar.min.js: -------------------------------------------------------------------------------- 1 | /*! Stellar.js v0.6.2 | Copyright 2014, Mark Dalgleish | http://markdalgleish.com/projects/stellar.js | http://markdalgleish.mit-license.org */ 2 | !function(a,b,c,d){function e(b,c){this.element=b,this.options=a.extend({},g,c),this._defaults=g,this._name=f,this.init()}var f="stellar",g={scrollProperty:"scroll",positionProperty:"position",horizontalScrolling:!0,verticalScrolling:!0,horizontalOffset:0,verticalOffset:0,responsive:!1,parallaxBackgrounds:!0,parallaxElements:!0,hideDistantElements:!0,hideElement:function(a){a.hide()},showElement:function(a){a.show()}},h={scroll:{getLeft:function(a){return a.scrollLeft()},setLeft:function(a,b){a.scrollLeft(b)},getTop:function(a){return a.scrollTop()},setTop:function(a,b){a.scrollTop(b)}},position:{getLeft:function(a){return-1*parseInt(a.css("left"),10)},getTop:function(a){return-1*parseInt(a.css("top"),10)}},margin:{getLeft:function(a){return-1*parseInt(a.css("margin-left"),10)},getTop:function(a){return-1*parseInt(a.css("margin-top"),10)}},transform:{getLeft:function(a){var b=getComputedStyle(a[0])[k];return"none"!==b?-1*parseInt(b.match(/(-?[0-9]+)/g)[4],10):0},getTop:function(a){var b=getComputedStyle(a[0])[k];return"none"!==b?-1*parseInt(b.match(/(-?[0-9]+)/g)[5],10):0}}},i={position:{setLeft:function(a,b){a.css("left",b)},setTop:function(a,b){a.css("top",b)}},transform:{setPosition:function(a,b,c,d,e){a[0].style[k]="translate3d("+(b-c)+"px, "+(d-e)+"px, 0)"}}},j=function(){var b,c=/^(Moz|Webkit|Khtml|O|ms|Icab)(?=[A-Z])/,d=a("script")[0].style,e="";for(b in d)if(c.test(b)){e=b.match(c)[0];break}return"WebkitOpacity"in d&&(e="Webkit"),"KhtmlOpacity"in d&&(e="Khtml"),function(a){return e+(e.length>0?a.charAt(0).toUpperCase()+a.slice(1):a)}}(),k=j("transform"),l=a("
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d=this,e=d._getScrollLeft(),f=d._getScrollTop();c&&c.firstLoad||this._reset(),this._setScrollLeft(0),this._setScrollTop(0),this._setOffsets(),this._findParticles(),this._findBackgrounds(),c&&c.firstLoad&&/WebKit/.test(navigator.userAgent)&&a(b).load(function(){var a=d._getScrollLeft(),b=d._getScrollTop();d._setScrollLeft(a+1),d._setScrollTop(b+1),d._setScrollLeft(a),d._setScrollTop(b)}),this._setScrollLeft(e),this._setScrollTop(f)},_detectViewport:function(){var a=this.$viewportElement.offset(),b=null!==a&&a!==d;this.viewportWidth=this.$viewportElement.width(),this.viewportHeight=this.$viewportElement.height(),this.viewportOffsetTop=b?a.top:0,this.viewportOffsetLeft=b?a.left:0},_findParticles:function(){{var b=this;this._getScrollLeft(),this._getScrollTop()}if(this.particles!==d)for(var 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b,c=this,e=this._getScrollLeft(),f=this._getScrollTop();this.backgrounds=[],this.options.parallaxBackgrounds&&(b=this.$element.find("[data-stellar-background-ratio]"),this.$element.data("stellar-background-ratio")&&(b=b.add(this.$element)),b.each(function(){var b,g,h,i,j,k,l,o=a(this),p=n(o),q=0,r=0,s=0,t=0;if(o.data("stellar-backgroundIsActive")){if(o.data("stellar-backgroundIsActive")!==this)return}else o.data("stellar-backgroundIsActive",this);o.data("stellar-backgroundStartingLeft")?m(o,o.data("stellar-backgroundStartingLeft"),o.data("stellar-backgroundStartingTop")):(o.data("stellar-backgroundStartingLeft",p[0]),o.data("stellar-backgroundStartingTop",p[1])),h="auto"===o.css("margin-left")?0:parseInt(o.css("margin-left"),10),i="auto"===o.css("margin-top")?0:parseInt(o.css("margin-top"),10),j=o.offset().left-h-e,k=o.offset().top-i-f,o.parents().each(function(){var b=a(this);return b.data("stellar-offset-parent")===!0?(q=s,r=t,l=b,!1):(s+=b.position().left,void(t+=b.position().top))}),b=o.data("stellar-horizontal-offset")!==d?o.data("stellar-horizontal-offset"):l!==d&&l.data("stellar-horizontal-offset")!==d?l.data("stellar-horizontal-offset"):c.horizontalOffset,g=o.data("stellar-vertical-offset")!==d?o.data("stellar-vertical-offset"):l!==d&&l.data("stellar-vertical-offset")!==d?l.data("stellar-vertical-offset"):c.verticalOffset,c.backgrounds.push({$element:o,$offsetParent:l,isFixed:"fixed"===o.css("background-attachment"),horizontalOffset:b,verticalOffset:g,startingValueLeft:p[0],startingValueTop:p[1],startingBackgroundPositionLeft:isNaN(parseInt(p[0],10))?0:parseInt(p[0],10),startingBackgroundPositionTop:isNaN(parseInt(p[1],10))?0:parseInt(p[1],10),startingPositionLeft:o.position().left,startingPositionTop:o.position().top,startingOffsetLeft:j,startingOffsetTop:k,parentOffsetLeft:q,parentOffsetTop:r,stellarRatio:o.data("stellar-background-ratio")===d?1:o.data("stellar-background-ratio")})}))},_reset:function(){var a,b,c,d,e;for(e=this.particles.length-1;e>=0;e--)a=this.particles[e],b=a.$element.data("stellar-startingLeft"),c=a.$element.data("stellar-startingTop"),this._setPosition(a.$element,b,b,c,c),this.options.showElement(a.$element),a.$element.data("stellar-startingLeft",null).data("stellar-elementIsActive",null).data("stellar-backgroundIsActive",null);for(e=this.backgrounds.length-1;e>=0;e--)d=this.backgrounds[e],d.$element.data("stellar-backgroundStartingLeft",null).data("stellar-backgroundStartingTop",null),m(d.$element,d.startingValueLeft,d.startingValueTop)},destroy:function(){this._reset(),this.$scrollElement.unbind("resize."+this.name).unbind("scroll."+this.name),this._animationLoop=a.noop,a(b).unbind("load."+this.name).unbind("resize."+this.name)},_setOffsets:function(){var c=this,d=a(b);d.unbind("resize.horizontal-"+this.name).unbind("resize.vertical-"+this.name),"function"==typeof this.options.horizontalOffset?(this.horizontalOffset=this.options.horizontalOffset(),d.bind("resize.horizontal-"+this.name,function(){c.horizontalOffset=c.options.horizontalOffset()})):this.horizontalOffset=this.options.horizontalOffset,"function"==typeof this.options.verticalOffset?(this.verticalOffset=this.options.verticalOffset(),d.bind("resize.vertical-"+this.name,function(){c.verticalOffset=c.options.verticalOffset()})):this.verticalOffset=this.options.verticalOffset},_repositionElements:function(){var a,b,c,d,e,f,g,h,i,j,k=this._getScrollLeft(),l=this._getScrollTop(),n=!0,o=!0;if(this.currentScrollLeft!==k||this.currentScrollTop!==l||this.currentWidth!==this.viewportWidth||this.currentHeight!==this.viewportHeight){for(this.currentScrollLeft=k,this.currentScrollTop=l,this.currentWidth=this.viewportWidth,this.currentHeight=this.viewportHeight,j=this.particles.length-1;j>=0;j--)a=this.particles[j],b=a.isFixed?1:0,this.options.horizontalScrolling?(f=(k+a.horizontalOffset+this.viewportOffsetLeft+a.startingPositionLeft-a.startingOffsetLeft+a.parentOffsetLeft)*-(a.stellarRatio+b-1)+a.startingPositionLeft,h=f-a.startingPositionLeft+a.startingOffsetLeft):(f=a.startingPositionLeft,h=a.startingOffsetLeft),this.options.verticalScrolling?(g=(l+a.verticalOffset+this.viewportOffsetTop+a.startingPositionTop-a.startingOffsetTop+a.parentOffsetTop)*-(a.stellarRatio+b-1)+a.startingPositionTop,i=g-a.startingPositionTop+a.startingOffsetTop):(g=a.startingPositionTop,i=a.startingOffsetTop),this.options.hideDistantElements&&(o=!this.options.horizontalScrolling||h+a.width>(a.isFixed?0:k)&&h<(a.isFixed?0:k)+this.viewportWidth+this.viewportOffsetLeft,n=!this.options.verticalScrolling||i+a.height>(a.isFixed?0:l)&&i<(a.isFixed?0:l)+this.viewportHeight+this.viewportOffsetTop),o&&n?(a.isHidden&&(this.options.showElement(a.$element),a.isHidden=!1),this._setPosition(a.$element,f,a.startingPositionLeft,g,a.startingPositionTop)):a.isHidden||(this.options.hideElement(a.$element),a.isHidden=!0);for(j=this.backgrounds.length-1;j>=0;j--)c=this.backgrounds[j],b=c.isFixed?0:1,d=this.options.horizontalScrolling?(k+c.horizontalOffset-this.viewportOffsetLeft-c.startingOffsetLeft+c.parentOffsetLeft-c.startingBackgroundPositionLeft)*(b-c.stellarRatio)+"px":c.startingValueLeft,e=this.options.verticalScrolling?(l+c.verticalOffset-this.viewportOffsetTop-c.startingOffsetTop+c.parentOffsetTop-c.startingBackgroundPositionTop)*(b-c.stellarRatio)+"px":c.startingValueTop,m(c.$element,d,e)}},_handleScrollEvent:function(){var a=this,b=!1,c=function(){a._repositionElements(),b=!1},d=function(){b||(o(c),b=!0)};this.$scrollElement.bind("scroll."+this.name,d),d()},_startAnimationLoop:function(){var a=this;this._animationLoop=function(){o(a._animationLoop),a._repositionElements()},this._animationLoop()}},a.fn[f]=function(b){var c=arguments;return b===d||"object"==typeof b?this.each(function(){a.data(this,"plugin_"+f)||a.data(this,"plugin_"+f,new e(this,b))}):"string"==typeof b&&"_"!==b[0]&&"init"!==b?this.each(function(){var d=a.data(this,"plugin_"+f);d instanceof e&&"function"==typeof d[b]&&d[b].apply(d,Array.prototype.slice.call(c,1)),"destroy"===b&&a.data(this,"plugin_"+f,null)}):void 0},a[f]=function(){var c=a(b);return c.stellar.apply(c,Array.prototype.slice.call(arguments,0))},a[f].scrollProperty=h,a[f].positionProperty=i,b.Stellar=e}(jQuery,this,document); -------------------------------------------------------------------------------- /firstApp/static/js/jquery.sticky.js: -------------------------------------------------------------------------------- 1 | // Sticky Plugin v1.0.3 for jQuery 2 | // ============= 3 | // Author: Anthony Garand 4 | // Improvements by German M. Bravo (Kronuz) and Ruud Kamphuis (ruudk) 5 | // Improvements by Leonardo C. Daronco (daronco) 6 | // Created: 02/14/2011 7 | // Date: 07/20/2015 8 | // Website: http://stickyjs.com/ 9 | // Description: Makes an element on the page stick on the screen as you scroll 10 | // It will only set the 'top' and 'position' of your element, you 11 | // might need to adjust the width in some cases. 12 | 13 | (function($) { 14 | var slice = Array.prototype.slice; // save ref to original slice() 15 | var splice = Array.prototype.splice; // save ref to original slice() 16 | 17 | var defaults = { 18 | topSpacing: 0, 19 | bottomSpacing: 0, 20 | className: 'is-sticky', 21 | wrapperClassName: 'sticky-wrapper', 22 | center: false, 23 | getWidthFrom: '', 24 | widthFromWrapper: true, // works only when .getWidthFrom is empty 25 | responsiveWidth: false 26 | }, 27 | $window = $(window), 28 | $document = $(document), 29 | sticked = [], 30 | windowHeight = $window.height(), 31 | scroller = function() { 32 | var scrollTop = $window.scrollTop(), 33 | documentHeight = $document.height(), 34 | dwh = documentHeight - windowHeight, 35 | extra = (scrollTop > dwh) ? dwh - scrollTop : 0; 36 | 37 | for (var i = 0; i < sticked.length; i++) { 38 | var s = sticked[i], 39 | elementTop = s.stickyWrapper.offset().top, 40 | etse = elementTop - s.topSpacing - extra; 41 | 42 | //update height in case of dynamic content 43 | s.stickyWrapper.css('height', s.stickyElement.outerHeight()); 44 | 45 | if (scrollTop <= etse) { 46 | if (s.currentTop !== null) { 47 | s.stickyElement 48 | .css({ 49 | 'width': '', 50 | 'position': '', 51 | 'top': '' 52 | }); 53 | s.stickyElement.parent().removeClass(s.className); 54 | s.stickyElement.trigger('sticky-end', [s]); 55 | s.currentTop = null; 56 | } 57 | } 58 | else { 59 | var newTop = documentHeight - s.stickyElement.outerHeight() 60 | - s.topSpacing - s.bottomSpacing - scrollTop - extra; 61 | if (newTop < 0) { 62 | newTop = newTop + s.topSpacing; 63 | } else { 64 | newTop = s.topSpacing; 65 | } 66 | if (s.currentTop != newTop) { 67 | var newWidth; 68 | if (s.getWidthFrom) { 69 | newWidth = $(s.getWidthFrom).width() || null; 70 | } else if (s.widthFromWrapper) { 71 | newWidth = s.stickyWrapper.width(); 72 | } 73 | if (newWidth == null) { 74 | newWidth = s.stickyElement.width(); 75 | } 76 | s.stickyElement 77 | .css('width', newWidth) 78 | .css('position', 'fixed') 79 | .css('top', newTop); 80 | 81 | s.stickyElement.parent().addClass(s.className); 82 | 83 | if (s.currentTop === null) { 84 | s.stickyElement.trigger('sticky-start', [s]); 85 | } else { 86 | // sticky is started but it have to be repositioned 87 | s.stickyElement.trigger('sticky-update', [s]); 88 | } 89 | 90 | if (s.currentTop === s.topSpacing && s.currentTop > newTop || s.currentTop === null && newTop < s.topSpacing) { 91 | // just reached bottom || just started to stick but bottom is already reached 92 | s.stickyElement.trigger('sticky-bottom-reached', [s]); 93 | } else if(s.currentTop !== null && newTop === s.topSpacing && s.currentTop < newTop) { 94 | // sticky is started && sticked at topSpacing && overflowing from top just finished 95 | s.stickyElement.trigger('sticky-bottom-unreached', [s]); 96 | } 97 | 98 | s.currentTop = newTop; 99 | } 100 | } 101 | } 102 | }, 103 | resizer = function() { 104 | windowHeight = $window.height(); 105 | 106 | for (var i = 0; i < sticked.length; i++) { 107 | var s = sticked[i]; 108 | var newWidth = null; 109 | if (s.getWidthFrom) { 110 | if (s.responsiveWidth === true) { 111 | newWidth = $(s.getWidthFrom).width(); 112 | } 113 | } else if(s.widthFromWrapper) { 114 | newWidth = s.stickyWrapper.width(); 115 | } 116 | if (newWidth != null) { 117 | s.stickyElement.css('width', newWidth); 118 | } 119 | } 120 | }, 121 | methods = { 122 | init: function(options) { 123 | var o = $.extend({}, defaults, options); 124 | return this.each(function() { 125 | var stickyElement = $(this); 126 | 127 | var stickyId = stickyElement.attr('id'); 128 | var stickyHeight = stickyElement.outerHeight(); 129 | var wrapperId = stickyId ? stickyId + '-' + defaults.wrapperClassName : defaults.wrapperClassName 130 | var wrapper = $('
') 131 | .attr('id', wrapperId) 132 | .addClass(o.wrapperClassName); 133 | 134 | stickyElement.wrapAll(wrapper); 135 | 136 | var stickyWrapper = stickyElement.parent(); 137 | 138 | if (o.center) { 139 | stickyWrapper.css({width:stickyElement.outerWidth(),marginLeft:"auto",marginRight:"auto"}); 140 | } 141 | 142 | if (stickyElement.css("float") == "right") { 143 | stickyElement.css({"float":"none"}).parent().css({"float":"right"}); 144 | } 145 | 146 | stickyWrapper.css('height', stickyHeight); 147 | 148 | o.stickyElement = stickyElement; 149 | o.stickyWrapper = stickyWrapper; 150 | o.currentTop = null; 151 | 152 | sticked.push(o); 153 | }); 154 | }, 155 | update: scroller, 156 | unstick: function(options) { 157 | return this.each(function() { 158 | var that = this; 159 | var unstickyElement = $(that); 160 | 161 | var removeIdx = -1; 162 | var i = sticked.length; 163 | while (i-- > 0) { 164 | if (sticked[i].stickyElement.get(0) === that) { 165 | splice.call(sticked,i,1); 166 | removeIdx = i; 167 | } 168 | } 169 | if(removeIdx != -1) { 170 | unstickyElement.unwrap(); 171 | unstickyElement 172 | .css({ 173 | 'width': '', 174 | 'position': '', 175 | 'top': '', 176 | 'float': '' 177 | }) 178 | ; 179 | } 180 | }); 181 | } 182 | }; 183 | 184 | // should be more efficient than using $window.scroll(scroller) and $window.resize(resizer): 185 | if (window.addEventListener) { 186 | window.addEventListener('scroll', scroller, false); 187 | window.addEventListener('resize', resizer, false); 188 | } else if (window.attachEvent) { 189 | window.attachEvent('onscroll', scroller); 190 | window.attachEvent('onresize', resizer); 191 | } 192 | 193 | $.fn.sticky = function(method) { 194 | if (methods[method]) { 195 | return methods[method].apply(this, slice.call(arguments, 1)); 196 | } else if (typeof method === 'object' || !method ) { 197 | return methods.init.apply( this, arguments ); 198 | } else { 199 | $.error('Method ' + method + ' does not exist on jQuery.sticky'); 200 | } 201 | }; 202 | 203 | $.fn.unstick = function(method) { 204 | if (methods[method]) { 205 | return methods[method].apply(this, slice.call(arguments, 1)); 206 | } else if (typeof method === 'object' || !method ) { 207 | return methods.unstick.apply( this, arguments ); 208 | } else { 209 | $.error('Method ' + method + ' does not exist on jQuery.sticky'); 210 | } 211 | }; 212 | $(function() { 213 | setTimeout(scroller, 0); 214 | }); 215 | })(jQuery); 216 | 217 | $(document).ready(function(){ 218 | $(".navbar-default").sticky({topSpacing:0}); 219 | }); 220 | -------------------------------------------------------------------------------- /firstApp/static/js/smoothscroll.js: -------------------------------------------------------------------------------- 1 | /** 2 | * SmoothScroll 3 | * This helper script created by DWUser.com. Copyright 2013 DWUser.com. 4 | * Dual-licensed under the GPL and MIT licenses. 5 | * All individual scripts remain property of their copyrighters. 6 | * Date: 10-Sep-2013 7 | * Version: 1.0.1 8 | */ 9 | if (!window['jQuery']) alert('The jQuery library must be included before the smoothscroll.js file. The plugin will not work propery.'); 10 | 11 | /** 12 | * jQuery.ScrollTo - Easy element scrolling using jQuery. 13 | * Copyright (c) 2007-2013 Ariel Flesler - aflesler(at)gmail(dot)com | http://flesler.blogspot.com 14 | * Dual licensed under MIT and GPL. 15 | * @author Ariel Flesler 16 | * @version 1.4.3.1 17 | */ 18 | ;(function($){var h=$.scrollTo=function(a,b,c){$(window).scrollTo(a,b,c)};h.defaults={axis:'xy',duration:parseFloat($.fn.jquery)>=1.3?0:1,limit:true};h.window=function(a){return $(window)._scrollable()};$.fn._scrollable=function(){return this.map(function(){var a=this,isWin=!a.nodeName||$.inArray(a.nodeName.toLowerCase(),['iframe','#document','html','body'])!=-1;if(!isWin)return a;var b=(a.contentWindow||a).document||a.ownerDocument||a;return/webkit/i.test(navigator.userAgent)||b.compatMode=='BackCompat'?b.body:b.documentElement})};$.fn.scrollTo=function(e,f,g){if(typeof f=='object'){g=f;f=0}if(typeof g=='function')g={onAfter:g};if(e=='max')e=9e9;g=$.extend({},h.defaults,g);f=f||g.duration;g.queue=g.queue&&g.axis.length>1;if(g.queue)f/=2;g.offset=both(g.offset);g.over=both(g.over);return this._scrollable().each(function(){if(e==null)return;var d=this,$elem=$(d),targ=e,toff,attr={},win=$elem.is('html,body');switch(typeof targ){case'number':case'string':if(/^([+-]=)?\d+(\.\d+)?(px|%)?$/.test(targ)){targ=both(targ);break}targ=$(targ,this);if(!targ.length)return;case'object':if(targ.is||targ.style)toff=(targ=$(targ)).offset()}$.each(g.axis.split(''),function(i,a){var b=a=='x'?'Left':'Top',pos=b.toLowerCase(),key='scroll'+b,old=d[key],max=h.max(d,a);if(toff){attr[key]=toff[pos]+(win?0:old-$elem.offset()[pos]);if(g.margin){attr[key]-=parseInt(targ.css('margin'+b))||0;attr[key]-=parseInt(targ.css('border'+b+'Width'))||0}attr[key]+=g.offset[pos]||0;if(g.over[pos])attr[key]+=targ[a=='x'?'width':'height']()*g.over[pos]}else{var c=targ[pos];attr[key]=c.slice&&c.slice(-1)=='%'?parseFloat(c)/100*max:c}if(g.limit&&/^\d+$/.test(attr[key]))attr[key]=attr[key]<=0?0:Math.min(attr[key],max);if(!i&&g.queue){if(old!=attr[key])animate(g.onAfterFirst);delete attr[key]}});animate(g.onAfter);function animate(a){$elem.animate(attr,f,g.easing,a&&function(){a.call(this,e,g)})}}).end()};h.max=function(a,b){var c=b=='x'?'Width':'Height',scroll='scroll'+c;if(!$(a).is('html,body'))return a[scroll]-$(a)[c.toLowerCase()]();var d='client'+c,html=a.ownerDocument.documentElement,body=a.ownerDocument.body;return Math.max(html[scroll],body[scroll])-Math.min(html[d],body[d])};function both(a){return typeof a=='object'?a:{top:a,left:a}}})(jQuery); 19 | 20 | /** 21 | * jQuery.LocalScroll 22 | * Copyright (c) 2007-2010 Ariel Flesler - aflesler(at)gmail(dot)com | http://flesler.blogspot.com 23 | * Dual licensed under MIT and GPL. 24 | * Date: 05/31/2010 25 | * @author Ariel Flesler 26 | * @version 1.2.8b 27 | **/ 28 | ;(function(b){function g(a,e,d){var h=e.hash.slice(1),f=document.getElementById(h)||document.getElementsByName(h)[0];if(f){a&&a.preventDefault();var c=b(d.target);if(!(d.lock&&c.is(":animated")||d.onBefore&&!1===d.onBefore(a,f,c))){d.stop&&c._scrollable().stop(!0);if(d.hash){var a=f.id==h?"id":"name",g=b(" ").attr(a,h).css({position:"absolute",top:b(window).scrollTop(),left:b(window).scrollLeft()});f[a]="";b("body").prepend(g);location=e.hash;g.remove();f[a]=h}c.scrollTo(f,d).trigger("notify.serialScroll", 29 | [f])}}}var i=location.href.replace(/#.*/,""),c=b.localScroll=function(a){b("body").localScroll(a)};c.defaults={duration:1E3,axis:"y",event:"click",stop:!0,target:window,reset:!0};c.hash=function(a){if(location.hash){a=b.extend({},c.defaults,a);a.hash=!1;if(a.reset){var e=a.duration;delete a.duration;b(a.target).scrollTo(0,a);a.duration=e}g(0,location,a)}};b.fn.localScroll=function(a){function e(){return!!this.href&&!!this.hash&&this.href.replace(this.hash,"")==i&&(!a.filter||b(this).is(a.filter))} 30 | a=b.extend({},c.defaults,a);return a.lazy?this.bind(a.event,function(d){var c=b([d.target,d.target.parentNode]).filter(e)[0];c&&g(d,c,a)}):this.find("a,area").filter(e).bind(a.event,function(b){g(b,this,a)}).end().end()}})(jQuery); 31 | 32 | // Initialize all .smoothScroll links 33 | jQuery(function($){ $.localScroll({filter:'.smoothScroll'}); }); 34 | -------------------------------------------------------------------------------- /firstApp/static/js/wow.min.js: -------------------------------------------------------------------------------- 1 | /*! WOW - v1.0.2 - 2014-10-28 2 | * Copyright (c) 2014 Matthieu Aussaguel; Licensed MIT */(function(){var a,b,c,d,e,f=function(a,b){return function(){return a.apply(b,arguments)}},g=[].indexOf||function(a){for(var b=0,c=this.length;c>b;b++)if(b in this&&this[b]===a)return b;return-1};b=function(){function a(){}return a.prototype.extend=function(a,b){var c,d;for(c in b)d=b[c],null==a[c]&&(a[c]=d);return a},a.prototype.isMobile=function(a){return/Android|webOS|iPhone|iPad|iPod|BlackBerry|IEMobile|Opera Mini/i.test(a)},a.prototype.addEvent=function(a,b,c){return null!=a.addEventListener?a.addEventListener(b,c,!1):null!=a.attachEvent?a.attachEvent("on"+b,c):a[b]=c},a.prototype.removeEvent=function(a,b,c){return null!=a.removeEventListener?a.removeEventListener(b,c,!1):null!=a.detachEvent?a.detachEvent("on"+b,c):delete a[b]},a.prototype.innerHeight=function(){return"innerHeight"in window?window.innerHeight:document.documentElement.clientHeight},a}(),c=this.WeakMap||this.MozWeakMap||(c=function(){function a(){this.keys=[],this.values=[]}return a.prototype.get=function(a){var b,c,d,e,f;for(f=this.keys,b=d=0,e=f.length;e>d;b=++d)if(c=f[b],c===a)return this.values[b]},a.prototype.set=function(a,b){var c,d,e,f,g;for(g=this.keys,c=e=0,f=g.length;f>e;c=++e)if(d=g[c],d===a)return void(this.values[c]=b);return this.keys.push(a),this.values.push(b)},a}()),a=this.MutationObserver||this.WebkitMutationObserver||this.MozMutationObserver||(a=function(){function a(){"undefined"!=typeof console&&null!==console&&console.warn("MutationObserver is not supported by your browser."),"undefined"!=typeof console&&null!==console&&console.warn("WOW.js cannot detect dom mutations, please call .sync() after loading new content.")}return a.notSupported=!0,a.prototype.observe=function(){},a}()),d=this.getComputedStyle||function(a){return this.getPropertyValue=function(b){var c;return"float"===b&&(b="styleFloat"),e.test(b)&&b.replace(e,function(a,b){return b.toUpperCase()}),(null!=(c=a.currentStyle)?c[b]:void 0)||null},this},e=/(\-([a-z]){1})/g,this.WOW=function(){function e(a){null==a&&(a={}),this.scrollCallback=f(this.scrollCallback,this),this.scrollHandler=f(this.scrollHandler,this),this.start=f(this.start,this),this.scrolled=!0,this.config=this.util().extend(a,this.defaults),this.animationNameCache=new c}return e.prototype.defaults={boxClass:"wow",animateClass:"animated",offset:0,mobile:!0,live:!0},e.prototype.init=function(){var a;return this.element=window.document.documentElement,"interactive"===(a=document.readyState)||"complete"===a?this.start():this.util().addEvent(document,"DOMContentLoaded",this.start),this.finished=[]},e.prototype.start=function(){var b,c,d,e;if(this.stopped=!1,this.boxes=function(){var a,c,d,e;for(d=this.element.querySelectorAll("."+this.config.boxClass),e=[],a=0,c=d.length;c>a;a++)b=d[a],e.push(b);return e}.call(this),this.all=function(){var a,c,d,e;for(d=this.boxes,e=[],a=0,c=d.length;c>a;a++)b=d[a],e.push(b);return e}.call(this),this.boxes.length)if(this.disabled())this.resetStyle();else for(e=this.boxes,c=0,d=e.length;d>c;c++)b=e[c],this.applyStyle(b,!0);return this.disabled()||(this.util().addEvent(window,"scroll",this.scrollHandler),this.util().addEvent(window,"resize",this.scrollHandler),this.interval=setInterval(this.scrollCallback,50)),this.config.live?new a(function(a){return function(b){var c,d,e,f,g;for(g=[],e=0,f=b.length;f>e;e++)d=b[e],g.push(function(){var a,b,e,f;for(e=d.addedNodes||[],f=[],a=0,b=e.length;b>a;a++)c=e[a],f.push(this.doSync(c));return f}.call(a));return g}}(this)).observe(document.body,{childList:!0,subtree:!0}):void 0},e.prototype.stop=function(){return this.stopped=!0,this.util().removeEvent(window,"scroll",this.scrollHandler),this.util().removeEvent(window,"resize",this.scrollHandler),null!=this.interval?clearInterval(this.interval):void 0},e.prototype.sync=function(){return a.notSupported?this.doSync(this.element):void 0},e.prototype.doSync=function(a){var b,c,d,e,f;if(null==a&&(a=this.element),1===a.nodeType){for(a=a.parentNode||a,e=a.querySelectorAll("."+this.config.boxClass),f=[],c=0,d=e.length;d>c;c++)b=e[c],g.call(this.all,b)<0?(this.boxes.push(b),this.all.push(b),this.stopped||this.disabled()?this.resetStyle():this.applyStyle(b,!0),f.push(this.scrolled=!0)):f.push(void 0);return f}},e.prototype.show=function(a){return this.applyStyle(a),a.className=""+a.className+" "+this.config.animateClass},e.prototype.applyStyle=function(a,b){var c,d,e;return d=a.getAttribute("data-wow-duration"),c=a.getAttribute("data-wow-delay"),e=a.getAttribute("data-wow-iteration"),this.animate(function(f){return function(){return f.customStyle(a,b,d,c,e)}}(this))},e.prototype.animate=function(){return"requestAnimationFrame"in window?function(a){return window.requestAnimationFrame(a)}:function(a){return a()}}(),e.prototype.resetStyle=function(){var a,b,c,d,e;for(d=this.boxes,e=[],b=0,c=d.length;c>b;b++)a=d[b],e.push(a.style.visibility="visible");return e},e.prototype.customStyle=function(a,b,c,d,e){return b&&this.cacheAnimationName(a),a.style.visibility=b?"hidden":"visible",c&&this.vendorSet(a.style,{animationDuration:c}),d&&this.vendorSet(a.style,{animationDelay:d}),e&&this.vendorSet(a.style,{animationIterationCount:e}),this.vendorSet(a.style,{animationName:b?"none":this.cachedAnimationName(a)}),a},e.prototype.vendors=["moz","webkit"],e.prototype.vendorSet=function(a,b){var c,d,e,f;f=[];for(c in b)d=b[c],a[""+c]=d,f.push(function(){var b,f,g,h;for(g=this.vendors,h=[],b=0,f=g.length;f>b;b++)e=g[b],h.push(a[""+e+c.charAt(0).toUpperCase()+c.substr(1)]=d);return h}.call(this));return f},e.prototype.vendorCSS=function(a,b){var c,e,f,g,h,i;for(e=d(a),c=e.getPropertyCSSValue(b),i=this.vendors,g=0,h=i.length;h>g;g++)f=i[g],c=c||e.getPropertyCSSValue("-"+f+"-"+b);return c},e.prototype.animationName=function(a){var b;try{b=this.vendorCSS(a,"animation-name").cssText}catch(c){b=d(a).getPropertyValue("animation-name")}return"none"===b?"":b},e.prototype.cacheAnimationName=function(a){return this.animationNameCache.set(a,this.animationName(a))},e.prototype.cachedAnimationName=function(a){return this.animationNameCache.get(a)},e.prototype.scrollHandler=function(){return this.scrolled=!0},e.prototype.scrollCallback=function(){var a;return!this.scrolled||(this.scrolled=!1,this.boxes=function(){var b,c,d,e;for(d=this.boxes,e=[],b=0,c=d.length;c>b;b++)a=d[b],a&&(this.isVisible(a)?this.show(a):e.push(a));return e}.call(this),this.boxes.length||this.config.live)?void 0:this.stop()},e.prototype.offsetTop=function(a){for(var b;void 0===a.offsetTop;)a=a.parentNode;for(b=a.offsetTop;a=a.offsetParent;)b+=a.offsetTop;return b},e.prototype.isVisible=function(a){var b,c,d,e,f;return c=a.getAttribute("data-wow-offset")||this.config.offset,f=window.pageYOffset,e=f+Math.min(this.element.clientHeight,this.util().innerHeight())-c,d=this.offsetTop(a),b=d+a.clientHeight,e>=d&&b>=f},e.prototype.util=function(){return null!=this._util?this._util:this._util=new b},e.prototype.disabled=function(){return!this.config.mobile&&this.util().isMobile(navigator.userAgent)},e}()}).call(this); -------------------------------------------------------------------------------- /firstApp/tests.py: -------------------------------------------------------------------------------- 1 | from django.test import TestCase 2 | 3 | # Create your tests here. 4 | -------------------------------------------------------------------------------- /firstApp/views.py: -------------------------------------------------------------------------------- 1 | from django.shortcuts import render 2 | # Create your views here. 3 | 4 | from django.core.files.storage import FileSystemStorage 5 | 6 | from keras.models import load_model 7 | from keras.preprocessing import image 8 | import tensorflow as tf 9 | import json 10 | from tensorflow import Graph, Session 11 | 12 | 13 | img_height, img_width=224,224 14 | with open('./models/imagenet_classes.json','r') as f: 15 | labelInfo=f.read() 16 | 17 | labelInfo=json.loads(labelInfo) 18 | 19 | 20 | model_graph = Graph() 21 | with model_graph.as_default(): 22 | tf_session = Session() 23 | with tf_session.as_default(): 24 | model=load_model('./models/MobileNetModelImagenet.h5') 25 | 26 | 27 | 28 | def index(request): 29 | context={'a':1} 30 | return render(request,'index.html',context) 31 | 32 | 33 | 34 | def predictImage(request): 35 | print (request) 36 | print (request.POST.dict()) 37 | fileObj=request.FILES['filePath'] 38 | fs=FileSystemStorage() 39 | filePathName=fs.save(fileObj.name,fileObj) 40 | filePathName=fs.url(filePathName) 41 | testimage='.'+filePathName 42 | img = image.load_img(testimage, target_size=(img_height, img_width)) 43 | x = image.img_to_array(img) 44 | x=x/255 45 | x=x.reshape(1,img_height, img_width,3) 46 | with model_graph.as_default(): 47 | with tf_session.as_default(): 48 | predi=model.predict(x) 49 | 50 | import numpy as np 51 | predictedLabel=labelInfo[str(np.argmax(predi[0]))] 52 | 53 | context={'filePathName':filePathName,'predictedLabel':predictedLabel[1]} 54 | return render(request,'index.html',context) 55 | 56 | def viewDataBase(request): 57 | import os 58 | listOfImages=os.listdir('./media/') 59 | listOfImagesPath=['./media/'+i for i in listOfImages] 60 | context={'listOfImagesPath':listOfImagesPath} 61 | return render(request,'viewDB.html',context) -------------------------------------------------------------------------------- /imageNetProj/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/imageNetProj/__init__.py -------------------------------------------------------------------------------- /imageNetProj/__pycache__/__init__.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/imageNetProj/__pycache__/__init__.cpython-36.pyc -------------------------------------------------------------------------------- /imageNetProj/__pycache__/settings.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/imageNetProj/__pycache__/settings.cpython-36.pyc -------------------------------------------------------------------------------- /imageNetProj/__pycache__/urls.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/imageNetProj/__pycache__/urls.cpython-36.pyc -------------------------------------------------------------------------------- /imageNetProj/__pycache__/wsgi.cpython-36.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/imageNetProj/__pycache__/wsgi.cpython-36.pyc -------------------------------------------------------------------------------- /imageNetProj/asgi.py: -------------------------------------------------------------------------------- 1 | """ 2 | ASGI config for imageNetProj project. 3 | 4 | It exposes the ASGI callable as a module-level variable named ``application``. 5 | 6 | For more information on this file, see 7 | https://docs.djangoproject.com/en/3.0/howto/deployment/asgi/ 8 | """ 9 | 10 | import os 11 | 12 | from django.core.asgi import get_asgi_application 13 | 14 | os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'imageNetProj.settings') 15 | 16 | application = get_asgi_application() 17 | -------------------------------------------------------------------------------- /imageNetProj/settings.py: -------------------------------------------------------------------------------- 1 | """ 2 | Django settings for imageNetProj project. 3 | 4 | Generated by 'django-admin startproject' using Django 3.0.3. 5 | 6 | For more information on this file, see 7 | https://docs.djangoproject.com/en/3.0/topics/settings/ 8 | 9 | For the full list of settings and their values, see 10 | https://docs.djangoproject.com/en/3.0/ref/settings/ 11 | """ 12 | 13 | import os 14 | 15 | # Build paths inside the project like this: os.path.join(BASE_DIR, ...) 16 | BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) 17 | 18 | 19 | # Quick-start development settings - unsuitable for production 20 | # See https://docs.djangoproject.com/en/3.0/howto/deployment/checklist/ 21 | 22 | # SECURITY WARNING: keep the secret key used in production secret! 23 | SECRET_KEY = 'i(+%se(h0ozh7v8e=p+s*yu*ijb66pvqt2h(i9upcyald-_a57' 24 | 25 | # SECURITY WARNING: don't run with debug turned on in production! 26 | DEBUG = True 27 | 28 | ALLOWED_HOSTS = [] 29 | 30 | 31 | # Application definition 32 | 33 | INSTALLED_APPS = [ 34 | 'django.contrib.admin', 35 | 'django.contrib.auth', 36 | 'django.contrib.contenttypes', 37 | 'django.contrib.sessions', 38 | 'django.contrib.messages', 39 | 'django.contrib.staticfiles', 40 | 'firstApp', 41 | ] 42 | 43 | MIDDLEWARE = [ 44 | 'django.middleware.security.SecurityMiddleware', 45 | 'django.contrib.sessions.middleware.SessionMiddleware', 46 | 'django.middleware.common.CommonMiddleware', 47 | 'django.middleware.csrf.CsrfViewMiddleware', 48 | 'django.contrib.auth.middleware.AuthenticationMiddleware', 49 | 'django.contrib.messages.middleware.MessageMiddleware', 50 | 'django.middleware.clickjacking.XFrameOptionsMiddleware', 51 | ] 52 | 53 | ROOT_URLCONF = 'imageNetProj.urls' 54 | 55 | TEMPLATES = [ 56 | { 57 | 'BACKEND': 'django.template.backends.django.DjangoTemplates', 58 | 'DIRS': [os.path.join(BASE_DIR,'template')], 59 | 'APP_DIRS': True, 60 | 'OPTIONS': { 61 | 'context_processors': [ 62 | 'django.template.context_processors.debug', 63 | 'django.template.context_processors.request', 64 | 'django.contrib.auth.context_processors.auth', 65 | 'django.contrib.messages.context_processors.messages', 66 | ], 67 | }, 68 | }, 69 | ] 70 | 71 | WSGI_APPLICATION = 'imageNetProj.wsgi.application' 72 | 73 | 74 | # Database 75 | # https://docs.djangoproject.com/en/3.0/ref/settings/#databases 76 | 77 | DATABASES = { 78 | 'default': { 79 | 'ENGINE': 'django.db.backends.sqlite3', 80 | 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), 81 | } 82 | } 83 | 84 | 85 | # Password validation 86 | # https://docs.djangoproject.com/en/3.0/ref/settings/#auth-password-validators 87 | 88 | AUTH_PASSWORD_VALIDATORS = [ 89 | { 90 | 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', 91 | }, 92 | { 93 | 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', 94 | }, 95 | { 96 | 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', 97 | }, 98 | { 99 | 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', 100 | }, 101 | ] 102 | 103 | 104 | # Internationalization 105 | # https://docs.djangoproject.com/en/3.0/topics/i18n/ 106 | 107 | LANGUAGE_CODE = 'en-us' 108 | 109 | TIME_ZONE = 'UTC' 110 | 111 | USE_I18N = True 112 | 113 | USE_L10N = True 114 | 115 | USE_TZ = True 116 | 117 | 118 | # Static files (CSS, JavaScript, Images) 119 | # https://docs.djangoproject.com/en/3.0/howto/static-files/ 120 | 121 | STATIC_URL = '/static/' 122 | STATIC_ROOT = os.path.join(BASE_DIR,'static') 123 | 124 | 125 | MEDIA_URL = '/media/' 126 | MEDIA_ROOT = os.path.join(BASE_DIR,'media') -------------------------------------------------------------------------------- /imageNetProj/urls.py: -------------------------------------------------------------------------------- 1 | """imageNetProj URL Configuration 2 | 3 | The `urlpatterns` list routes URLs to views. For more information please see: 4 | https://docs.djangoproject.com/en/3.0/topics/http/urls/ 5 | Examples: 6 | Function views 7 | 1. Add an import: from my_app import views 8 | 2. Add a URL to urlpatterns: path('', views.home, name='home') 9 | Class-based views 10 | 1. Add an import: from other_app.views import Home 11 | 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') 12 | Including another URLconf 13 | 1. Import the include() function: from django.urls import include, path 14 | 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) 15 | """ 16 | from django.contrib import admin 17 | from django.urls import path 18 | from django.conf.urls import url 19 | from firstApp import views 20 | from django.conf.urls.static import static 21 | from django.conf import settings 22 | 23 | urlpatterns = [ 24 | path('admin/', admin.site.urls), 25 | url('^$',views.index,name='homepage'), 26 | url('predictImage',views.predictImage,name='predictImage'), 27 | url('viewDataBase',views.viewDataBase,name='viewDataBase'), 28 | ] 29 | 30 | urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT) -------------------------------------------------------------------------------- /imageNetProj/wsgi.py: -------------------------------------------------------------------------------- 1 | """ 2 | WSGI config for imageNetProj project. 3 | 4 | It exposes the WSGI callable as a module-level variable named ``application``. 5 | 6 | For more information on this file, see 7 | https://docs.djangoproject.com/en/3.0/howto/deployment/wsgi/ 8 | """ 9 | 10 | import os 11 | 12 | from django.core.wsgi import get_wsgi_application 13 | 14 | os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'imageNetProj.settings') 15 | 16 | application = get_wsgi_application() 17 | -------------------------------------------------------------------------------- /manage.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | """Django's command-line utility for administrative tasks.""" 3 | import os 4 | import sys 5 | 6 | 7 | def main(): 8 | os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'imageNetProj.settings') 9 | try: 10 | from django.core.management import execute_from_command_line 11 | except ImportError as exc: 12 | raise ImportError( 13 | "Couldn't import Django. Are you sure it's installed and " 14 | "available on your PYTHONPATH environment variable? Did you " 15 | "forget to activate a virtual environment?" 16 | ) from exc 17 | execute_from_command_line(sys.argv) 18 | 19 | 20 | if __name__ == '__main__': 21 | main() 22 | -------------------------------------------------------------------------------- /media/bird-article-s.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/media/bird-article-s.png -------------------------------------------------------------------------------- /media/bird-article-s_5I9dh1o.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/media/bird-article-s_5I9dh1o.png -------------------------------------------------------------------------------- /media/bird-article-s_90vhIi8.png: 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-------------------------------------------------------------------------------- /models/MobileNetModelImagenet.h5: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/models/MobileNetModelImagenet.h5 -------------------------------------------------------------------------------- /models/imagenet_classes.json: -------------------------------------------------------------------------------- 1 | {"0": ["n01440764", "tench"], "1": ["n01443537", "goldfish"], "2": ["n01484850", "great_white_shark"], "3": ["n01491361", "tiger_shark"], "4": ["n01494475", "hammerhead"], "5": ["n01496331", "electric_ray"], "6": ["n01498041", "stingray"], "7": ["n01514668", "cock"], "8": ["n01514859", "hen"], "9": ["n01518878", "ostrich"], "10": ["n01530575", "brambling"], "11": ["n01531178", "goldfinch"], "12": ["n01532829", "house_finch"], "13": ["n01534433", "junco"], "14": ["n01537544", "indigo_bunting"], "15": ["n01558993", "robin"], "16": ["n01560419", "bulbul"], "17": ["n01580077", "jay"], "18": ["n01582220", "magpie"], "19": ["n01592084", "chickadee"], "20": ["n01601694", "water_ouzel"], "21": ["n01608432", "kite"], "22": ["n01614925", "bald_eagle"], "23": ["n01616318", "vulture"], "24": ["n01622779", "great_grey_owl"], "25": ["n01629819", "European_fire_salamander"], "26": ["n01630670", "common_newt"], "27": ["n01631663", "eft"], "28": ["n01632458", "spotted_salamander"], "29": ["n01632777", "axolotl"], "30": ["n01641577", "bullfrog"], "31": ["n01644373", "tree_frog"], "32": ["n01644900", "tailed_frog"], "33": ["n01664065", "loggerhead"], "34": ["n01665541", "leatherback_turtle"], "35": ["n01667114", "mud_turtle"], "36": ["n01667778", "terrapin"], "37": ["n01669191", "box_turtle"], "38": ["n01675722", "banded_gecko"], "39": ["n01677366", "common_iguana"], "40": ["n01682714", "American_chameleon"], "41": ["n01685808", "whiptail"], "42": ["n01687978", "agama"], "43": ["n01688243", "frilled_lizard"], "44": ["n01689811", "alligator_lizard"], "45": ["n01692333", "Gila_monster"], "46": ["n01693334", "green_lizard"], "47": ["n01694178", "African_chameleon"], "48": ["n01695060", "Komodo_dragon"], "49": ["n01697457", "African_crocodile"], "50": ["n01698640", "American_alligator"], "51": ["n01704323", "triceratops"], "52": ["n01728572", "thunder_snake"], "53": ["n01728920", "ringneck_snake"], "54": ["n01729322", "hognose_snake"], "55": ["n01729977", "green_snake"], "56": ["n01734418", "king_snake"], "57": ["n01735189", "garter_snake"], "58": ["n01737021", "water_snake"], "59": ["n01739381", "vine_snake"], "60": ["n01740131", "night_snake"], "61": ["n01742172", "boa_constrictor"], "62": ["n01744401", "rock_python"], "63": ["n01748264", "Indian_cobra"], "64": ["n01749939", "green_mamba"], "65": ["n01751748", "sea_snake"], "66": ["n01753488", "horned_viper"], "67": ["n01755581", "diamondback"], "68": ["n01756291", "sidewinder"], "69": ["n01768244", "trilobite"], "70": ["n01770081", "harvestman"], "71": ["n01770393", "scorpion"], "72": ["n01773157", "black_and_gold_garden_spider"], "73": ["n01773549", "barn_spider"], "74": ["n01773797", "garden_spider"], "75": ["n01774384", "black_widow"], "76": ["n01774750", "tarantula"], "77": ["n01775062", "wolf_spider"], "78": ["n01776313", "tick"], "79": ["n01784675", "centipede"], "80": ["n01795545", "black_grouse"], "81": ["n01796340", "ptarmigan"], "82": ["n01797886", "ruffed_grouse"], "83": ["n01798484", "prairie_chicken"], "84": ["n01806143", "peacock"], "85": ["n01806567", "quail"], "86": ["n01807496", "partridge"], "87": ["n01817953", "African_grey"], "88": ["n01818515", "macaw"], "89": ["n01819313", "sulphur-crested_cockatoo"], "90": ["n01820546", "lorikeet"], "91": ["n01824575", "coucal"], "92": ["n01828970", "bee_eater"], "93": ["n01829413", "hornbill"], "94": ["n01833805", "hummingbird"], "95": ["n01843065", "jacamar"], "96": ["n01843383", "toucan"], "97": ["n01847000", "drake"], "98": ["n01855032", "red-breasted_merganser"], "99": ["n01855672", "goose"], "100": ["n01860187", "black_swan"], "101": ["n01871265", "tusker"], "102": ["n01872401", "echidna"], "103": ["n01873310", "platypus"], "104": ["n01877812", "wallaby"], "105": ["n01882714", "koala"], "106": ["n01883070", "wombat"], "107": ["n01910747", "jellyfish"], "108": ["n01914609", "sea_anemone"], "109": ["n01917289", "brain_coral"], "110": ["n01924916", "flatworm"], "111": ["n01930112", "nematode"], "112": ["n01943899", "conch"], "113": ["n01944390", "snail"], "114": ["n01945685", "slug"], "115": ["n01950731", "sea_slug"], "116": ["n01955084", "chiton"], "117": ["n01968897", "chambered_nautilus"], "118": ["n01978287", "Dungeness_crab"], "119": ["n01978455", "rock_crab"], "120": ["n01980166", "fiddler_crab"], "121": ["n01981276", "king_crab"], "122": ["n01983481", "American_lobster"], "123": ["n01984695", "spiny_lobster"], "124": ["n01985128", "crayfish"], "125": ["n01986214", "hermit_crab"], "126": ["n01990800", "isopod"], "127": ["n02002556", "white_stork"], "128": ["n02002724", "black_stork"], "129": ["n02006656", "spoonbill"], "130": ["n02007558", "flamingo"], "131": ["n02009229", "little_blue_heron"], "132": ["n02009912", "American_egret"], "133": ["n02011460", "bittern"], "134": ["n02012849", "crane"], "135": ["n02013706", "limpkin"], "136": ["n02017213", "European_gallinule"], "137": ["n02018207", "American_coot"], "138": ["n02018795", "bustard"], "139": ["n02025239", "ruddy_turnstone"], "140": ["n02027492", "red-backed_sandpiper"], "141": ["n02028035", "redshank"], "142": ["n02033041", "dowitcher"], "143": ["n02037110", "oystercatcher"], "144": ["n02051845", "pelican"], "145": ["n02056570", "king_penguin"], "146": ["n02058221", "albatross"], "147": ["n02066245", "grey_whale"], "148": ["n02071294", "killer_whale"], "149": ["n02074367", "dugong"], "150": ["n02077923", "sea_lion"], "151": ["n02085620", "Chihuahua"], "152": ["n02085782", "Japanese_spaniel"], "153": ["n02085936", "Maltese_dog"], "154": ["n02086079", "Pekinese"], "155": ["n02086240", "Shih-Tzu"], "156": ["n02086646", "Blenheim_spaniel"], "157": ["n02086910", "papillon"], "158": ["n02087046", "toy_terrier"], "159": ["n02087394", "Rhodesian_ridgeback"], "160": ["n02088094", "Afghan_hound"], "161": ["n02088238", "basset"], "162": ["n02088364", "beagle"], "163": ["n02088466", "bloodhound"], "164": ["n02088632", "bluetick"], "165": ["n02089078", "black-and-tan_coonhound"], "166": ["n02089867", "Walker_hound"], "167": ["n02089973", "English_foxhound"], "168": ["n02090379", "redbone"], "169": ["n02090622", "borzoi"], "170": ["n02090721", "Irish_wolfhound"], "171": ["n02091032", "Italian_greyhound"], "172": ["n02091134", "whippet"], "173": ["n02091244", "Ibizan_hound"], "174": ["n02091467", "Norwegian_elkhound"], "175": ["n02091635", "otterhound"], "176": ["n02091831", "Saluki"], "177": ["n02092002", "Scottish_deerhound"], "178": ["n02092339", "Weimaraner"], "179": ["n02093256", "Staffordshire_bullterrier"], "180": ["n02093428", "American_Staffordshire_terrier"], "181": ["n02093647", "Bedlington_terrier"], "182": ["n02093754", "Border_terrier"], "183": ["n02093859", "Kerry_blue_terrier"], "184": ["n02093991", "Irish_terrier"], "185": ["n02094114", "Norfolk_terrier"], "186": ["n02094258", "Norwich_terrier"], "187": ["n02094433", "Yorkshire_terrier"], "188": ["n02095314", "wire-haired_fox_terrier"], "189": ["n02095570", "Lakeland_terrier"], "190": ["n02095889", "Sealyham_terrier"], "191": ["n02096051", "Airedale"], "192": ["n02096177", "cairn"], "193": ["n02096294", "Australian_terrier"], "194": ["n02096437", "Dandie_Dinmont"], "195": ["n02096585", "Boston_bull"], "196": ["n02097047", "miniature_schnauzer"], "197": ["n02097130", "giant_schnauzer"], "198": ["n02097209", "standard_schnauzer"], "199": ["n02097298", "Scotch_terrier"], "200": ["n02097474", "Tibetan_terrier"], "201": ["n02097658", "silky_terrier"], "202": ["n02098105", "soft-coated_wheaten_terrier"], "203": ["n02098286", "West_Highland_white_terrier"], "204": ["n02098413", "Lhasa"], "205": ["n02099267", "flat-coated_retriever"], "206": ["n02099429", "curly-coated_retriever"], "207": ["n02099601", "golden_retriever"], "208": ["n02099712", "Labrador_retriever"], "209": ["n02099849", "Chesapeake_Bay_retriever"], "210": ["n02100236", "German_short-haired_pointer"], "211": ["n02100583", "vizsla"], "212": ["n02100735", "English_setter"], "213": ["n02100877", "Irish_setter"], "214": ["n02101006", "Gordon_setter"], "215": ["n02101388", "Brittany_spaniel"], "216": ["n02101556", "clumber"], "217": ["n02102040", "English_springer"], "218": ["n02102177", "Welsh_springer_spaniel"], "219": ["n02102318", "cocker_spaniel"], "220": ["n02102480", "Sussex_spaniel"], "221": ["n02102973", "Irish_water_spaniel"], "222": ["n02104029", "kuvasz"], "223": ["n02104365", "schipperke"], "224": ["n02105056", "groenendael"], "225": ["n02105162", "malinois"], "226": ["n02105251", "briard"], "227": ["n02105412", "kelpie"], "228": ["n02105505", "komondor"], "229": ["n02105641", "Old_English_sheepdog"], "230": ["n02105855", "Shetland_sheepdog"], "231": ["n02106030", "collie"], "232": ["n02106166", "Border_collie"], "233": ["n02106382", "Bouvier_des_Flandres"], "234": ["n02106550", "Rottweiler"], "235": ["n02106662", "German_shepherd"], "236": ["n02107142", "Doberman"], "237": ["n02107312", "miniature_pinscher"], "238": ["n02107574", "Greater_Swiss_Mountain_dog"], "239": ["n02107683", "Bernese_mountain_dog"], "240": ["n02107908", "Appenzeller"], "241": ["n02108000", "EntleBucher"], "242": ["n02108089", "boxer"], "243": ["n02108422", "bull_mastiff"], "244": ["n02108551", "Tibetan_mastiff"], "245": ["n02108915", "French_bulldog"], "246": ["n02109047", "Great_Dane"], "247": ["n02109525", "Saint_Bernard"], "248": ["n02109961", "Eskimo_dog"], "249": ["n02110063", "malamute"], "250": ["n02110185", "Siberian_husky"], "251": ["n02110341", "dalmatian"], "252": ["n02110627", "affenpinscher"], "253": ["n02110806", "basenji"], "254": ["n02110958", "pug"], "255": ["n02111129", "Leonberg"], "256": ["n02111277", "Newfoundland"], "257": ["n02111500", "Great_Pyrenees"], "258": ["n02111889", "Samoyed"], "259": ["n02112018", "Pomeranian"], "260": ["n02112137", "chow"], "261": ["n02112350", "keeshond"], "262": ["n02112706", "Brabancon_griffon"], "263": ["n02113023", "Pembroke"], "264": ["n02113186", "Cardigan"], "265": ["n02113624", "toy_poodle"], "266": ["n02113712", "miniature_poodle"], "267": ["n02113799", "standard_poodle"], "268": ["n02113978", "Mexican_hairless"], "269": ["n02114367", "timber_wolf"], "270": ["n02114548", "white_wolf"], "271": ["n02114712", "red_wolf"], "272": ["n02114855", "coyote"], "273": ["n02115641", "dingo"], "274": ["n02115913", "dhole"], "275": ["n02116738", "African_hunting_dog"], "276": ["n02117135", "hyena"], "277": ["n02119022", "red_fox"], "278": ["n02119789", "kit_fox"], "279": ["n02120079", "Arctic_fox"], "280": ["n02120505", "grey_fox"], "281": ["n02123045", "tabby"], "282": ["n02123159", "tiger_cat"], "283": ["n02123394", "Persian_cat"], "284": ["n02123597", "Siamese_cat"], "285": ["n02124075", "Egyptian_cat"], "286": ["n02125311", "cougar"], "287": ["n02127052", "lynx"], "288": ["n02128385", "leopard"], "289": ["n02128757", "snow_leopard"], "290": ["n02128925", "jaguar"], "291": ["n02129165", "lion"], "292": ["n02129604", "tiger"], "293": ["n02130308", "cheetah"], "294": ["n02132136", "brown_bear"], "295": ["n02133161", "American_black_bear"], "296": ["n02134084", "ice_bear"], "297": ["n02134418", "sloth_bear"], "298": ["n02137549", "mongoose"], "299": ["n02138441", "meerkat"], "300": ["n02165105", "tiger_beetle"], "301": ["n02165456", "ladybug"], "302": ["n02167151", "ground_beetle"], "303": ["n02168699", "long-horned_beetle"], "304": ["n02169497", "leaf_beetle"], "305": ["n02172182", "dung_beetle"], "306": ["n02174001", "rhinoceros_beetle"], "307": ["n02177972", "weevil"], "308": ["n02190166", "fly"], "309": ["n02206856", "bee"], "310": ["n02219486", "ant"], "311": ["n02226429", "grasshopper"], "312": ["n02229544", "cricket"], "313": ["n02231487", "walking_stick"], "314": ["n02233338", "cockroach"], "315": ["n02236044", "mantis"], "316": ["n02256656", "cicada"], "317": ["n02259212", "leafhopper"], "318": ["n02264363", "lacewing"], "319": ["n02268443", "dragonfly"], "320": ["n02268853", "damselfly"], "321": ["n02276258", "admiral"], "322": ["n02277742", "ringlet"], "323": ["n02279972", "monarch"], "324": ["n02280649", "cabbage_butterfly"], "325": ["n02281406", "sulphur_butterfly"], "326": ["n02281787", "lycaenid"], "327": ["n02317335", "starfish"], "328": ["n02319095", "sea_urchin"], "329": ["n02321529", "sea_cucumber"], "330": ["n02325366", "wood_rabbit"], "331": ["n02326432", "hare"], "332": ["n02328150", "Angora"], "333": ["n02342885", "hamster"], "334": ["n02346627", "porcupine"], "335": ["n02356798", "fox_squirrel"], "336": ["n02361337", "marmot"], "337": ["n02363005", "beaver"], "338": ["n02364673", "guinea_pig"], "339": ["n02389026", "sorrel"], "340": ["n02391049", "zebra"], "341": ["n02395406", "hog"], "342": ["n02396427", "wild_boar"], "343": ["n02397096", "warthog"], "344": ["n02398521", "hippopotamus"], "345": ["n02403003", "ox"], "346": ["n02408429", "water_buffalo"], "347": ["n02410509", "bison"], "348": ["n02412080", "ram"], "349": ["n02415577", "bighorn"], "350": ["n02417914", "ibex"], "351": ["n02422106", "hartebeest"], "352": ["n02422699", "impala"], "353": ["n02423022", "gazelle"], "354": ["n02437312", "Arabian_camel"], "355": ["n02437616", "llama"], "356": ["n02441942", "weasel"], "357": ["n02442845", "mink"], "358": ["n02443114", "polecat"], "359": ["n02443484", "black-footed_ferret"], "360": ["n02444819", "otter"], "361": ["n02445715", "skunk"], "362": ["n02447366", "badger"], "363": ["n02454379", "armadillo"], "364": ["n02457408", "three-toed_sloth"], "365": ["n02480495", "orangutan"], "366": ["n02480855", "gorilla"], "367": ["n02481823", "chimpanzee"], "368": ["n02483362", "gibbon"], "369": ["n02483708", "siamang"], "370": ["n02484975", "guenon"], "371": ["n02486261", "patas"], "372": ["n02486410", "baboon"], "373": ["n02487347", "macaque"], "374": ["n02488291", "langur"], "375": ["n02488702", "colobus"], "376": ["n02489166", "proboscis_monkey"], "377": ["n02490219", "marmoset"], "378": ["n02492035", "capuchin"], "379": ["n02492660", "howler_monkey"], "380": ["n02493509", "titi"], "381": ["n02493793", "spider_monkey"], "382": ["n02494079", "squirrel_monkey"], "383": ["n02497673", "Madagascar_cat"], "384": ["n02500267", "indri"], "385": ["n02504013", "Indian_elephant"], "386": ["n02504458", "African_elephant"], "387": ["n02509815", "lesser_panda"], "388": ["n02510455", "giant_panda"], "389": ["n02514041", "barracouta"], "390": ["n02526121", "eel"], "391": ["n02536864", "coho"], "392": ["n02606052", "rock_beauty"], "393": ["n02607072", "anemone_fish"], "394": ["n02640242", "sturgeon"], "395": ["n02641379", "gar"], "396": ["n02643566", "lionfish"], "397": ["n02655020", "puffer"], "398": ["n02666196", "abacus"], "399": ["n02667093", "abaya"], "400": ["n02669723", "academic_gown"], "401": ["n02672831", "accordion"], "402": ["n02676566", "acoustic_guitar"], "403": ["n02687172", "aircraft_carrier"], "404": ["n02690373", "airliner"], "405": ["n02692877", "airship"], "406": ["n02699494", "altar"], "407": ["n02701002", "ambulance"], "408": ["n02704792", "amphibian"], "409": ["n02708093", "analog_clock"], "410": ["n02727426", "apiary"], "411": ["n02730930", "apron"], "412": ["n02747177", "ashcan"], "413": ["n02749479", "assault_rifle"], "414": ["n02769748", "backpack"], "415": ["n02776631", "bakery"], "416": ["n02777292", "balance_beam"], "417": ["n02782093", "balloon"], "418": ["n02783161", "ballpoint"], "419": ["n02786058", "Band_Aid"], "420": ["n02787622", "banjo"], "421": ["n02788148", "bannister"], "422": ["n02790996", "barbell"], "423": ["n02791124", "barber_chair"], "424": ["n02791270", "barbershop"], "425": ["n02793495", "barn"], "426": ["n02794156", "barometer"], "427": ["n02795169", "barrel"], "428": ["n02797295", "barrow"], "429": ["n02799071", "baseball"], "430": ["n02802426", "basketball"], "431": ["n02804414", "bassinet"], "432": ["n02804610", "bassoon"], "433": ["n02807133", "bathing_cap"], "434": ["n02808304", "bath_towel"], "435": ["n02808440", "bathtub"], "436": ["n02814533", "beach_wagon"], "437": ["n02814860", "beacon"], "438": ["n02815834", "beaker"], "439": ["n02817516", "bearskin"], "440": ["n02823428", "beer_bottle"], "441": ["n02823750", "beer_glass"], "442": ["n02825657", "bell_cote"], "443": ["n02834397", "bib"], "444": ["n02835271", "bicycle-built-for-two"], "445": ["n02837789", "bikini"], "446": ["n02840245", "binder"], "447": ["n02841315", "binoculars"], "448": ["n02843684", "birdhouse"], "449": ["n02859443", "boathouse"], "450": ["n02860847", "bobsled"], "451": ["n02865351", "bolo_tie"], "452": ["n02869837", "bonnet"], "453": ["n02870880", "bookcase"], "454": ["n02871525", "bookshop"], "455": ["n02877765", "bottlecap"], "456": ["n02879718", "bow"], "457": ["n02883205", "bow_tie"], "458": ["n02892201", "brass"], "459": ["n02892767", "brassiere"], "460": ["n02894605", "breakwater"], "461": ["n02895154", "breastplate"], "462": ["n02906734", "broom"], "463": ["n02909870", "bucket"], "464": ["n02910353", "buckle"], "465": ["n02916936", "bulletproof_vest"], "466": ["n02917067", "bullet_train"], "467": ["n02927161", "butcher_shop"], "468": ["n02930766", "cab"], "469": ["n02939185", "caldron"], "470": ["n02948072", "candle"], "471": ["n02950826", "cannon"], "472": ["n02951358", "canoe"], "473": ["n02951585", "can_opener"], "474": ["n02963159", "cardigan"], "475": ["n02965783", "car_mirror"], "476": ["n02966193", "carousel"], "477": ["n02966687", "carpenter's_kit"], "478": ["n02971356", "carton"], "479": ["n02974003", "car_wheel"], "480": ["n02977058", "cash_machine"], "481": ["n02978881", "cassette"], "482": ["n02979186", "cassette_player"], "483": ["n02980441", "castle"], "484": ["n02981792", "catamaran"], "485": ["n02988304", "CD_player"], "486": ["n02992211", "cello"], "487": ["n02992529", "cellular_telephone"], "488": ["n02999410", "chain"], "489": ["n03000134", "chainlink_fence"], "490": ["n03000247", "chain_mail"], "491": ["n03000684", "chain_saw"], "492": ["n03014705", "chest"], "493": ["n03016953", "chiffonier"], "494": ["n03017168", "chime"], "495": ["n03018349", "china_cabinet"], "496": ["n03026506", "Christmas_stocking"], "497": ["n03028079", "church"], "498": ["n03032252", "cinema"], "499": ["n03041632", "cleaver"], "500": ["n03042490", "cliff_dwelling"], "501": ["n03045698", "cloak"], "502": ["n03047690", "clog"], "503": ["n03062245", "cocktail_shaker"], "504": ["n03063599", "coffee_mug"], "505": ["n03063689", "coffeepot"], "506": ["n03065424", "coil"], "507": ["n03075370", "combination_lock"], "508": ["n03085013", "computer_keyboard"], "509": ["n03089624", "confectionery"], "510": ["n03095699", "container_ship"], "511": ["n03100240", "convertible"], "512": ["n03109150", "corkscrew"], "513": ["n03110669", "cornet"], "514": ["n03124043", "cowboy_boot"], "515": ["n03124170", "cowboy_hat"], "516": ["n03125729", "cradle"], "517": ["n03126707", "crane_2"], "518": ["n03127747", "crash_helmet"], "519": ["n03127925", "crate"], "520": ["n03131574", "crib"], "521": ["n03133878", "Crock_Pot"], "522": ["n03134739", "croquet_ball"], "523": ["n03141823", "crutch"], "524": ["n03146219", "cuirass"], "525": ["n03160309", "dam"], "526": ["n03179701", "desk"], "527": ["n03180011", "desktop_computer"], "528": ["n03187595", "dial_telephone"], "529": ["n03188531", "diaper"], "530": ["n03196217", "digital_clock"], "531": ["n03197337", "digital_watch"], "532": ["n03201208", "dining_table"], "533": ["n03207743", "dishrag"], "534": ["n03207941", "dishwasher"], "535": ["n03208938", "disk_brake"], "536": ["n03216828", "dock"], "537": ["n03218198", "dogsled"], "538": ["n03220513", "dome"], "539": ["n03223299", "doormat"], "540": ["n03240683", "drilling_platform"], "541": ["n03249569", "drum"], "542": ["n03250847", "drumstick"], "543": ["n03255030", "dumbbell"], "544": ["n03259280", "Dutch_oven"], "545": ["n03271574", "electric_fan"], "546": ["n03272010", "electric_guitar"], "547": ["n03272562", "electric_locomotive"], "548": ["n03290653", "entertainment_center"], "549": ["n03291819", "envelope"], "550": ["n03297495", "espresso_maker"], "551": ["n03314780", "face_powder"], "552": ["n03325584", "feather_boa"], "553": ["n03337140", "file"], "554": ["n03344393", "fireboat"], "555": ["n03345487", "fire_engine"], "556": ["n03347037", "fire_screen"], "557": ["n03355925", "flagpole"], "558": ["n03372029", "flute"], "559": ["n03376595", "folding_chair"], "560": ["n03379051", "football_helmet"], "561": ["n03384352", "forklift"], "562": ["n03388043", "fountain"], "563": ["n03388183", "fountain_pen"], "564": ["n03388549", "four-poster"], "565": ["n03393912", "freight_car"], "566": ["n03394916", "French_horn"], "567": ["n03400231", "frying_pan"], "568": ["n03404251", "fur_coat"], "569": ["n03417042", "garbage_truck"], "570": ["n03424325", "gasmask"], "571": ["n03425413", "gas_pump"], "572": ["n03443371", "goblet"], "573": ["n03444034", "go-kart"], "574": ["n03445777", "golf_ball"], "575": ["n03445924", "golfcart"], "576": ["n03447447", "gondola"], "577": ["n03447721", "gong"], "578": ["n03450230", "gown"], "579": ["n03452741", "grand_piano"], "580": ["n03457902", "greenhouse"], "581": ["n03459775", "grille"], "582": ["n03461385", "grocery_store"], "583": ["n03467068", "guillotine"], "584": ["n03476684", "hair_slide"], "585": ["n03476991", "hair_spray"], "586": ["n03478589", "half_track"], "587": ["n03481172", "hammer"], "588": ["n03482405", "hamper"], "589": ["n03483316", "hand_blower"], "590": ["n03485407", "hand-held_computer"], "591": ["n03485794", "handkerchief"], "592": ["n03492542", "hard_disc"], "593": ["n03494278", "harmonica"], "594": ["n03495258", "harp"], "595": ["n03496892", "harvester"], "596": ["n03498962", "hatchet"], "597": ["n03527444", "holster"], "598": ["n03529860", "home_theater"], "599": ["n03530642", "honeycomb"], "600": ["n03532672", "hook"], "601": ["n03534580", "hoopskirt"], "602": ["n03535780", "horizontal_bar"], "603": ["n03538406", "horse_cart"], "604": ["n03544143", "hourglass"], "605": ["n03584254", "iPod"], "606": ["n03584829", "iron"], "607": ["n03590841", "jack-o'-lantern"], "608": ["n03594734", "jean"], "609": ["n03594945", "jeep"], "610": ["n03595614", "jersey"], "611": ["n03598930", "jigsaw_puzzle"], "612": ["n03599486", "jinrikisha"], "613": ["n03602883", "joystick"], "614": ["n03617480", "kimono"], "615": ["n03623198", "knee_pad"], "616": ["n03627232", "knot"], "617": ["n03630383", "lab_coat"], "618": ["n03633091", "ladle"], "619": ["n03637318", "lampshade"], "620": ["n03642806", "laptop"], "621": ["n03649909", "lawn_mower"], "622": ["n03657121", "lens_cap"], "623": ["n03658185", "letter_opener"], "624": ["n03661043", "library"], "625": ["n03662601", "lifeboat"], "626": ["n03666591", "lighter"], "627": ["n03670208", "limousine"], "628": ["n03673027", "liner"], "629": ["n03676483", "lipstick"], "630": ["n03680355", "Loafer"], "631": ["n03690938", "lotion"], "632": ["n03691459", "loudspeaker"], "633": ["n03692522", "loupe"], "634": ["n03697007", "lumbermill"], "635": ["n03706229", "magnetic_compass"], "636": ["n03709823", "mailbag"], "637": ["n03710193", "mailbox"], "638": ["n03710637", "maillot"], "639": ["n03710721", "maillot_2"], "640": ["n03717622", "manhole_cover"], "641": ["n03720891", "maraca"], "642": ["n03721384", "marimba"], "643": ["n03724870", "mask"], "644": ["n03729826", "matchstick"], "645": ["n03733131", "maypole"], "646": ["n03733281", "maze"], "647": ["n03733805", "measuring_cup"], "648": ["n03742115", "medicine_chest"], "649": ["n03743016", "megalith"], "650": ["n03759954", "microphone"], "651": ["n03761084", "microwave"], "652": ["n03763968", "military_uniform"], "653": ["n03764736", "milk_can"], "654": ["n03769881", "minibus"], "655": ["n03770439", "miniskirt"], "656": ["n03770679", "minivan"], "657": ["n03773504", "missile"], "658": ["n03775071", "mitten"], "659": ["n03775546", "mixing_bowl"], "660": ["n03776460", "mobile_home"], "661": ["n03777568", "Model_T"], "662": ["n03777754", "modem"], "663": ["n03781244", "monastery"], "664": ["n03782006", "monitor"], "665": ["n03785016", "moped"], "666": ["n03786901", "mortar"], "667": ["n03787032", "mortarboard"], "668": ["n03788195", "mosque"], "669": ["n03788365", "mosquito_net"], "670": ["n03791053", "motor_scooter"], "671": ["n03792782", "mountain_bike"], "672": ["n03792972", "mountain_tent"], "673": ["n03793489", "mouse"], "674": ["n03794056", "mousetrap"], "675": ["n03796401", "moving_van"], "676": ["n03803284", "muzzle"], "677": ["n03804744", "nail"], "678": ["n03814639", "neck_brace"], "679": ["n03814906", "necklace"], "680": ["n03825788", "nipple"], "681": ["n03832673", "notebook"], "682": ["n03837869", "obelisk"], "683": ["n03838899", "oboe"], "684": ["n03840681", "ocarina"], "685": ["n03841143", "odometer"], "686": ["n03843555", "oil_filter"], "687": ["n03854065", "organ"], "688": ["n03857828", "oscilloscope"], "689": ["n03866082", "overskirt"], "690": ["n03868242", "oxcart"], "691": ["n03868863", "oxygen_mask"], "692": ["n03871628", "packet"], "693": ["n03873416", "paddle"], "694": ["n03874293", "paddlewheel"], "695": ["n03874599", "padlock"], "696": ["n03876231", "paintbrush"], "697": ["n03877472", "pajama"], "698": ["n03877845", "palace"], "699": ["n03884397", "panpipe"], "700": ["n03887697", "paper_towel"], "701": ["n03888257", "parachute"], "702": ["n03888605", "parallel_bars"], "703": ["n03891251", "park_bench"], "704": ["n03891332", "parking_meter"], "705": ["n03895866", "passenger_car"], "706": ["n03899768", "patio"], "707": ["n03902125", "pay-phone"], "708": ["n03903868", "pedestal"], "709": ["n03908618", "pencil_box"], "710": ["n03908714", "pencil_sharpener"], "711": ["n03916031", "perfume"], "712": ["n03920288", "Petri_dish"], "713": ["n03924679", "photocopier"], "714": ["n03929660", "pick"], "715": ["n03929855", "pickelhaube"], "716": ["n03930313", "picket_fence"], "717": ["n03930630", "pickup"], "718": ["n03933933", "pier"], "719": ["n03935335", "piggy_bank"], "720": ["n03937543", "pill_bottle"], "721": ["n03938244", "pillow"], "722": ["n03942813", "ping-pong_ball"], "723": ["n03944341", "pinwheel"], "724": ["n03947888", "pirate"], "725": ["n03950228", "pitcher"], "726": ["n03954731", "plane"], "727": ["n03956157", "planetarium"], "728": ["n03958227", "plastic_bag"], "729": ["n03961711", "plate_rack"], "730": ["n03967562", "plow"], "731": ["n03970156", "plunger"], "732": ["n03976467", "Polaroid_camera"], "733": ["n03976657", "pole"], "734": ["n03977966", "police_van"], "735": ["n03980874", "poncho"], "736": ["n03982430", "pool_table"], "737": ["n03983396", "pop_bottle"], "738": ["n03991062", "pot"], "739": ["n03992509", "potter's_wheel"], "740": ["n03995372", "power_drill"], "741": ["n03998194", "prayer_rug"], "742": ["n04004767", "printer"], "743": ["n04005630", "prison"], "744": ["n04008634", "projectile"], "745": ["n04009552", "projector"], "746": ["n04019541", "puck"], "747": ["n04023962", "punching_bag"], "748": ["n04026417", "purse"], "749": ["n04033901", "quill"], "750": ["n04033995", "quilt"], "751": ["n04037443", "racer"], "752": ["n04039381", "racket"], "753": ["n04040759", "radiator"], "754": ["n04041544", "radio"], "755": ["n04044716", "radio_telescope"], "756": ["n04049303", "rain_barrel"], "757": ["n04065272", "recreational_vehicle"], "758": ["n04067472", "reel"], "759": ["n04069434", "reflex_camera"], "760": ["n04070727", "refrigerator"], "761": ["n04074963", "remote_control"], "762": ["n04081281", "restaurant"], "763": ["n04086273", "revolver"], "764": ["n04090263", "rifle"], "765": ["n04099969", "rocking_chair"], "766": ["n04111531", "rotisserie"], "767": ["n04116512", "rubber_eraser"], "768": ["n04118538", "rugby_ball"], "769": ["n04118776", "rule"], "770": ["n04120489", "running_shoe"], "771": ["n04125021", "safe"], "772": ["n04127249", "safety_pin"], "773": ["n04131690", "saltshaker"], "774": ["n04133789", "sandal"], "775": ["n04136333", "sarong"], "776": ["n04141076", "sax"], "777": ["n04141327", "scabbard"], "778": ["n04141975", "scale"], "779": ["n04146614", "school_bus"], "780": ["n04147183", "schooner"], "781": ["n04149813", "scoreboard"], "782": ["n04152593", "screen"], "783": ["n04153751", "screw"], "784": ["n04154565", "screwdriver"], "785": ["n04162706", "seat_belt"], "786": ["n04179913", "sewing_machine"], "787": ["n04192698", "shield"], "788": ["n04200800", "shoe_shop"], "789": ["n04201297", "shoji"], "790": ["n04204238", "shopping_basket"], "791": ["n04204347", "shopping_cart"], "792": ["n04208210", "shovel"], "793": ["n04209133", "shower_cap"], "794": ["n04209239", "shower_curtain"], "795": ["n04228054", "ski"], "796": ["n04229816", "ski_mask"], "797": ["n04235860", "sleeping_bag"], "798": ["n04238763", "slide_rule"], "799": ["n04239074", "sliding_door"], "800": ["n04243546", "slot"], "801": ["n04251144", "snorkel"], "802": ["n04252077", "snowmobile"], "803": ["n04252225", "snowplow"], "804": ["n04254120", "soap_dispenser"], "805": ["n04254680", "soccer_ball"], "806": ["n04254777", "sock"], "807": ["n04258138", "solar_dish"], "808": ["n04259630", "sombrero"], "809": ["n04263257", "soup_bowl"], "810": ["n04264628", "space_bar"], "811": ["n04265275", "space_heater"], "812": ["n04266014", "space_shuttle"], "813": ["n04270147", "spatula"], "814": ["n04273569", "speedboat"], "815": ["n04275548", "spider_web"], "816": ["n04277352", "spindle"], "817": ["n04285008", "sports_car"], "818": ["n04286575", "spotlight"], "819": ["n04296562", "stage"], "820": ["n04310018", "steam_locomotive"], "821": ["n04311004", "steel_arch_bridge"], "822": ["n04311174", "steel_drum"], "823": ["n04317175", "stethoscope"], "824": ["n04325704", "stole"], "825": ["n04326547", "stone_wall"], "826": ["n04328186", "stopwatch"], "827": ["n04330267", "stove"], "828": ["n04332243", "strainer"], "829": ["n04335435", "streetcar"], "830": ["n04336792", "stretcher"], "831": ["n04344873", "studio_couch"], "832": ["n04346328", "stupa"], "833": ["n04347754", "submarine"], "834": ["n04350905", "suit"], "835": ["n04355338", "sundial"], "836": ["n04355933", "sunglass"], "837": ["n04356056", "sunglasses"], "838": ["n04357314", "sunscreen"], "839": ["n04366367", "suspension_bridge"], "840": ["n04367480", "swab"], "841": ["n04370456", "sweatshirt"], "842": ["n04371430", "swimming_trunks"], "843": ["n04371774", "swing"], "844": ["n04372370", "switch"], "845": ["n04376876", "syringe"], "846": ["n04380533", "table_lamp"], "847": ["n04389033", "tank"], "848": ["n04392985", "tape_player"], "849": ["n04398044", "teapot"], "850": ["n04399382", "teddy"], "851": ["n04404412", "television"], "852": ["n04409515", "tennis_ball"], "853": ["n04417672", "thatch"], "854": ["n04418357", "theater_curtain"], "855": ["n04423845", "thimble"], "856": ["n04428191", "thresher"], "857": ["n04429376", "throne"], "858": ["n04435653", "tile_roof"], "859": ["n04442312", "toaster"], "860": ["n04443257", "tobacco_shop"], "861": ["n04447861", "toilet_seat"], "862": ["n04456115", "torch"], "863": ["n04458633", "totem_pole"], "864": ["n04461696", "tow_truck"], "865": ["n04462240", "toyshop"], "866": ["n04465501", "tractor"], "867": ["n04467665", "trailer_truck"], "868": ["n04476259", "tray"], "869": ["n04479046", "trench_coat"], "870": ["n04482393", "tricycle"], "871": ["n04483307", "trimaran"], "872": ["n04485082", "tripod"], "873": ["n04486054", "triumphal_arch"], "874": ["n04487081", "trolleybus"], "875": ["n04487394", "trombone"], "876": ["n04493381", "tub"], "877": ["n04501370", "turnstile"], "878": ["n04505470", "typewriter_keyboard"], "879": ["n04507155", "umbrella"], "880": ["n04509417", "unicycle"], "881": ["n04515003", "upright"], "882": ["n04517823", "vacuum"], "883": ["n04522168", "vase"], "884": ["n04523525", "vault"], "885": ["n04525038", "velvet"], "886": ["n04525305", "vending_machine"], "887": ["n04532106", "vestment"], "888": ["n04532670", "viaduct"], "889": ["n04536866", "violin"], "890": ["n04540053", "volleyball"], "891": ["n04542943", "waffle_iron"], "892": ["n04548280", "wall_clock"], "893": ["n04548362", "wallet"], "894": ["n04550184", "wardrobe"], "895": ["n04552348", "warplane"], "896": ["n04553703", "washbasin"], "897": ["n04554684", "washer"], "898": ["n04557648", "water_bottle"], "899": ["n04560804", "water_jug"], "900": ["n04562935", "water_tower"], "901": ["n04579145", "whiskey_jug"], "902": ["n04579432", "whistle"], "903": ["n04584207", "wig"], "904": ["n04589890", "window_screen"], "905": ["n04590129", "window_shade"], "906": ["n04591157", "Windsor_tie"], "907": ["n04591713", "wine_bottle"], "908": ["n04592741", "wing"], "909": ["n04596742", "wok"], "910": ["n04597913", "wooden_spoon"], "911": ["n04599235", "wool"], "912": ["n04604644", "worm_fence"], "913": ["n04606251", "wreck"], "914": ["n04612504", "yawl"], "915": ["n04613696", "yurt"], "916": ["n06359193", "web_site"], "917": ["n06596364", "comic_book"], "918": ["n06785654", "crossword_puzzle"], "919": ["n06794110", "street_sign"], "920": ["n06874185", "traffic_light"], "921": ["n07248320", "book_jacket"], "922": ["n07565083", "menu"], "923": ["n07579787", "plate"], "924": ["n07583066", "guacamole"], "925": ["n07584110", "consomme"], "926": ["n07590611", "hot_pot"], "927": ["n07613480", "trifle"], "928": ["n07614500", "ice_cream"], "929": ["n07615774", "ice_lolly"], "930": ["n07684084", "French_loaf"], "931": ["n07693725", "bagel"], "932": ["n07695742", "pretzel"], "933": ["n07697313", "cheeseburger"], "934": ["n07697537", "hotdog"], "935": ["n07711569", "mashed_potato"], "936": ["n07714571", "head_cabbage"], "937": ["n07714990", "broccoli"], "938": ["n07715103", "cauliflower"], "939": ["n07716358", "zucchini"], "940": ["n07716906", "spaghetti_squash"], "941": ["n07717410", "acorn_squash"], "942": ["n07717556", "butternut_squash"], "943": ["n07718472", "cucumber"], "944": ["n07718747", "artichoke"], "945": ["n07720875", "bell_pepper"], "946": ["n07730033", "cardoon"], "947": ["n07734744", "mushroom"], "948": ["n07742313", "Granny_Smith"], "949": ["n07745940", "strawberry"], "950": ["n07747607", "orange"], "951": ["n07749582", "lemon"], "952": ["n07753113", "fig"], "953": ["n07753275", "pineapple"], "954": ["n07753592", "banana"], "955": ["n07754684", "jackfruit"], "956": ["n07760859", "custard_apple"], "957": ["n07768694", "pomegranate"], "958": ["n07802026", "hay"], "959": ["n07831146", "carbonara"], "960": ["n07836838", "chocolate_sauce"], "961": ["n07860988", "dough"], "962": ["n07871810", "meat_loaf"], "963": ["n07873807", "pizza"], "964": ["n07875152", "potpie"], "965": ["n07880968", "burrito"], "966": ["n07892512", "red_wine"], "967": ["n07920052", "espresso"], "968": ["n07930864", "cup"], "969": ["n07932039", "eggnog"], "970": ["n09193705", "alp"], "971": ["n09229709", "bubble"], "972": ["n09246464", "cliff"], "973": ["n09256479", "coral_reef"], "974": ["n09288635", "geyser"], "975": ["n09332890", "lakeside"], "976": ["n09399592", "promontory"], "977": ["n09421951", "sandbar"], "978": ["n09428293", "seashore"], "979": ["n09468604", "valley"], "980": ["n09472597", "volcano"], "981": ["n09835506", "ballplayer"], "982": ["n10148035", "groom"], "983": ["n10565667", "scuba_diver"], "984": ["n11879895", "rapeseed"], "985": ["n11939491", "daisy"], "986": ["n12057211", "yellow_lady's_slipper"], "987": ["n12144580", "corn"], "988": ["n12267677", "acorn"], "989": ["n12620546", "hip"], "990": ["n12768682", "buckeye"], "991": ["n12985857", "coral_fungus"], "992": ["n12998815", "agaric"], "993": ["n13037406", "gyromitra"], "994": ["n13040303", "stinkhorn"], "995": ["n13044778", "earthstar"], "996": ["n13052670", "hen-of-the-woods"], "997": ["n13054560", "bolete"], "998": ["n13133613", "ear"], "999": ["n15075141", "toilet_tissue"]} -------------------------------------------------------------------------------- /notebook/.ipynb_checkpoints/dummy model for MPG-checkpoint.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "import pandas as pd\n", 10 | "import numpy as np\n", 11 | "from sklearn import pipeline,preprocessing,metrics,model_selection,ensemble\n", 12 | "from sklearn_pandas import DataFrameMapper" 13 | ] 14 | }, 15 | { 16 | "cell_type": "code", 17 | "execution_count": 2, 18 | "metadata": {}, 19 | "outputs": [], 20 | "source": [ 21 | "data=pd.read_csv('../mpg_data_example.csv')" 22 | ] 23 | }, 24 | { 25 | "cell_type": "code", 26 | "execution_count": 3, 27 | "metadata": {}, 28 | "outputs": [ 29 | { 30 | "data": { 31 | "text/html": [ 32 | "
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mpgcylindersdisplacementhorsepowerweightaccelerationmodel yearorigincar name
018.08307.0130.0350412.0701chevrolet chevelle malibu
115.08350.0165.0369311.5701buick skylark 320
218.08318.0150.0343611.0701plymouth satellite
316.08304.0150.0343312.0701amc rebel sst
417.08302.0140.0344910.5701ford torino
\n", 124 | "
" 125 | ], 126 | "text/plain": [ 127 | " mpg cylinders displacement horsepower weight acceleration \\\n", 128 | "0 18.0 8 307.0 130.0 3504 12.0 \n", 129 | "1 15.0 8 350.0 165.0 3693 11.5 \n", 130 | "2 18.0 8 318.0 150.0 3436 11.0 \n", 131 | "3 16.0 8 304.0 150.0 3433 12.0 \n", 132 | "4 17.0 8 302.0 140.0 3449 10.5 \n", 133 | "\n", 134 | " model year origin car name \n", 135 | "0 70 1 chevrolet chevelle malibu \n", 136 | "1 70 1 buick skylark 320 \n", 137 | "2 70 1 plymouth satellite \n", 138 | "3 70 1 amc rebel sst \n", 139 | "4 70 1 ford torino " 140 | ] 141 | }, 142 | "execution_count": 3, 143 | "metadata": {}, 144 | "output_type": "execute_result" 145 | } 146 | ], 147 | "source": [ 148 | "data.head()" 149 | ] 150 | }, 151 | { 152 | "cell_type": "code", 153 | "execution_count": 4, 154 | "metadata": {}, 155 | "outputs": [ 156 | { 157 | "data": { 158 | "text/plain": [ 159 | "mpg 0\n", 160 | "cylinders 0\n", 161 | "displacement 0\n", 162 | "horsepower 6\n", 163 | "weight 0\n", 164 | "acceleration 0\n", 165 | "model year 0\n", 166 | "origin 0\n", 167 | "car name 0\n", 168 | "dtype: int64" 169 | ] 170 | }, 171 | "execution_count": 4, 172 | "metadata": {}, 173 | "output_type": "execute_result" 174 | } 175 | ], 176 | "source": [ 177 | "data.isnull().sum()" 178 | ] 179 | }, 180 | { 181 | "cell_type": "code", 182 | "execution_count": 6, 183 | "metadata": {}, 184 | "outputs": [ 185 | { 186 | "name": "stderr", 187 | "output_type": "stream", 188 | "text": [ 189 | "c:\\users\\themachine\\.conda\\envs\\python36\\lib\\site-packages\\sklearn\\utils\\deprecation.py:58: DeprecationWarning: Class Imputer is deprecated; Imputer was deprecated in version 0.20 and will be removed in 0.22. Import impute.SimpleImputer from sklearn instead.\n", 190 | " warnings.warn(msg, category=DeprecationWarning)\n" 191 | ] 192 | } 193 | ], 194 | "source": [ 195 | "mapper = DataFrameMapper([\n", 196 | " (['cylinders','displacement','weight','acceleration','model year'], preprocessing.StandardScaler()),\n", 197 | " (['horsepower'],preprocessing.Imputer()),\n", 198 | " (['origin'], preprocessing.OneHotEncoder())\n", 199 | " ])" 200 | ] 201 | }, 202 | { 203 | "cell_type": "code", 204 | "execution_count": 7, 205 | "metadata": {}, 206 | "outputs": [], 207 | "source": [ 208 | "pipeline_obj = pipeline.Pipeline([\n", 209 | " ('mapper',mapper),\n", 210 | " (\"model\", ensemble.RandomForestRegressor())\n", 211 | "])" 212 | ] 213 | }, 214 | { 215 | "cell_type": "code", 216 | "execution_count": 8, 217 | "metadata": {}, 218 | "outputs": [ 219 | { 220 | "data": { 221 | "text/plain": [ 222 | "Index(['mpg', 'cylinders', 'displacement', 'horsepower', 'weight',\n", 223 | " 'acceleration', 'model year', 'origin', 'car name'],\n", 224 | " dtype='object')" 225 | ] 226 | }, 227 | "execution_count": 8, 228 | "metadata": {}, 229 | "output_type": "execute_result" 230 | } 231 | ], 232 | "source": [ 233 | "data.columns" 234 | ] 235 | }, 236 | { 237 | "cell_type": "code", 238 | "execution_count": 9, 239 | "metadata": {}, 240 | "outputs": [], 241 | "source": [ 242 | "X=['cylinders', 'displacement', 'horsepower', 'weight',\n", 243 | " 'acceleration', 'model year', 'origin']\n", 244 | "Y=['mpg']" 245 | ] 246 | }, 247 | { 248 | "cell_type": "code", 249 | "execution_count": 10, 250 | "metadata": {}, 251 | "outputs": [ 252 | { 253 | "name": "stderr", 254 | "output_type": "stream", 255 | "text": [ 256 | "c:\\users\\themachine\\.conda\\envs\\python36\\lib\\site-packages\\sklearn\\preprocessing\\_encoders.py:371: FutureWarning: The handling of integer data will change in version 0.22. Currently, the categories are determined based on the range [0, max(values)], while in the future they will be determined based on the unique values.\n", 257 | "If you want the future behaviour and silence this warning, you can specify \"categories='auto'\".\n", 258 | "In case you used a LabelEncoder before this OneHotEncoder to convert the categories to integers, then you can now use the OneHotEncoder directly.\n", 259 | " warnings.warn(msg, FutureWarning)\n", 260 | "c:\\users\\themachine\\.conda\\envs\\python36\\lib\\site-packages\\sklearn\\ensemble\\forest.py:246: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n", 261 | " \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n", 262 | "c:\\users\\themachine\\.conda\\envs\\python36\\lib\\site-packages\\sklearn\\pipeline.py:267: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n", 263 | " self._final_estimator.fit(Xt, y, **fit_params)\n" 264 | ] 265 | }, 266 | { 267 | "data": { 268 | "text/plain": [ 269 | "Pipeline(memory=None,\n", 270 | " steps=[('mapper', DataFrameMapper(default=False, df_out=False,\n", 271 | " features=[(['cylinders', 'displacement', 'weight', 'acceleration', 'model year'], StandardScaler(copy=True, with_mean=True, with_std=True)), (['horsepower'], Imputer(axis=0, copy=True, missing_values='NaN', strategy='mean', verbo...ators=10, n_jobs=None,\n", 272 | " oob_score=False, random_state=None, verbose=0, warm_start=False))])" 273 | ] 274 | }, 275 | "execution_count": 10, 276 | "metadata": {}, 277 | "output_type": "execute_result" 278 | } 279 | ], 280 | "source": [ 281 | "pipeline_obj.fit(data[X],data[Y])" 282 | ] 283 | }, 284 | { 285 | "cell_type": "code", 286 | "execution_count": 11, 287 | "metadata": {}, 288 | "outputs": [ 289 | { 290 | "data": { 291 | "text/plain": [ 292 | "array([16.9 , 14.7 , 17.2 , 16.3 , 16.6 , 14.9 , 14.1 , 13.8 , 13.6 ,\n", 293 | " 14.7 , 14.8 , 14.3 , 14.9 , 15.1 , 24. , 21.7 , 19.1 , 20.02,\n", 294 | " 27. , 26.45, 24.85, 24.1 , 24.8 , 24.7 , 20.4 , 10.9 , 11.8 ,\n", 295 | " 12. , 9.7 , 27. , 24.7 , 24.5 , 24.5 , 19.3 , 16.4 , 17.6 ,\n", 296 | " 18.7 , 18.3 , 13.8 , 13.5 , 14.1 , 14. , 12.1 , 13. , 12.8 ,\n", 297 | " 18. , 22.65, 18.9 , 18.1 , 22.4 , 27.2 , 30.1 , 29.6 , 31.7 ,\n", 298 | " 34. , 27.65, 26.2 , 23.6 , 25.2 , 22.7 , 21. , 21.2 , 13.2 ,\n", 299 | " 13.5 , 14.7 , 14.2 , 15.9 , 11.5 , 12.7 , 12.5 , 13.1 , 18.9 ,\n", 300 | " 14.8 , 13.4 , 13.7 , 14.1 , 18.79, 21.9 , 20.8 , 26.15, 22.25,\n", 301 | " 25.1 , 22.7 , 26.8 , 26.3 , 13.3 , 14.5 , 13.2 , 14.15, 14.4 ,\n", 302 | " 11.6 , 13. , 13.4 , 14. , 12.1 , 11.9 , 13.2 , 18. , 16.7 ,\n", 303 | " 19. , 18.9 , 22.4 , 26.3 , 11.9 , 12.3 , 12.7 , 12.3 , 19.1 ,\n", 304 | " 19.9 , 22.15, 23.9 , 21.6 , 20.1 , 21.1 , 25.5 , 14.2 , 15. ,\n", 305 | " 28.1 , 24.8 , 21.85, 19.65, 15.2 , 23.6 , 20.1 , 12.5 , 20.1 ,\n", 306 | " 20. , 19.1 , 16.4 , 31.1 , 24.7 , 31.2 , 25.15, 16.35, 15.6 ,\n", 307 | " 17.8 , 15.2 , 13.3 , 13.9 , 14.4 , 14.25, 28.3 , 27.05, 25.9 ,\n", 308 | " 31.4 , 31.9 , 27.4 , 25.2 , 26.15, 24.3 , 25.6 , 30.65, 19.25,\n", 309 | " 17.8 , 15.3 , 17.55, 15.15, 14.9 , 15. , 14.75, 16.6 , 15.55,\n", 310 | " 15.1 , 17.2 , 20.5 , 19.5 , 15.75, 28.8 , 24.45, 19.4 , 23.2 ,\n", 311 | " 24.55, 26.25, 24.25, 19.48, 29. , 19.24, 23.95, 22.7 , 21.86,\n", 312 | " 24.55, 32.1 , 26.9 , 25.99, 25. , 25.9 , 26.9 , 16.94, 15.6 ,\n", 313 | " 16.03, 15.4 , 21.75, 20.35, 23.4 , 21.24, 28.4 , 25.55, 29. ,\n", 314 | " 32.4 , 19.16, 18.46, 18.46, 18.74, 30.05, 31.95, 27.95, 25.9 ,\n", 315 | " 20.36, 13. , 19.6 , 19.3 , 17.42, 16.35, 13.95, 13.97, 13.1 ,\n", 316 | " 31.35, 29.2 , 34.6 , 26.35, 33.59, 14.8 , 17.25, 15.35, 15.57,\n", 317 | " 18.23, 19.8 , 19.01, 18.34, 15.85, 15.6 , 15.8 , 15.84, 29.49,\n", 318 | " 25.13, 25.35, 24.46, 30.53, 32.85, 31.19, 30.2 , 22.04, 22.45,\n", 319 | " 20.3 , 38.53, 35.58, 33.9 , 37.77, 36.04, 19.85, 19.4 , 19.64,\n", 320 | " 18.97, 20.12, 20.5 , 24.88, 19.89, 19.68, 20.37, 20.44, 18.49,\n", 321 | " 17.99, 19.2 , 18.22, 18.63, 17.16, 31.23, 26.26, 26.09, 29.34,\n", 322 | " 23.07, 23.01, 23.04, 24.93, 20.47, 19. , 20.97, 17.87, 31.8 ,\n", 323 | " 31.71, 21.46, 21.97, 23.63, 20.63, 20.39, 17.1 , 18.34, 18.01,\n", 324 | " 17.46, 16.68, 16.65, 18.99, 18.57, 35.93, 34.49, 35.46, 27.17,\n", 325 | " 25.98, 21.5 , 28.65, 22.32, 35.07, 35.32, 32.7 , 36.86, 27.85,\n", 326 | " 27.98, 25.9 , 31.04, 39.22, 38.1 , 32.93, 37.27, 27.68, 26.09,\n", 327 | " 25.37, 20.33, 35.02, 30.46, 31.2 , 34.09, 32.58, 44.73, 27.06,\n", 328 | " 41.24, 41.44, 39.56, 35.83, 31.01, 38.04, 38.33, 37.21, 33.17,\n", 329 | " 27.6 , 26.36, 33.59, 23.63, 32.93, 28.24, 26.74, 27.08, 23.96,\n", 330 | " 30.01, 38.02, 36.98, 36.45, 34.86, 36.31, 36.93, 34.02, 35.05,\n", 331 | " 34.68, 31.28, 33.3 , 35.12, 34.39, 33.08, 32.61, 31.21, 27.33,\n", 332 | " 30.9 , 26.16, 26.73, 20.47, 25.16, 20.39, 20.94, 28.9 , 28.5 ,\n", 333 | " 33.12, 30.4 , 30.35, 27.1 , 24.9 , 25.59, 34.66, 35.71, 32.31,\n", 334 | " 37.6 , 35.68, 36.35, 35.31, 34. , 35.32, 32.72, 35.82, 24.57,\n", 335 | " 32.29, 26.93, 25.5 , 30.44, 33.77, 26.67, 26.66, 40.84, 32.57,\n", 336 | " 28.24, 30.64])" 337 | ] 338 | }, 339 | "execution_count": 11, 340 | "metadata": {}, 341 | "output_type": "execute_result" 342 | } 343 | ], 344 | "source": [ 345 | "pipeline_obj.predict(data[X])" 346 | ] 347 | }, 348 | { 349 | "cell_type": "code", 350 | "execution_count": 12, 351 | "metadata": {}, 352 | "outputs": [], 353 | "source": [ 354 | "from sklearn.externals import joblib" 355 | ] 356 | }, 357 | { 358 | "cell_type": "code", 359 | "execution_count": 13, 360 | "metadata": {}, 361 | "outputs": [ 362 | { 363 | "data": { 364 | "text/plain": [ 365 | "['RFModelforMPG.pkl']" 366 | ] 367 | }, 368 | "execution_count": 13, 369 | "metadata": {}, 370 | "output_type": "execute_result" 371 | } 372 | ], 373 | "source": [ 374 | "joblib.dump(pipeline_obj,'RFModelforMPG.pkl')" 375 | ] 376 | }, 377 | { 378 | "cell_type": "code", 379 | "execution_count": 14, 380 | "metadata": {}, 381 | "outputs": [], 382 | "source": [ 383 | "modelReload=joblib.load('RFModelforMPG.pkl')" 384 | ] 385 | }, 386 | { 387 | "cell_type": "code", 388 | "execution_count": 15, 389 | "metadata": {}, 390 | "outputs": [ 391 | { 392 | "data": { 393 | "text/plain": [ 394 | "array([16.9 , 14.7 , 17.2 , 16.3 , 16.6 , 14.9 , 14.1 , 13.8 , 13.6 ,\n", 395 | " 14.7 , 14.8 , 14.3 , 14.9 , 15.1 , 24. , 21.7 , 19.1 , 20.02,\n", 396 | " 27. , 26.45, 24.85, 24.1 , 24.8 , 24.7 , 20.4 , 10.9 , 11.8 ,\n", 397 | " 12. , 9.7 , 27. , 24.7 , 24.5 , 24.5 , 19.3 , 16.4 , 17.6 ,\n", 398 | " 18.7 , 18.3 , 13.8 , 13.5 , 14.1 , 14. , 12.1 , 13. , 12.8 ,\n", 399 | " 18. , 22.65, 18.9 , 18.1 , 22.4 , 27.2 , 30.1 , 29.6 , 31.7 ,\n", 400 | " 34. , 27.65, 26.2 , 23.6 , 25.2 , 22.7 , 21. , 21.2 , 13.2 ,\n", 401 | " 13.5 , 14.7 , 14.2 , 15.9 , 11.5 , 12.7 , 12.5 , 13.1 , 18.9 ,\n", 402 | " 14.8 , 13.4 , 13.7 , 14.1 , 18.79, 21.9 , 20.8 , 26.15, 22.25,\n", 403 | " 25.1 , 22.7 , 26.8 , 26.3 , 13.3 , 14.5 , 13.2 , 14.15, 14.4 ,\n", 404 | " 11.6 , 13. , 13.4 , 14. , 12.1 , 11.9 , 13.2 , 18. , 16.7 ,\n", 405 | " 19. , 18.9 , 22.4 , 26.3 , 11.9 , 12.3 , 12.7 , 12.3 , 19.1 ,\n", 406 | " 19.9 , 22.15, 23.9 , 21.6 , 20.1 , 21.1 , 25.5 , 14.2 , 15. ,\n", 407 | " 28.1 , 24.8 , 21.85, 19.65, 15.2 , 23.6 , 20.1 , 12.5 , 20.1 ,\n", 408 | " 20. , 19.1 , 16.4 , 31.1 , 24.7 , 31.2 , 25.15, 16.35, 15.6 ,\n", 409 | " 17.8 , 15.2 , 13.3 , 13.9 , 14.4 , 14.25, 28.3 , 27.05, 25.9 ,\n", 410 | " 31.4 , 31.9 , 27.4 , 25.2 , 26.15, 24.3 , 25.6 , 30.65, 19.25,\n", 411 | " 17.8 , 15.3 , 17.55, 15.15, 14.9 , 15. , 14.75, 16.6 , 15.55,\n", 412 | " 15.1 , 17.2 , 20.5 , 19.5 , 15.75, 28.8 , 24.45, 19.4 , 23.2 ,\n", 413 | " 24.55, 26.25, 24.25, 19.48, 29. , 19.24, 23.95, 22.7 , 21.86,\n", 414 | " 24.55, 32.1 , 26.9 , 25.99, 25. , 25.9 , 26.9 , 16.94, 15.6 ,\n", 415 | " 16.03, 15.4 , 21.75, 20.35, 23.4 , 21.24, 28.4 , 25.55, 29. ,\n", 416 | " 32.4 , 19.16, 18.46, 18.46, 18.74, 30.05, 31.95, 27.95, 25.9 ,\n", 417 | " 20.36, 13. , 19.6 , 19.3 , 17.42, 16.35, 13.95, 13.97, 13.1 ,\n", 418 | " 31.35, 29.2 , 34.6 , 26.35, 33.59, 14.8 , 17.25, 15.35, 15.57,\n", 419 | " 18.23, 19.8 , 19.01, 18.34, 15.85, 15.6 , 15.8 , 15.84, 29.49,\n", 420 | " 25.13, 25.35, 24.46, 30.53, 32.85, 31.19, 30.2 , 22.04, 22.45,\n", 421 | " 20.3 , 38.53, 35.58, 33.9 , 37.77, 36.04, 19.85, 19.4 , 19.64,\n", 422 | " 18.97, 20.12, 20.5 , 24.88, 19.89, 19.68, 20.37, 20.44, 18.49,\n", 423 | " 17.99, 19.2 , 18.22, 18.63, 17.16, 31.23, 26.26, 26.09, 29.34,\n", 424 | " 23.07, 23.01, 23.04, 24.93, 20.47, 19. , 20.97, 17.87, 31.8 ,\n", 425 | " 31.71, 21.46, 21.97, 23.63, 20.63, 20.39, 17.1 , 18.34, 18.01,\n", 426 | " 17.46, 16.68, 16.65, 18.99, 18.57, 35.93, 34.49, 35.46, 27.17,\n", 427 | " 25.98, 21.5 , 28.65, 22.32, 35.07, 35.32, 32.7 , 36.86, 27.85,\n", 428 | " 27.98, 25.9 , 31.04, 39.22, 38.1 , 32.93, 37.27, 27.68, 26.09,\n", 429 | " 25.37, 20.33, 35.02, 30.46, 31.2 , 34.09, 32.58, 44.73, 27.06,\n", 430 | " 41.24, 41.44, 39.56, 35.83, 31.01, 38.04, 38.33, 37.21, 33.17,\n", 431 | " 27.6 , 26.36, 33.59, 23.63, 32.93, 28.24, 26.74, 27.08, 23.96,\n", 432 | " 30.01, 38.02, 36.98, 36.45, 34.86, 36.31, 36.93, 34.02, 35.05,\n", 433 | " 34.68, 31.28, 33.3 , 35.12, 34.39, 33.08, 32.61, 31.21, 27.33,\n", 434 | " 30.9 , 26.16, 26.73, 20.47, 25.16, 20.39, 20.94, 28.9 , 28.5 ,\n", 435 | " 33.12, 30.4 , 30.35, 27.1 , 24.9 , 25.59, 34.66, 35.71, 32.31,\n", 436 | " 37.6 , 35.68, 36.35, 35.31, 34. , 35.32, 32.72, 35.82, 24.57,\n", 437 | " 32.29, 26.93, 25.5 , 30.44, 33.77, 26.67, 26.66, 40.84, 32.57,\n", 438 | " 28.24, 30.64])" 439 | ] 440 | }, 441 | "execution_count": 15, 442 | "metadata": {}, 443 | "output_type": "execute_result" 444 | } 445 | ], 446 | "source": [ 447 | "modelReload.predict(data[X])" 448 | ] 449 | }, 450 | { 451 | "cell_type": "code", 452 | "execution_count": null, 453 | "metadata": {}, 454 | "outputs": [], 455 | "source": [ 456 | "temp={}\n", 457 | "temp['cylinders']=1\n", 458 | "temp['displacement']=2\n", 459 | "temp['horsepower']=3\n", 460 | "temp['weight']=4\n", 461 | "temp['acceleration']=5\n", 462 | "temp['model year']=6\n", 463 | "temp['origin']=1" 464 | ] 465 | }, 466 | { 467 | "cell_type": "code", 468 | "execution_count": null, 469 | "metadata": {}, 470 | "outputs": [], 471 | "source": [ 472 | "testDtaa=pd.DataFrame({'x':temp}).transpose()" 473 | ] 474 | }, 475 | { 476 | "cell_type": "code", 477 | "execution_count": null, 478 | "metadata": {}, 479 | "outputs": [], 480 | "source": [ 481 | "modelReload.predict(testDtaa)[0]" 482 | ] 483 | }, 484 | { 485 | "cell_type": "code", 486 | "execution_count": null, 487 | "metadata": {}, 488 | "outputs": [], 489 | "source": [] 490 | } 491 | ], 492 | "metadata": { 493 | "kernelspec": { 494 | "display_name": "Python 3", 495 | "language": "python", 496 | "name": "python3" 497 | }, 498 | "language_info": { 499 | "codemirror_mode": { 500 | "name": "ipython", 501 | "version": 3 502 | }, 503 | "file_extension": ".py", 504 | "mimetype": "text/x-python", 505 | "name": "python", 506 | "nbconvert_exporter": "python", 507 | "pygments_lexer": "ipython3", 508 | "version": "3.6.9" 509 | } 510 | }, 511 | "nbformat": 4, 512 | "nbformat_minor": 2 513 | } 514 | -------------------------------------------------------------------------------- /notebook/.ipynb_checkpoints/mobilenet Model-checkpoint.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "https://keras.io/applications/#mobilenet\n", 8 | "\n", 9 | "https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a#file-imagenet1000_clsidx_to_labels-txt" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 1, 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "name": "stderr", 19 | "output_type": "stream", 20 | "text": [ 21 | "Using TensorFlow backend.\n", 22 | "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\envs\\py36\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:526: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", 23 | " _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n", 24 | "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\envs\\py36\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:527: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", 25 | " _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n", 26 | "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\envs\\py36\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:528: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", 27 | " _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n", 28 | "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\envs\\py36\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:529: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", 29 | " _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n", 30 | "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\envs\\py36\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:530: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", 31 | " _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n", 32 | "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\envs\\py36\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:535: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n", 33 | " np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n" 34 | ] 35 | } 36 | ], 37 | "source": [ 38 | "from keras.applications import mobilenet" 39 | ] 40 | }, 41 | { 42 | "cell_type": "code", 43 | "execution_count": 2, 44 | "metadata": {}, 45 | "outputs": [ 46 | { 47 | "name": "stdout", 48 | "output_type": "stream", 49 | "text": [ 50 | "WARNING:tensorflow:From C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\envs\\py36\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n", 51 | "Instructions for updating:\n", 52 | "Colocations handled automatically by placer.\n", 53 | "WARNING:tensorflow:From C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\envs\\py36\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n", 54 | "Instructions for updating:\n", 55 | "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n" 56 | ] 57 | } 58 | ], 59 | "source": [ 60 | "model=mobilenet.MobileNet(include_top=True,weights='imagenet')" 61 | ] 62 | }, 63 | { 64 | "cell_type": "code", 65 | "execution_count": 3, 66 | "metadata": { 67 | "scrolled": true 68 | }, 69 | "outputs": [ 70 | { 71 | "data": { 72 | "text/plain": [ 73 | "[,\n", 74 | " ,\n", 75 | " ,\n", 76 | " ,\n", 77 | " ,\n", 78 | " ,\n", 79 | " ,\n", 80 | " ,\n", 81 | " ,\n", 82 | " ,\n", 83 | " ,\n", 84 | " ,\n", 85 | " ,\n", 86 | " ,\n", 87 | " ,\n", 88 | " ,\n", 89 | " ,\n", 90 | " ,\n", 91 | " ,\n", 92 | " ,\n", 93 | " ,\n", 94 | " ,\n", 95 | " ,\n", 96 | " ,\n", 97 | " ,\n", 98 | " ,\n", 99 | " ,\n", 100 | " ,\n", 101 | " ,\n", 102 | " ,\n", 103 | " ,\n", 104 | " ,\n", 105 | " ,\n", 106 | " ,\n", 107 | " ,\n", 108 | " ,\n", 109 | " ,\n", 110 | " ,\n", 111 | " ,\n", 112 | " ,\n", 113 | " ,\n", 114 | " ,\n", 115 | " ,\n", 116 | " ,\n", 117 | " ,\n", 118 | " ,\n", 119 | " ,\n", 120 | " ,\n", 121 | " ,\n", 122 | " ,\n", 123 | " ,\n", 124 | " ,\n", 125 | " ,\n", 126 | " ,\n", 127 | " ,\n", 128 | " ,\n", 129 | " ,\n", 130 | " ,\n", 131 | " ,\n", 132 | " ,\n", 133 | " ,\n", 134 | " ,\n", 135 | " ,\n", 136 | " ,\n", 137 | " ,\n", 138 | " ,\n", 139 | " ,\n", 140 | " ,\n", 141 | " ,\n", 142 | " ,\n", 143 | " ,\n", 144 | " ,\n", 145 | " ,\n", 146 | " ,\n", 147 | " ,\n", 148 | " ,\n", 149 | " ,\n", 150 | " ,\n", 151 | " ,\n", 152 | " ,\n", 153 | " ,\n", 154 | " ,\n", 155 | " ,\n", 156 | " ,\n", 157 | " ,\n", 158 | " ,\n", 159 | " ,\n", 160 | " ,\n", 161 | " ,\n", 162 | " ,\n", 163 | " ,\n", 164 | " ,\n", 165 | " ]" 166 | ] 167 | }, 168 | "execution_count": 3, 169 | "metadata": {}, 170 | "output_type": "execute_result" 171 | } 172 | ], 173 | "source": [ 174 | "model.layers" 175 | ] 176 | }, 177 | { 178 | "cell_type": "code", 179 | "execution_count": 4, 180 | "metadata": {}, 181 | "outputs": [], 182 | "source": [ 183 | "from keras.preprocessing import image\n", 184 | "import tensorflow as tf\n", 185 | "from tensorflow import Graph, Session" 186 | ] 187 | }, 188 | { 189 | "cell_type": "code", 190 | "execution_count": 5, 191 | "metadata": {}, 192 | "outputs": [], 193 | "source": [ 194 | "img_height, img_width=224,224" 195 | ] 196 | }, 197 | { 198 | "cell_type": "code", 199 | "execution_count": 6, 200 | "metadata": {}, 201 | "outputs": [], 202 | "source": [ 203 | "with open('imagenet_classes.json','r') as f:\n", 204 | " labelInfo=f.read()" 205 | ] 206 | }, 207 | { 208 | "cell_type": "code", 209 | "execution_count": 7, 210 | "metadata": {}, 211 | "outputs": [], 212 | "source": [ 213 | "import json" 214 | ] 215 | }, 216 | { 217 | "cell_type": "code", 218 | "execution_count": 8, 219 | "metadata": {}, 220 | "outputs": [], 221 | "source": [ 222 | "labelInfo=json.loads(labelInfo)" 223 | ] 224 | }, 225 | { 226 | "cell_type": "code", 227 | "execution_count": 9, 228 | "metadata": {}, 229 | "outputs": [], 230 | "source": [ 231 | "testimage='sumatran-tiger-wz-gsmp-m.jpg'" 232 | ] 233 | }, 234 | { 235 | "cell_type": "code", 236 | "execution_count": 10, 237 | "metadata": {}, 238 | "outputs": [], 239 | "source": [ 240 | "img = image.load_img(testimage, target_size=(img_height, img_width))\n", 241 | "x = image.img_to_array(img)\n", 242 | "x=x/255\n", 243 | "x=x.reshape(1,img_height, img_width,3)\n", 244 | "model_graph = modeScope['modelObj']['model_graph']\n", 245 | "tf_session = modeScope['modelObj']['tf_session']\n", 246 | "with model_graph.as_default():\n", 247 | " with tf_session.as_default():\n", 248 | " modelToUse=modeScope['modelObj']['recoModelObj'].model\n", 249 | " predi=modelToUse.predict(x)" 250 | ] 251 | }, 252 | { 253 | "cell_type": "code", 254 | "execution_count": 11, 255 | "metadata": {}, 256 | "outputs": [ 257 | { 258 | "data": { 259 | "text/plain": [ 260 | "292" 261 | ] 262 | }, 263 | "execution_count": 11, 264 | "metadata": {}, 265 | "output_type": "execute_result" 266 | } 267 | ], 268 | "source": [ 269 | "import numpy as np\n", 270 | "np.argmax(predi[0])" 271 | ] 272 | }, 273 | { 274 | "cell_type": "code", 275 | "execution_count": 12, 276 | "metadata": {}, 277 | "outputs": [ 278 | { 279 | "data": { 280 | "text/plain": [ 281 | "['n02129604', 'tiger']" 282 | ] 283 | }, 284 | "execution_count": 12, 285 | "metadata": {}, 286 | "output_type": "execute_result" 287 | } 288 | ], 289 | "source": [ 290 | "labelInfo['292']" 291 | ] 292 | }, 293 | { 294 | "cell_type": "code", 295 | "execution_count": 13, 296 | "metadata": {}, 297 | "outputs": [], 298 | "source": [ 299 | "testimage='bird-article-s.png'\n", 300 | "img = image.load_img(testimage, target_size=(img_height, img_width))\n", 301 | "x = image.img_to_array(img)\n", 302 | "x=x/255\n", 303 | "x=x.reshape(1,img_height, img_width,3)\n", 304 | "# model_graph = tf.\n", 305 | "# tf_session = modeScope['modelObj']['tf_session']\n", 306 | "# with model_graph.as_default():\n", 307 | "# with tf_session.as_default():\n", 308 | "# modelToUse=modeScope['modelObj']['recoModelObj'].model\n", 309 | "predi=model.predict(x)" 310 | ] 311 | }, 312 | { 313 | "cell_type": "code", 314 | "execution_count": 14, 315 | "metadata": {}, 316 | "outputs": [ 317 | { 318 | "data": { 319 | "text/plain": [ 320 | "11" 321 | ] 322 | }, 323 | "execution_count": 14, 324 | "metadata": {}, 325 | "output_type": "execute_result" 326 | } 327 | ], 328 | "source": [ 329 | "import numpy as np\n", 330 | "np.argmax(predi[0])" 331 | ] 332 | }, 333 | { 334 | "cell_type": "code", 335 | "execution_count": 15, 336 | "metadata": {}, 337 | "outputs": [ 338 | { 339 | "data": { 340 | "text/plain": [ 341 | "['n01531178', 'goldfinch']" 342 | ] 343 | }, 344 | "execution_count": 15, 345 | "metadata": {}, 346 | "output_type": "execute_result" 347 | } 348 | ], 349 | "source": [ 350 | "labelInfo['11']" 351 | ] 352 | }, 353 | { 354 | "cell_type": "code", 355 | "execution_count": 16, 356 | "metadata": {}, 357 | "outputs": [], 358 | "source": [ 359 | "model.save('MobileNetModelImagenet.h5')" 360 | ] 361 | }, 362 | { 363 | "cell_type": "code", 364 | "execution_count": 18, 365 | "metadata": {}, 366 | "outputs": [], 367 | "source": [ 368 | "import keras" 369 | ] 370 | }, 371 | { 372 | "cell_type": "code", 373 | "execution_count": 19, 374 | "metadata": {}, 375 | "outputs": [], 376 | "source": [ 377 | "from keras.models import load_model" 378 | ] 379 | }, 380 | { 381 | "cell_type": "code", 382 | "execution_count": 20, 383 | "metadata": {}, 384 | "outputs": [ 385 | { 386 | "name": "stderr", 387 | "output_type": "stream", 388 | "text": [ 389 | "C:\\Users\\swsh\\AppData\\Local\\Continuum\\anaconda3\\envs\\py36\\lib\\site-packages\\keras\\engine\\saving.py:292: UserWarning: No training configuration found in save file: the model was *not* compiled. Compile it manually.\n", 390 | " warnings.warn('No training configuration found in save file: '\n" 391 | ] 392 | }, 393 | { 394 | "data": { 395 | "text/plain": [ 396 | "" 397 | ] 398 | }, 399 | "execution_count": 20, 400 | "metadata": {}, 401 | "output_type": "execute_result" 402 | } 403 | ], 404 | "source": [ 405 | "load_model('MobileNetModelImagenet.h5')" 406 | ] 407 | }, 408 | { 409 | "cell_type": "code", 410 | "execution_count": null, 411 | "metadata": {}, 412 | "outputs": [], 413 | "source": [] 414 | } 415 | ], 416 | "metadata": { 417 | "kernelspec": { 418 | "display_name": "Python 3", 419 | "language": "python", 420 | "name": "python3" 421 | }, 422 | "language_info": { 423 | "codemirror_mode": { 424 | "name": "ipython", 425 | "version": 3 426 | }, 427 | "file_extension": ".py", 428 | "mimetype": "text/x-python", 429 | "name": "python", 430 | "nbconvert_exporter": "python", 431 | "pygments_lexer": "ipython3", 432 | "version": "3.6.8" 433 | } 434 | }, 435 | "nbformat": 4, 436 | "nbformat_minor": 2 437 | } 438 | -------------------------------------------------------------------------------- /notebook/.ipynb_checkpoints/mongodb connection-checkpoint.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 2, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "name": "stdout", 10 | "output_type": "stream", 11 | "text": [ 12 | "Collecting pymongo\n", 13 | " Downloading https://files.pythonhosted.org/packages/40/bc/015c54f2a26cba27763a0ce6a11d0ea6c647967d96ac6ae19e02c6598094/pymongo-3.10.1-cp36-cp36m-win_amd64.whl (354kB)\n", 14 | "Installing collected packages: pymongo\n", 15 | "Successfully installed pymongo-3.10.1\n" 16 | ] 17 | } 18 | ], 19 | "source": [ 20 | "!pip install pymongo" 21 | ] 22 | }, 23 | { 24 | "cell_type": "code", 25 | "execution_count": 3, 26 | "metadata": {}, 27 | "outputs": [], 28 | "source": [ 29 | "import pymongo" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": 1, 35 | "metadata": {}, 36 | "outputs": [], 37 | "source": [ 38 | "from pymongo import MongoClient\n", 39 | "# client = MongoClient()" 40 | ] 41 | }, 42 | { 43 | "cell_type": "code", 44 | "execution_count": 2, 45 | "metadata": {}, 46 | "outputs": [], 47 | "source": [ 48 | "client = MongoClient('localhost', 27017)" 49 | ] 50 | }, 51 | { 52 | "cell_type": "code", 53 | "execution_count": 3, 54 | "metadata": {}, 55 | "outputs": [ 56 | { 57 | "name": "stderr", 58 | "output_type": "stream", 59 | "text": [ 60 | "c:\\users\\themachine\\.conda\\envs\\python36\\lib\\site-packages\\ipykernel_launcher.py:1: DeprecationWarning: database_names is deprecated. Use list_database_names instead.\n", 61 | " \"\"\"Entry point for launching an IPython kernel.\n" 62 | ] 63 | }, 64 | { 65 | "data": { 66 | "text/plain": [ 67 | "['admin', 'config', 'local', 'mpgDataBase']" 68 | ] 69 | }, 70 | "execution_count": 3, 71 | "metadata": {}, 72 | "output_type": "execute_result" 73 | } 74 | ], 75 | "source": [ 76 | "client.database_names()" 77 | ] 78 | }, 79 | { 80 | "cell_type": "code", 81 | "execution_count": 4, 82 | "metadata": {}, 83 | "outputs": [], 84 | "source": [ 85 | "db = client['mpgDataBase']" 86 | ] 87 | }, 88 | { 89 | "cell_type": "code", 90 | "execution_count": 5, 91 | "metadata": {}, 92 | "outputs": [], 93 | "source": [ 94 | "collectionD = db['mpgTable']" 95 | ] 96 | }, 97 | { 98 | "cell_type": "code", 99 | "execution_count": 9, 100 | "metadata": {}, 101 | "outputs": [ 102 | { 103 | "data": { 104 | "text/plain": [ 105 | "{'cylinders': 1,\n", 106 | " 'displacement': 2,\n", 107 | " 'horsepower': 3,\n", 108 | " 'weight': 4,\n", 109 | " 'acceleration': 5,\n", 110 | " 'model year': 6,\n", 111 | " 'origin': 1}" 112 | ] 113 | }, 114 | "execution_count": 9, 115 | "metadata": {}, 116 | "output_type": "execute_result" 117 | } 118 | ], 119 | "source": [ 120 | "temp={}\n", 121 | "temp['cylinders']=1\n", 122 | "temp['displacement']=2\n", 123 | "temp['horsepower']=3\n", 124 | "temp['weight']=4\n", 125 | "temp['acceleration']=5\n", 126 | "temp['model year']=6\n", 127 | "temp['origin']=1\n", 128 | "temp" 129 | ] 130 | }, 131 | { 132 | "cell_type": "code", 133 | "execution_count": 10, 134 | "metadata": {}, 135 | "outputs": [], 136 | "source": [ 137 | "pp=collectionD.insert_one(temp)" 138 | ] 139 | }, 140 | { 141 | "cell_type": "code", 142 | "execution_count": 11, 143 | "metadata": {}, 144 | "outputs": [ 145 | { 146 | "data": { 147 | "text/plain": [ 148 | "True" 149 | ] 150 | }, 151 | "execution_count": 11, 152 | "metadata": {}, 153 | "output_type": "execute_result" 154 | } 155 | ], 156 | "source": [ 157 | "pp.acknowledged" 158 | ] 159 | }, 160 | { 161 | "cell_type": "code", 162 | "execution_count": 12, 163 | "metadata": {}, 164 | "outputs": [ 165 | { 166 | "data": { 167 | "text/plain": [ 168 | "ObjectId('5e5cd3680c2fe68649203981')" 169 | ] 170 | }, 171 | "execution_count": 12, 172 | "metadata": {}, 173 | "output_type": "execute_result" 174 | } 175 | ], 176 | "source": [ 177 | "pp.inserted_id" 178 | ] 179 | }, 180 | { 181 | "cell_type": "code", 182 | "execution_count": 13, 183 | "metadata": {}, 184 | "outputs": [ 185 | { 186 | "data": { 187 | "text/plain": [ 188 | "['mpgTable']" 189 | ] 190 | }, 191 | "execution_count": 13, 192 | "metadata": {}, 193 | "output_type": "execute_result" 194 | } 195 | ], 196 | "source": [ 197 | "db.list_collection_names()" 198 | ] 199 | }, 200 | { 201 | "cell_type": "code", 202 | "execution_count": 15, 203 | "metadata": {}, 204 | "outputs": [ 205 | { 206 | "data": { 207 | "text/plain": [ 208 | "{'_id': ObjectId('5e5cd3680c2fe68649203981'),\n", 209 | " 'cylinders': 1,\n", 210 | " 'displacement': 2,\n", 211 | " 'horsepower': 3,\n", 212 | " 'weight': 4,\n", 213 | " 'acceleration': 5,\n", 214 | " 'model year': 6,\n", 215 | " 'origin': 1}" 216 | ] 217 | }, 218 | "execution_count": 15, 219 | "metadata": {}, 220 | "output_type": "execute_result" 221 | } 222 | ], 223 | "source": [ 224 | "collectionD.find_one()" 225 | ] 226 | }, 227 | { 228 | "cell_type": "code", 229 | "execution_count": 16, 230 | "metadata": {}, 231 | "outputs": [ 232 | { 233 | "name": "stdout", 234 | "output_type": "stream", 235 | "text": [ 236 | "{'_id': ObjectId('5e5cd3680c2fe68649203981'), 'cylinders': 1, 'displacement': 2, 'horsepower': 3, 'weight': 4, 'acceleration': 5, 'model year': 6, 'origin': 1}\n" 237 | ] 238 | } 239 | ], 240 | "source": [ 241 | "for i in collectionD.find():\n", 242 | " print (i)" 243 | ] 244 | }, 245 | { 246 | "cell_type": "code", 247 | "execution_count": 17, 248 | "metadata": {}, 249 | "outputs": [ 250 | { 251 | "name": "stderr", 252 | "output_type": "stream", 253 | "text": [ 254 | "c:\\users\\themachine\\.conda\\envs\\python36\\lib\\site-packages\\ipykernel_launcher.py:1: DeprecationWarning: count is deprecated. Use Collection.count_documents instead.\n", 255 | " \"\"\"Entry point for launching an IPython kernel.\n" 256 | ] 257 | }, 258 | { 259 | "data": { 260 | "text/plain": [ 261 | "1" 262 | ] 263 | }, 264 | "execution_count": 17, 265 | "metadata": {}, 266 | "output_type": "execute_result" 267 | } 268 | ], 269 | "source": [ 270 | "collectionD.find().count()" 271 | ] 272 | }, 273 | { 274 | "cell_type": "code", 275 | "execution_count": 6, 276 | "metadata": {}, 277 | "outputs": [], 278 | "source": [ 279 | "import pandas as pd" 280 | ] 281 | }, 282 | { 283 | "cell_type": "code", 284 | "execution_count": 7, 285 | "metadata": {}, 286 | "outputs": [], 287 | "source": [ 288 | "data=pd.read_csv('../mpg_data_example.csv')" 289 | ] 290 | }, 291 | { 292 | "cell_type": "code", 293 | "execution_count": 8, 294 | "metadata": {}, 295 | "outputs": [ 296 | { 297 | "name": "stderr", 298 | "output_type": "stream", 299 | "text": [ 300 | "c:\\users\\themachine\\.conda\\envs\\python36\\lib\\site-packages\\ipykernel_launcher.py:2: FutureWarning: \n", 301 | ".ix is deprecated. Please use\n", 302 | ".loc for label based indexing or\n", 303 | ".iloc for positional indexing\n", 304 | "\n", 305 | "See the documentation here:\n", 306 | "http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#ix-indexer-is-deprecated\n", 307 | " \n" 308 | ] 309 | } 310 | ], 311 | "source": [ 312 | "for i in range(10,100):\n", 313 | " tempData=dict(data.ix[i])\n", 314 | " for j in tempData:\n", 315 | " try:\n", 316 | " tempData[j]=float(tempData[j])\n", 317 | " except:\n", 318 | " pass\n", 319 | " collectionD.insert_one(tempData)" 320 | ] 321 | }, 322 | { 323 | "cell_type": "code", 324 | "execution_count": 9, 325 | "metadata": {}, 326 | "outputs": [ 327 | { 328 | "name": "stderr", 329 | "output_type": "stream", 330 | "text": [ 331 | "c:\\users\\themachine\\.conda\\envs\\python36\\lib\\site-packages\\ipykernel_launcher.py:1: DeprecationWarning: count is deprecated. Use Collection.count_documents instead.\n", 332 | " \"\"\"Entry point for launching an IPython kernel.\n" 333 | ] 334 | }, 335 | { 336 | "data": { 337 | "text/plain": [ 338 | "91" 339 | ] 340 | }, 341 | "execution_count": 9, 342 | "metadata": {}, 343 | "output_type": "execute_result" 344 | } 345 | ], 346 | "source": [ 347 | "collectionD.find().count()" 348 | ] 349 | }, 350 | { 351 | "cell_type": "code", 352 | "execution_count": null, 353 | "metadata": {}, 354 | "outputs": [], 355 | "source": [] 356 | } 357 | ], 358 | "metadata": { 359 | "kernelspec": { 360 | "display_name": "Python 3", 361 | "language": "python", 362 | "name": "python3" 363 | }, 364 | "language_info": { 365 | "codemirror_mode": { 366 | "name": "ipython", 367 | "version": 3 368 | }, 369 | "file_extension": ".py", 370 | "mimetype": "text/x-python", 371 | "name": "python", 372 | "nbconvert_exporter": "python", 373 | "pygments_lexer": "ipython3", 374 | "version": "3.6.9" 375 | } 376 | }, 377 | "nbformat": 4, 378 | "nbformat_minor": 2 379 | } 380 | -------------------------------------------------------------------------------- /notebook/bird-article-s.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/notebook/bird-article-s.png -------------------------------------------------------------------------------- /notebook/imagenet_classes.json: -------------------------------------------------------------------------------- 1 | {"0": ["n01440764", "tench"], "1": ["n01443537", "goldfish"], "2": ["n01484850", "great_white_shark"], "3": ["n01491361", "tiger_shark"], "4": ["n01494475", "hammerhead"], "5": ["n01496331", "electric_ray"], "6": ["n01498041", "stingray"], "7": ["n01514668", "cock"], "8": ["n01514859", "hen"], "9": ["n01518878", "ostrich"], "10": ["n01530575", "brambling"], "11": ["n01531178", "goldfinch"], "12": ["n01532829", "house_finch"], "13": ["n01534433", "junco"], "14": ["n01537544", "indigo_bunting"], "15": ["n01558993", "robin"], "16": ["n01560419", "bulbul"], "17": ["n01580077", "jay"], "18": ["n01582220", "magpie"], "19": ["n01592084", "chickadee"], "20": ["n01601694", "water_ouzel"], "21": ["n01608432", "kite"], "22": ["n01614925", "bald_eagle"], "23": ["n01616318", "vulture"], "24": ["n01622779", "great_grey_owl"], "25": ["n01629819", "European_fire_salamander"], "26": ["n01630670", "common_newt"], "27": ["n01631663", "eft"], "28": ["n01632458", "spotted_salamander"], "29": ["n01632777", "axolotl"], "30": ["n01641577", "bullfrog"], "31": ["n01644373", "tree_frog"], "32": ["n01644900", "tailed_frog"], "33": ["n01664065", "loggerhead"], "34": ["n01665541", "leatherback_turtle"], "35": ["n01667114", "mud_turtle"], "36": ["n01667778", "terrapin"], "37": ["n01669191", "box_turtle"], "38": ["n01675722", "banded_gecko"], "39": ["n01677366", "common_iguana"], "40": ["n01682714", "American_chameleon"], "41": ["n01685808", "whiptail"], "42": ["n01687978", "agama"], "43": ["n01688243", "frilled_lizard"], "44": ["n01689811", "alligator_lizard"], "45": ["n01692333", "Gila_monster"], "46": ["n01693334", "green_lizard"], "47": ["n01694178", "African_chameleon"], "48": ["n01695060", "Komodo_dragon"], "49": ["n01697457", "African_crocodile"], "50": ["n01698640", "American_alligator"], "51": ["n01704323", "triceratops"], "52": ["n01728572", "thunder_snake"], "53": ["n01728920", "ringneck_snake"], "54": ["n01729322", "hognose_snake"], "55": ["n01729977", "green_snake"], "56": ["n01734418", "king_snake"], "57": ["n01735189", "garter_snake"], "58": ["n01737021", "water_snake"], "59": ["n01739381", "vine_snake"], "60": ["n01740131", "night_snake"], "61": ["n01742172", "boa_constrictor"], "62": ["n01744401", "rock_python"], "63": ["n01748264", "Indian_cobra"], "64": ["n01749939", "green_mamba"], "65": ["n01751748", "sea_snake"], "66": ["n01753488", "horned_viper"], "67": ["n01755581", "diamondback"], "68": ["n01756291", "sidewinder"], "69": ["n01768244", "trilobite"], "70": ["n01770081", "harvestman"], "71": ["n01770393", "scorpion"], "72": ["n01773157", "black_and_gold_garden_spider"], "73": ["n01773549", "barn_spider"], "74": ["n01773797", "garden_spider"], "75": ["n01774384", "black_widow"], "76": ["n01774750", "tarantula"], "77": ["n01775062", "wolf_spider"], "78": ["n01776313", "tick"], "79": ["n01784675", "centipede"], "80": ["n01795545", "black_grouse"], "81": ["n01796340", "ptarmigan"], "82": ["n01797886", "ruffed_grouse"], "83": ["n01798484", "prairie_chicken"], "84": ["n01806143", "peacock"], "85": ["n01806567", "quail"], "86": ["n01807496", "partridge"], "87": ["n01817953", "African_grey"], "88": ["n01818515", "macaw"], "89": ["n01819313", "sulphur-crested_cockatoo"], "90": ["n01820546", "lorikeet"], "91": ["n01824575", "coucal"], "92": ["n01828970", "bee_eater"], "93": ["n01829413", "hornbill"], "94": ["n01833805", "hummingbird"], "95": ["n01843065", "jacamar"], "96": ["n01843383", "toucan"], "97": ["n01847000", "drake"], "98": ["n01855032", "red-breasted_merganser"], "99": ["n01855672", "goose"], "100": ["n01860187", "black_swan"], "101": ["n01871265", "tusker"], "102": ["n01872401", "echidna"], "103": ["n01873310", "platypus"], "104": ["n01877812", "wallaby"], "105": ["n01882714", "koala"], "106": ["n01883070", "wombat"], "107": ["n01910747", "jellyfish"], "108": ["n01914609", "sea_anemone"], "109": ["n01917289", "brain_coral"], "110": ["n01924916", "flatworm"], "111": ["n01930112", "nematode"], "112": ["n01943899", "conch"], "113": ["n01944390", "snail"], "114": ["n01945685", "slug"], "115": ["n01950731", "sea_slug"], "116": ["n01955084", "chiton"], "117": ["n01968897", "chambered_nautilus"], "118": ["n01978287", "Dungeness_crab"], "119": ["n01978455", "rock_crab"], "120": ["n01980166", "fiddler_crab"], "121": ["n01981276", "king_crab"], "122": ["n01983481", "American_lobster"], "123": ["n01984695", "spiny_lobster"], "124": ["n01985128", "crayfish"], "125": ["n01986214", "hermit_crab"], "126": ["n01990800", "isopod"], "127": ["n02002556", "white_stork"], "128": ["n02002724", "black_stork"], "129": ["n02006656", "spoonbill"], "130": ["n02007558", "flamingo"], "131": ["n02009229", "little_blue_heron"], "132": ["n02009912", "American_egret"], "133": ["n02011460", "bittern"], "134": ["n02012849", "crane"], "135": ["n02013706", "limpkin"], "136": ["n02017213", "European_gallinule"], "137": ["n02018207", "American_coot"], "138": ["n02018795", "bustard"], "139": ["n02025239", "ruddy_turnstone"], "140": ["n02027492", "red-backed_sandpiper"], "141": ["n02028035", "redshank"], "142": ["n02033041", "dowitcher"], "143": ["n02037110", "oystercatcher"], "144": ["n02051845", "pelican"], "145": ["n02056570", "king_penguin"], "146": ["n02058221", "albatross"], "147": ["n02066245", "grey_whale"], "148": ["n02071294", "killer_whale"], "149": ["n02074367", "dugong"], "150": ["n02077923", "sea_lion"], "151": ["n02085620", "Chihuahua"], "152": ["n02085782", "Japanese_spaniel"], "153": ["n02085936", "Maltese_dog"], "154": ["n02086079", "Pekinese"], "155": ["n02086240", "Shih-Tzu"], "156": ["n02086646", "Blenheim_spaniel"], "157": ["n02086910", "papillon"], "158": ["n02087046", "toy_terrier"], "159": ["n02087394", "Rhodesian_ridgeback"], "160": ["n02088094", "Afghan_hound"], "161": ["n02088238", "basset"], "162": ["n02088364", "beagle"], "163": ["n02088466", "bloodhound"], "164": ["n02088632", "bluetick"], "165": ["n02089078", "black-and-tan_coonhound"], "166": ["n02089867", "Walker_hound"], "167": ["n02089973", "English_foxhound"], "168": ["n02090379", "redbone"], "169": ["n02090622", "borzoi"], "170": ["n02090721", "Irish_wolfhound"], "171": ["n02091032", "Italian_greyhound"], "172": ["n02091134", "whippet"], "173": ["n02091244", "Ibizan_hound"], "174": ["n02091467", "Norwegian_elkhound"], "175": ["n02091635", "otterhound"], "176": ["n02091831", "Saluki"], "177": ["n02092002", "Scottish_deerhound"], "178": ["n02092339", "Weimaraner"], "179": ["n02093256", "Staffordshire_bullterrier"], "180": ["n02093428", "American_Staffordshire_terrier"], "181": ["n02093647", "Bedlington_terrier"], "182": ["n02093754", "Border_terrier"], "183": ["n02093859", "Kerry_blue_terrier"], "184": ["n02093991", "Irish_terrier"], "185": ["n02094114", "Norfolk_terrier"], "186": ["n02094258", "Norwich_terrier"], "187": ["n02094433", "Yorkshire_terrier"], "188": ["n02095314", "wire-haired_fox_terrier"], "189": ["n02095570", "Lakeland_terrier"], "190": ["n02095889", "Sealyham_terrier"], "191": ["n02096051", "Airedale"], "192": ["n02096177", "cairn"], "193": ["n02096294", "Australian_terrier"], "194": ["n02096437", "Dandie_Dinmont"], "195": ["n02096585", "Boston_bull"], "196": ["n02097047", "miniature_schnauzer"], "197": ["n02097130", "giant_schnauzer"], "198": ["n02097209", "standard_schnauzer"], "199": ["n02097298", "Scotch_terrier"], "200": ["n02097474", "Tibetan_terrier"], "201": ["n02097658", "silky_terrier"], "202": ["n02098105", "soft-coated_wheaten_terrier"], "203": ["n02098286", "West_Highland_white_terrier"], "204": ["n02098413", "Lhasa"], "205": ["n02099267", "flat-coated_retriever"], "206": ["n02099429", "curly-coated_retriever"], "207": ["n02099601", "golden_retriever"], "208": ["n02099712", "Labrador_retriever"], "209": ["n02099849", "Chesapeake_Bay_retriever"], "210": ["n02100236", "German_short-haired_pointer"], "211": ["n02100583", "vizsla"], "212": ["n02100735", "English_setter"], "213": ["n02100877", "Irish_setter"], "214": ["n02101006", "Gordon_setter"], "215": ["n02101388", "Brittany_spaniel"], "216": ["n02101556", "clumber"], "217": ["n02102040", "English_springer"], "218": ["n02102177", "Welsh_springer_spaniel"], "219": ["n02102318", "cocker_spaniel"], "220": ["n02102480", "Sussex_spaniel"], "221": ["n02102973", "Irish_water_spaniel"], "222": ["n02104029", "kuvasz"], "223": ["n02104365", "schipperke"], "224": ["n02105056", "groenendael"], "225": ["n02105162", "malinois"], "226": ["n02105251", "briard"], "227": ["n02105412", "kelpie"], "228": ["n02105505", "komondor"], "229": ["n02105641", "Old_English_sheepdog"], "230": ["n02105855", "Shetland_sheepdog"], "231": ["n02106030", "collie"], "232": ["n02106166", "Border_collie"], "233": ["n02106382", "Bouvier_des_Flandres"], "234": ["n02106550", "Rottweiler"], "235": ["n02106662", "German_shepherd"], "236": ["n02107142", "Doberman"], "237": ["n02107312", "miniature_pinscher"], "238": ["n02107574", "Greater_Swiss_Mountain_dog"], "239": ["n02107683", "Bernese_mountain_dog"], "240": ["n02107908", "Appenzeller"], "241": ["n02108000", "EntleBucher"], "242": ["n02108089", "boxer"], "243": ["n02108422", "bull_mastiff"], "244": ["n02108551", "Tibetan_mastiff"], "245": ["n02108915", "French_bulldog"], "246": ["n02109047", "Great_Dane"], "247": ["n02109525", "Saint_Bernard"], "248": ["n02109961", "Eskimo_dog"], "249": ["n02110063", "malamute"], "250": ["n02110185", "Siberian_husky"], "251": ["n02110341", "dalmatian"], "252": ["n02110627", "affenpinscher"], "253": ["n02110806", "basenji"], "254": ["n02110958", "pug"], "255": ["n02111129", "Leonberg"], "256": ["n02111277", "Newfoundland"], "257": ["n02111500", "Great_Pyrenees"], "258": ["n02111889", "Samoyed"], "259": ["n02112018", "Pomeranian"], "260": ["n02112137", "chow"], "261": ["n02112350", "keeshond"], "262": ["n02112706", "Brabancon_griffon"], "263": ["n02113023", "Pembroke"], "264": ["n02113186", "Cardigan"], "265": ["n02113624", "toy_poodle"], "266": ["n02113712", "miniature_poodle"], "267": ["n02113799", "standard_poodle"], "268": ["n02113978", "Mexican_hairless"], "269": ["n02114367", "timber_wolf"], "270": ["n02114548", "white_wolf"], "271": ["n02114712", "red_wolf"], "272": ["n02114855", "coyote"], "273": ["n02115641", "dingo"], "274": ["n02115913", "dhole"], "275": ["n02116738", "African_hunting_dog"], "276": ["n02117135", "hyena"], "277": ["n02119022", "red_fox"], "278": ["n02119789", "kit_fox"], "279": ["n02120079", "Arctic_fox"], "280": ["n02120505", "grey_fox"], "281": ["n02123045", "tabby"], "282": ["n02123159", "tiger_cat"], "283": ["n02123394", "Persian_cat"], "284": ["n02123597", "Siamese_cat"], "285": ["n02124075", "Egyptian_cat"], "286": ["n02125311", "cougar"], "287": ["n02127052", "lynx"], "288": ["n02128385", "leopard"], "289": ["n02128757", "snow_leopard"], "290": ["n02128925", "jaguar"], "291": ["n02129165", "lion"], "292": ["n02129604", "tiger"], "293": ["n02130308", "cheetah"], "294": ["n02132136", "brown_bear"], "295": ["n02133161", "American_black_bear"], "296": ["n02134084", "ice_bear"], "297": ["n02134418", "sloth_bear"], "298": ["n02137549", "mongoose"], "299": ["n02138441", "meerkat"], "300": ["n02165105", "tiger_beetle"], "301": ["n02165456", "ladybug"], "302": ["n02167151", "ground_beetle"], "303": ["n02168699", "long-horned_beetle"], "304": ["n02169497", "leaf_beetle"], "305": ["n02172182", "dung_beetle"], "306": ["n02174001", "rhinoceros_beetle"], "307": ["n02177972", "weevil"], "308": ["n02190166", "fly"], "309": ["n02206856", "bee"], "310": ["n02219486", "ant"], "311": ["n02226429", "grasshopper"], "312": ["n02229544", "cricket"], "313": ["n02231487", "walking_stick"], "314": ["n02233338", "cockroach"], "315": ["n02236044", "mantis"], "316": ["n02256656", "cicada"], "317": ["n02259212", "leafhopper"], "318": ["n02264363", "lacewing"], "319": ["n02268443", "dragonfly"], "320": ["n02268853", "damselfly"], "321": ["n02276258", "admiral"], "322": ["n02277742", "ringlet"], "323": ["n02279972", "monarch"], "324": ["n02280649", "cabbage_butterfly"], "325": ["n02281406", "sulphur_butterfly"], "326": ["n02281787", "lycaenid"], "327": ["n02317335", "starfish"], "328": ["n02319095", "sea_urchin"], "329": ["n02321529", "sea_cucumber"], "330": ["n02325366", "wood_rabbit"], "331": ["n02326432", "hare"], "332": ["n02328150", "Angora"], "333": ["n02342885", "hamster"], "334": ["n02346627", "porcupine"], "335": ["n02356798", "fox_squirrel"], "336": ["n02361337", "marmot"], "337": ["n02363005", "beaver"], "338": ["n02364673", "guinea_pig"], "339": ["n02389026", "sorrel"], "340": ["n02391049", "zebra"], "341": ["n02395406", "hog"], "342": ["n02396427", "wild_boar"], "343": ["n02397096", "warthog"], "344": ["n02398521", "hippopotamus"], "345": ["n02403003", "ox"], "346": ["n02408429", "water_buffalo"], "347": ["n02410509", "bison"], "348": ["n02412080", "ram"], "349": ["n02415577", "bighorn"], "350": ["n02417914", "ibex"], "351": ["n02422106", "hartebeest"], "352": ["n02422699", "impala"], "353": ["n02423022", "gazelle"], "354": ["n02437312", "Arabian_camel"], "355": ["n02437616", "llama"], "356": ["n02441942", "weasel"], "357": ["n02442845", "mink"], "358": ["n02443114", "polecat"], "359": ["n02443484", "black-footed_ferret"], "360": ["n02444819", "otter"], "361": ["n02445715", "skunk"], "362": ["n02447366", "badger"], "363": ["n02454379", "armadillo"], "364": ["n02457408", "three-toed_sloth"], "365": ["n02480495", "orangutan"], "366": ["n02480855", "gorilla"], "367": ["n02481823", "chimpanzee"], "368": ["n02483362", "gibbon"], "369": ["n02483708", "siamang"], "370": ["n02484975", "guenon"], "371": ["n02486261", "patas"], "372": ["n02486410", "baboon"], "373": ["n02487347", "macaque"], "374": ["n02488291", "langur"], "375": ["n02488702", "colobus"], "376": ["n02489166", "proboscis_monkey"], "377": ["n02490219", "marmoset"], "378": ["n02492035", "capuchin"], "379": ["n02492660", "howler_monkey"], "380": ["n02493509", "titi"], "381": ["n02493793", "spider_monkey"], "382": ["n02494079", "squirrel_monkey"], "383": ["n02497673", "Madagascar_cat"], "384": ["n02500267", "indri"], "385": ["n02504013", "Indian_elephant"], "386": ["n02504458", "African_elephant"], "387": ["n02509815", "lesser_panda"], "388": ["n02510455", "giant_panda"], "389": ["n02514041", "barracouta"], "390": ["n02526121", "eel"], "391": ["n02536864", "coho"], "392": ["n02606052", "rock_beauty"], "393": ["n02607072", "anemone_fish"], "394": ["n02640242", "sturgeon"], "395": ["n02641379", "gar"], "396": ["n02643566", "lionfish"], "397": ["n02655020", "puffer"], "398": ["n02666196", "abacus"], "399": ["n02667093", "abaya"], "400": ["n02669723", "academic_gown"], "401": ["n02672831", "accordion"], "402": ["n02676566", "acoustic_guitar"], "403": ["n02687172", "aircraft_carrier"], "404": ["n02690373", "airliner"], "405": ["n02692877", "airship"], "406": ["n02699494", "altar"], "407": ["n02701002", "ambulance"], "408": ["n02704792", "amphibian"], "409": ["n02708093", "analog_clock"], "410": ["n02727426", "apiary"], "411": ["n02730930", "apron"], "412": ["n02747177", "ashcan"], "413": ["n02749479", "assault_rifle"], "414": ["n02769748", "backpack"], "415": ["n02776631", "bakery"], "416": ["n02777292", "balance_beam"], "417": ["n02782093", "balloon"], "418": ["n02783161", "ballpoint"], "419": ["n02786058", "Band_Aid"], "420": ["n02787622", "banjo"], "421": ["n02788148", "bannister"], "422": ["n02790996", "barbell"], "423": ["n02791124", "barber_chair"], "424": ["n02791270", "barbershop"], "425": ["n02793495", "barn"], "426": ["n02794156", "barometer"], "427": ["n02795169", "barrel"], "428": ["n02797295", "barrow"], "429": ["n02799071", "baseball"], "430": ["n02802426", "basketball"], "431": ["n02804414", "bassinet"], "432": ["n02804610", "bassoon"], "433": ["n02807133", "bathing_cap"], "434": ["n02808304", "bath_towel"], "435": ["n02808440", "bathtub"], "436": ["n02814533", "beach_wagon"], "437": ["n02814860", "beacon"], "438": ["n02815834", "beaker"], "439": ["n02817516", "bearskin"], "440": ["n02823428", "beer_bottle"], "441": ["n02823750", "beer_glass"], "442": ["n02825657", "bell_cote"], "443": ["n02834397", "bib"], "444": ["n02835271", "bicycle-built-for-two"], "445": ["n02837789", "bikini"], "446": ["n02840245", "binder"], "447": ["n02841315", "binoculars"], "448": ["n02843684", "birdhouse"], "449": ["n02859443", "boathouse"], "450": ["n02860847", "bobsled"], "451": ["n02865351", "bolo_tie"], "452": ["n02869837", "bonnet"], "453": ["n02870880", "bookcase"], "454": ["n02871525", "bookshop"], "455": ["n02877765", "bottlecap"], "456": ["n02879718", "bow"], "457": ["n02883205", "bow_tie"], "458": ["n02892201", "brass"], "459": ["n02892767", "brassiere"], "460": ["n02894605", "breakwater"], "461": ["n02895154", "breastplate"], "462": ["n02906734", "broom"], "463": ["n02909870", "bucket"], "464": ["n02910353", "buckle"], "465": ["n02916936", "bulletproof_vest"], "466": ["n02917067", "bullet_train"], "467": ["n02927161", "butcher_shop"], "468": ["n02930766", "cab"], "469": ["n02939185", "caldron"], "470": ["n02948072", "candle"], "471": ["n02950826", "cannon"], "472": ["n02951358", "canoe"], "473": ["n02951585", "can_opener"], "474": ["n02963159", "cardigan"], "475": ["n02965783", "car_mirror"], "476": ["n02966193", "carousel"], "477": ["n02966687", "carpenter's_kit"], "478": ["n02971356", "carton"], "479": ["n02974003", "car_wheel"], "480": ["n02977058", "cash_machine"], "481": ["n02978881", "cassette"], "482": ["n02979186", "cassette_player"], "483": ["n02980441", "castle"], "484": ["n02981792", "catamaran"], "485": ["n02988304", "CD_player"], "486": ["n02992211", "cello"], "487": ["n02992529", "cellular_telephone"], "488": ["n02999410", "chain"], "489": ["n03000134", "chainlink_fence"], "490": ["n03000247", "chain_mail"], "491": ["n03000684", "chain_saw"], "492": ["n03014705", "chest"], "493": ["n03016953", "chiffonier"], "494": ["n03017168", "chime"], "495": ["n03018349", "china_cabinet"], "496": ["n03026506", "Christmas_stocking"], "497": ["n03028079", "church"], "498": ["n03032252", "cinema"], "499": ["n03041632", "cleaver"], "500": ["n03042490", "cliff_dwelling"], "501": ["n03045698", "cloak"], "502": ["n03047690", "clog"], "503": ["n03062245", "cocktail_shaker"], "504": ["n03063599", "coffee_mug"], "505": ["n03063689", "coffeepot"], "506": ["n03065424", "coil"], "507": ["n03075370", "combination_lock"], "508": ["n03085013", "computer_keyboard"], "509": ["n03089624", "confectionery"], "510": ["n03095699", "container_ship"], "511": ["n03100240", "convertible"], "512": ["n03109150", "corkscrew"], "513": ["n03110669", "cornet"], "514": ["n03124043", "cowboy_boot"], "515": ["n03124170", "cowboy_hat"], "516": ["n03125729", "cradle"], "517": ["n03126707", "crane_2"], "518": ["n03127747", "crash_helmet"], "519": ["n03127925", "crate"], "520": ["n03131574", "crib"], "521": ["n03133878", "Crock_Pot"], "522": ["n03134739", "croquet_ball"], "523": ["n03141823", "crutch"], "524": ["n03146219", "cuirass"], "525": ["n03160309", "dam"], "526": ["n03179701", "desk"], "527": ["n03180011", "desktop_computer"], "528": ["n03187595", "dial_telephone"], "529": ["n03188531", "diaper"], "530": ["n03196217", "digital_clock"], "531": ["n03197337", "digital_watch"], "532": ["n03201208", "dining_table"], "533": ["n03207743", "dishrag"], "534": ["n03207941", "dishwasher"], "535": ["n03208938", "disk_brake"], "536": ["n03216828", "dock"], "537": ["n03218198", "dogsled"], "538": ["n03220513", "dome"], "539": ["n03223299", "doormat"], "540": ["n03240683", "drilling_platform"], "541": ["n03249569", "drum"], "542": ["n03250847", "drumstick"], "543": ["n03255030", "dumbbell"], "544": ["n03259280", "Dutch_oven"], "545": ["n03271574", "electric_fan"], "546": ["n03272010", "electric_guitar"], "547": ["n03272562", "electric_locomotive"], "548": ["n03290653", "entertainment_center"], "549": ["n03291819", "envelope"], "550": ["n03297495", "espresso_maker"], "551": ["n03314780", "face_powder"], "552": ["n03325584", "feather_boa"], "553": ["n03337140", "file"], "554": ["n03344393", "fireboat"], "555": ["n03345487", "fire_engine"], "556": ["n03347037", "fire_screen"], "557": ["n03355925", "flagpole"], "558": ["n03372029", "flute"], "559": ["n03376595", "folding_chair"], "560": ["n03379051", "football_helmet"], "561": ["n03384352", "forklift"], "562": ["n03388043", "fountain"], "563": ["n03388183", "fountain_pen"], "564": ["n03388549", "four-poster"], "565": ["n03393912", "freight_car"], "566": ["n03394916", "French_horn"], "567": ["n03400231", "frying_pan"], "568": ["n03404251", "fur_coat"], "569": ["n03417042", "garbage_truck"], "570": ["n03424325", "gasmask"], "571": ["n03425413", "gas_pump"], "572": ["n03443371", "goblet"], "573": ["n03444034", "go-kart"], "574": ["n03445777", "golf_ball"], "575": ["n03445924", "golfcart"], "576": ["n03447447", "gondola"], "577": ["n03447721", "gong"], "578": ["n03450230", "gown"], "579": ["n03452741", "grand_piano"], "580": ["n03457902", "greenhouse"], "581": ["n03459775", "grille"], "582": ["n03461385", "grocery_store"], "583": ["n03467068", "guillotine"], "584": ["n03476684", "hair_slide"], "585": ["n03476991", "hair_spray"], "586": ["n03478589", "half_track"], "587": ["n03481172", "hammer"], "588": ["n03482405", "hamper"], "589": ["n03483316", "hand_blower"], "590": ["n03485407", "hand-held_computer"], "591": ["n03485794", "handkerchief"], "592": ["n03492542", "hard_disc"], "593": ["n03494278", "harmonica"], "594": ["n03495258", "harp"], "595": ["n03496892", "harvester"], "596": ["n03498962", "hatchet"], "597": ["n03527444", "holster"], "598": ["n03529860", "home_theater"], "599": ["n03530642", "honeycomb"], "600": ["n03532672", "hook"], "601": ["n03534580", "hoopskirt"], "602": ["n03535780", "horizontal_bar"], "603": ["n03538406", "horse_cart"], "604": ["n03544143", "hourglass"], "605": ["n03584254", "iPod"], "606": ["n03584829", "iron"], "607": ["n03590841", "jack-o'-lantern"], "608": ["n03594734", "jean"], "609": ["n03594945", "jeep"], "610": ["n03595614", "jersey"], "611": ["n03598930", "jigsaw_puzzle"], "612": ["n03599486", "jinrikisha"], "613": ["n03602883", "joystick"], "614": ["n03617480", "kimono"], "615": ["n03623198", "knee_pad"], "616": ["n03627232", "knot"], "617": ["n03630383", "lab_coat"], "618": ["n03633091", "ladle"], "619": ["n03637318", "lampshade"], "620": ["n03642806", "laptop"], "621": ["n03649909", "lawn_mower"], "622": ["n03657121", "lens_cap"], "623": ["n03658185", "letter_opener"], "624": ["n03661043", "library"], "625": ["n03662601", "lifeboat"], "626": ["n03666591", "lighter"], "627": ["n03670208", "limousine"], "628": ["n03673027", "liner"], "629": ["n03676483", "lipstick"], "630": ["n03680355", "Loafer"], "631": ["n03690938", "lotion"], "632": ["n03691459", "loudspeaker"], "633": ["n03692522", "loupe"], "634": ["n03697007", "lumbermill"], "635": ["n03706229", "magnetic_compass"], "636": ["n03709823", "mailbag"], "637": ["n03710193", "mailbox"], "638": ["n03710637", "maillot"], "639": ["n03710721", "maillot_2"], "640": ["n03717622", "manhole_cover"], "641": ["n03720891", "maraca"], "642": ["n03721384", "marimba"], "643": ["n03724870", "mask"], "644": ["n03729826", "matchstick"], "645": ["n03733131", "maypole"], "646": ["n03733281", "maze"], "647": ["n03733805", "measuring_cup"], "648": ["n03742115", "medicine_chest"], "649": ["n03743016", "megalith"], "650": ["n03759954", "microphone"], "651": ["n03761084", "microwave"], "652": ["n03763968", "military_uniform"], "653": ["n03764736", "milk_can"], "654": ["n03769881", "minibus"], "655": ["n03770439", "miniskirt"], "656": ["n03770679", "minivan"], "657": ["n03773504", "missile"], "658": ["n03775071", "mitten"], "659": ["n03775546", "mixing_bowl"], "660": ["n03776460", "mobile_home"], "661": ["n03777568", "Model_T"], "662": ["n03777754", "modem"], "663": ["n03781244", "monastery"], "664": ["n03782006", "monitor"], "665": ["n03785016", "moped"], "666": ["n03786901", "mortar"], "667": ["n03787032", "mortarboard"], "668": ["n03788195", "mosque"], "669": ["n03788365", "mosquito_net"], "670": ["n03791053", "motor_scooter"], "671": ["n03792782", "mountain_bike"], "672": ["n03792972", "mountain_tent"], "673": ["n03793489", "mouse"], "674": ["n03794056", "mousetrap"], "675": ["n03796401", "moving_van"], "676": ["n03803284", "muzzle"], "677": ["n03804744", "nail"], "678": ["n03814639", "neck_brace"], "679": ["n03814906", "necklace"], "680": ["n03825788", "nipple"], "681": ["n03832673", "notebook"], "682": ["n03837869", "obelisk"], "683": ["n03838899", "oboe"], "684": ["n03840681", "ocarina"], "685": ["n03841143", "odometer"], "686": ["n03843555", "oil_filter"], "687": ["n03854065", "organ"], "688": ["n03857828", "oscilloscope"], "689": ["n03866082", "overskirt"], "690": ["n03868242", "oxcart"], "691": ["n03868863", "oxygen_mask"], "692": ["n03871628", "packet"], "693": ["n03873416", "paddle"], "694": ["n03874293", "paddlewheel"], "695": ["n03874599", "padlock"], "696": ["n03876231", "paintbrush"], "697": ["n03877472", "pajama"], "698": ["n03877845", "palace"], "699": ["n03884397", "panpipe"], "700": ["n03887697", "paper_towel"], "701": ["n03888257", "parachute"], "702": ["n03888605", "parallel_bars"], "703": ["n03891251", "park_bench"], "704": ["n03891332", "parking_meter"], "705": ["n03895866", "passenger_car"], "706": ["n03899768", "patio"], "707": ["n03902125", "pay-phone"], "708": ["n03903868", "pedestal"], "709": ["n03908618", "pencil_box"], "710": ["n03908714", "pencil_sharpener"], "711": ["n03916031", "perfume"], "712": ["n03920288", "Petri_dish"], "713": ["n03924679", "photocopier"], "714": ["n03929660", "pick"], "715": ["n03929855", "pickelhaube"], "716": ["n03930313", "picket_fence"], "717": ["n03930630", "pickup"], "718": ["n03933933", "pier"], "719": ["n03935335", "piggy_bank"], "720": ["n03937543", "pill_bottle"], "721": ["n03938244", "pillow"], "722": ["n03942813", "ping-pong_ball"], "723": ["n03944341", "pinwheel"], "724": ["n03947888", "pirate"], "725": ["n03950228", "pitcher"], "726": ["n03954731", "plane"], "727": ["n03956157", "planetarium"], "728": ["n03958227", "plastic_bag"], "729": ["n03961711", "plate_rack"], "730": ["n03967562", "plow"], "731": ["n03970156", "plunger"], "732": ["n03976467", "Polaroid_camera"], "733": ["n03976657", "pole"], "734": ["n03977966", "police_van"], "735": ["n03980874", "poncho"], "736": ["n03982430", "pool_table"], "737": ["n03983396", "pop_bottle"], "738": ["n03991062", "pot"], "739": ["n03992509", "potter's_wheel"], "740": ["n03995372", "power_drill"], "741": ["n03998194", "prayer_rug"], "742": ["n04004767", "printer"], "743": ["n04005630", "prison"], "744": ["n04008634", "projectile"], "745": ["n04009552", "projector"], "746": ["n04019541", "puck"], "747": ["n04023962", "punching_bag"], "748": ["n04026417", "purse"], "749": ["n04033901", "quill"], "750": ["n04033995", "quilt"], "751": ["n04037443", "racer"], "752": ["n04039381", "racket"], "753": ["n04040759", "radiator"], "754": ["n04041544", "radio"], "755": ["n04044716", "radio_telescope"], "756": ["n04049303", "rain_barrel"], "757": ["n04065272", "recreational_vehicle"], "758": ["n04067472", "reel"], "759": ["n04069434", "reflex_camera"], "760": ["n04070727", "refrigerator"], "761": ["n04074963", "remote_control"], "762": ["n04081281", "restaurant"], "763": ["n04086273", "revolver"], "764": ["n04090263", "rifle"], "765": ["n04099969", "rocking_chair"], "766": ["n04111531", "rotisserie"], "767": ["n04116512", "rubber_eraser"], "768": ["n04118538", "rugby_ball"], "769": ["n04118776", "rule"], "770": ["n04120489", "running_shoe"], "771": ["n04125021", "safe"], "772": ["n04127249", "safety_pin"], "773": ["n04131690", "saltshaker"], "774": ["n04133789", "sandal"], "775": ["n04136333", "sarong"], "776": ["n04141076", "sax"], "777": ["n04141327", "scabbard"], "778": ["n04141975", "scale"], "779": ["n04146614", "school_bus"], "780": ["n04147183", "schooner"], "781": ["n04149813", "scoreboard"], "782": ["n04152593", "screen"], "783": ["n04153751", "screw"], "784": ["n04154565", "screwdriver"], "785": ["n04162706", "seat_belt"], "786": ["n04179913", "sewing_machine"], "787": ["n04192698", "shield"], "788": ["n04200800", "shoe_shop"], "789": ["n04201297", "shoji"], "790": ["n04204238", "shopping_basket"], "791": ["n04204347", "shopping_cart"], "792": ["n04208210", "shovel"], "793": ["n04209133", "shower_cap"], "794": ["n04209239", "shower_curtain"], "795": ["n04228054", "ski"], "796": ["n04229816", "ski_mask"], "797": ["n04235860", "sleeping_bag"], "798": ["n04238763", "slide_rule"], "799": ["n04239074", "sliding_door"], "800": ["n04243546", "slot"], "801": ["n04251144", "snorkel"], "802": ["n04252077", "snowmobile"], "803": ["n04252225", "snowplow"], "804": ["n04254120", "soap_dispenser"], "805": ["n04254680", "soccer_ball"], "806": ["n04254777", "sock"], "807": ["n04258138", "solar_dish"], "808": ["n04259630", "sombrero"], "809": ["n04263257", "soup_bowl"], "810": ["n04264628", "space_bar"], "811": ["n04265275", "space_heater"], "812": ["n04266014", "space_shuttle"], "813": ["n04270147", "spatula"], "814": ["n04273569", "speedboat"], "815": ["n04275548", "spider_web"], "816": ["n04277352", "spindle"], "817": ["n04285008", "sports_car"], "818": ["n04286575", "spotlight"], "819": ["n04296562", "stage"], "820": ["n04310018", "steam_locomotive"], "821": ["n04311004", "steel_arch_bridge"], "822": ["n04311174", "steel_drum"], "823": ["n04317175", "stethoscope"], "824": ["n04325704", "stole"], "825": ["n04326547", "stone_wall"], "826": ["n04328186", "stopwatch"], "827": ["n04330267", "stove"], "828": ["n04332243", "strainer"], "829": ["n04335435", "streetcar"], "830": ["n04336792", "stretcher"], "831": ["n04344873", "studio_couch"], "832": ["n04346328", "stupa"], "833": ["n04347754", "submarine"], "834": ["n04350905", "suit"], "835": ["n04355338", "sundial"], "836": ["n04355933", "sunglass"], "837": ["n04356056", "sunglasses"], "838": ["n04357314", "sunscreen"], "839": ["n04366367", "suspension_bridge"], "840": ["n04367480", "swab"], "841": ["n04370456", "sweatshirt"], "842": ["n04371430", "swimming_trunks"], "843": ["n04371774", "swing"], "844": ["n04372370", "switch"], "845": ["n04376876", "syringe"], "846": ["n04380533", "table_lamp"], "847": ["n04389033", "tank"], "848": ["n04392985", "tape_player"], "849": ["n04398044", "teapot"], "850": ["n04399382", "teddy"], "851": ["n04404412", "television"], "852": ["n04409515", "tennis_ball"], "853": ["n04417672", "thatch"], "854": ["n04418357", "theater_curtain"], "855": ["n04423845", "thimble"], "856": ["n04428191", "thresher"], "857": ["n04429376", "throne"], "858": ["n04435653", "tile_roof"], "859": ["n04442312", "toaster"], "860": ["n04443257", "tobacco_shop"], "861": ["n04447861", "toilet_seat"], "862": ["n04456115", "torch"], "863": ["n04458633", "totem_pole"], "864": ["n04461696", "tow_truck"], "865": ["n04462240", "toyshop"], "866": ["n04465501", "tractor"], "867": ["n04467665", "trailer_truck"], "868": ["n04476259", "tray"], "869": ["n04479046", "trench_coat"], "870": ["n04482393", "tricycle"], "871": ["n04483307", "trimaran"], "872": ["n04485082", "tripod"], "873": ["n04486054", "triumphal_arch"], "874": ["n04487081", "trolleybus"], "875": ["n04487394", "trombone"], "876": ["n04493381", "tub"], "877": ["n04501370", "turnstile"], "878": ["n04505470", "typewriter_keyboard"], "879": ["n04507155", "umbrella"], "880": ["n04509417", "unicycle"], "881": ["n04515003", "upright"], "882": ["n04517823", "vacuum"], "883": ["n04522168", "vase"], "884": ["n04523525", "vault"], "885": ["n04525038", "velvet"], "886": ["n04525305", "vending_machine"], "887": ["n04532106", "vestment"], "888": ["n04532670", "viaduct"], "889": ["n04536866", "violin"], "890": ["n04540053", "volleyball"], "891": ["n04542943", "waffle_iron"], "892": ["n04548280", "wall_clock"], "893": ["n04548362", "wallet"], "894": ["n04550184", "wardrobe"], "895": ["n04552348", "warplane"], "896": ["n04553703", "washbasin"], "897": ["n04554684", "washer"], "898": ["n04557648", "water_bottle"], "899": ["n04560804", "water_jug"], "900": ["n04562935", "water_tower"], "901": ["n04579145", "whiskey_jug"], "902": ["n04579432", "whistle"], "903": ["n04584207", "wig"], "904": ["n04589890", "window_screen"], "905": ["n04590129", "window_shade"], "906": ["n04591157", "Windsor_tie"], "907": ["n04591713", "wine_bottle"], "908": ["n04592741", "wing"], "909": ["n04596742", "wok"], "910": ["n04597913", "wooden_spoon"], "911": ["n04599235", "wool"], "912": ["n04604644", "worm_fence"], "913": ["n04606251", "wreck"], "914": ["n04612504", "yawl"], "915": ["n04613696", "yurt"], "916": ["n06359193", "web_site"], "917": ["n06596364", "comic_book"], "918": ["n06785654", "crossword_puzzle"], "919": ["n06794110", "street_sign"], "920": ["n06874185", "traffic_light"], "921": ["n07248320", "book_jacket"], "922": ["n07565083", "menu"], "923": ["n07579787", "plate"], "924": ["n07583066", "guacamole"], "925": ["n07584110", "consomme"], "926": ["n07590611", "hot_pot"], "927": ["n07613480", "trifle"], "928": ["n07614500", "ice_cream"], "929": ["n07615774", "ice_lolly"], "930": ["n07684084", "French_loaf"], "931": ["n07693725", "bagel"], "932": ["n07695742", "pretzel"], "933": ["n07697313", "cheeseburger"], "934": ["n07697537", "hotdog"], "935": ["n07711569", "mashed_potato"], "936": ["n07714571", "head_cabbage"], "937": ["n07714990", "broccoli"], "938": ["n07715103", "cauliflower"], "939": ["n07716358", "zucchini"], "940": ["n07716906", "spaghetti_squash"], "941": ["n07717410", "acorn_squash"], "942": ["n07717556", "butternut_squash"], "943": ["n07718472", "cucumber"], "944": ["n07718747", "artichoke"], "945": ["n07720875", "bell_pepper"], "946": ["n07730033", "cardoon"], "947": ["n07734744", "mushroom"], "948": ["n07742313", "Granny_Smith"], "949": ["n07745940", "strawberry"], "950": ["n07747607", "orange"], "951": ["n07749582", "lemon"], "952": ["n07753113", "fig"], "953": ["n07753275", "pineapple"], "954": ["n07753592", "banana"], "955": ["n07754684", "jackfruit"], "956": ["n07760859", "custard_apple"], "957": ["n07768694", "pomegranate"], "958": ["n07802026", "hay"], "959": ["n07831146", "carbonara"], "960": ["n07836838", "chocolate_sauce"], "961": ["n07860988", "dough"], "962": ["n07871810", "meat_loaf"], "963": ["n07873807", "pizza"], "964": ["n07875152", "potpie"], "965": ["n07880968", "burrito"], "966": ["n07892512", "red_wine"], "967": ["n07920052", "espresso"], "968": ["n07930864", "cup"], "969": ["n07932039", "eggnog"], "970": ["n09193705", "alp"], "971": ["n09229709", "bubble"], "972": ["n09246464", "cliff"], "973": ["n09256479", "coral_reef"], "974": ["n09288635", "geyser"], "975": ["n09332890", "lakeside"], "976": ["n09399592", "promontory"], "977": ["n09421951", "sandbar"], "978": ["n09428293", "seashore"], "979": ["n09468604", "valley"], "980": ["n09472597", "volcano"], "981": ["n09835506", "ballplayer"], "982": ["n10148035", "groom"], "983": ["n10565667", "scuba_diver"], "984": ["n11879895", "rapeseed"], "985": ["n11939491", "daisy"], "986": ["n12057211", "yellow_lady's_slipper"], "987": ["n12144580", "corn"], "988": ["n12267677", "acorn"], "989": ["n12620546", "hip"], "990": ["n12768682", "buckeye"], "991": ["n12985857", "coral_fungus"], "992": ["n12998815", "agaric"], "993": ["n13037406", "gyromitra"], "994": ["n13040303", "stinkhorn"], "995": ["n13044778", "earthstar"], "996": ["n13052670", "hen-of-the-woods"], "997": ["n13054560", "bolete"], "998": ["n13133613", "ear"], "999": ["n15075141", "toilet_tissue"]} -------------------------------------------------------------------------------- /notebook/sumatran-tiger-wz-gsmp-m.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sharmasw/ImageClassification_DjangoApp/4afe6c98cb190c7fb3117996e524bedaad02db33/notebook/sumatran-tiger-wz-gsmp-m.jpg -------------------------------------------------------------------------------- /req,txt: -------------------------------------------------------------------------------- 1 | absl-py==0.11.0 2 | asgiref==3.3.1 3 | astor==0.8.1 4 | astunparse==1.6.3 5 | cached-property==1.5.2 6 | cachetools==4.2.0 7 | certifi==2020.12.5 8 | chardet==4.0.0 9 | Django==3.1.4 10 | flatbuffers==1.12 11 | gast==0.2.2 12 | google-auth==1.24.0 13 | google-auth-oauthlib==0.4.2 14 | google-pasta==0.2.0 15 | grpcio==1.32.0 16 | h5py==2.10.0 17 | idna==2.10 18 | importlib-metadata==3.3.0 19 | Keras==2.4.0 20 | Keras-Applications==1.0.8 21 | Keras-Preprocessing==1.1.2 22 | Markdown==3.3.3 23 | numpy==1.19.4 24 | oauthlib==3.1.0 25 | opt-einsum==3.3.0 26 | ortools==8.0.8283 27 | Pillow==8.0.1 28 | protobuf==3.13.0 29 | pyasn1==0.4.8 30 | pyasn1-modules==0.2.8 31 | pytz==2020.5 32 | PyYAML==5.3.1 33 | requests==2.25.1 34 | requests-oauthlib==1.3.0 35 | rsa==4.6 36 | scipy==1.5.4 37 | six==1.15.0 38 | sqlparse==0.4.1 39 | tensorboard==1.15.0 40 | tensorboard-plugin-wit==1.7.0 41 | tensorflow==1.15.3 42 | tensorflow-estimator==1.15.1 43 | termcolor==1.1.0 44 | typing-extensions==3.7.4.3 45 | urllib3==1.26.2 46 | Werkzeug==1.0.1 47 | wincertstore==0.2 48 | wrapt==1.12.1 49 | zipp==3.4.0 50 | -------------------------------------------------------------------------------- /template/headerPage.html: -------------------------------------------------------------------------------- 1 | {% load static %} 2 | 3 | 4 | 5 | 6 | MPG prediction usecase 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 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60 | {% block content%} 61 | {% endblock %} 62 | 63 |
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Copyright

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Uplaod Image for Classification

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The classification of the image is {{predictedLabel}}

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25 | 26 | 27 | {% endblock %} -------------------------------------------------------------------------------- /template/viewDB.html: -------------------------------------------------------------------------------- 1 | {% extends 'headerPage.html' %} 2 | 3 | {% block content%} 4 | 5 | {% for i in listOfImagesPath %} 6 | 7 |
8 | 9 | {% endfor%} 10 | 11 | 12 | 13 | {% endblock %} --------------------------------------------------------------------------------