├── LICENSE ├── README.md ├── config.yml ├── config100.yml ├── create_checkpoint.sh ├── create_records.sh ├── data ├── images │ ├── 0101_003.png │ ├── 0110_099.png │ ├── 0113_013.png │ ├── 0140_007.png │ ├── 0146_281.png │ ├── 0147_090.png │ ├── 0147_125.png │ ├── 0147_256.png │ ├── 0148_271.png │ ├── 0148_479.png │ ├── 0151_180.png │ ├── 0151_208.png │ ├── 0154_080.png │ ├── 0154_474.png │ ├── 0155_081.png │ ├── 0199_384.png │ ├── 0203_075.png │ ├── 0203_207.png │ ├── 0206_007.png │ ├── 0206_048.png │ ├── 0207_025.png │ ├── 0209_207.png │ ├── 0210_111.png │ ├── 0212_175.png │ ├── 0219_043.png │ ├── 0220_030.png │ ├── 0223_017.png │ ├── 0626_005.png │ ├── 0651_008.png │ ├── 0651_013.png │ ├── 0667_005.png │ ├── 0672_278.png │ ├── 0672_356.png │ ├── 0685_048.png │ ├── 0717_023.png │ ├── 0725_026.png │ ├── 0725_043.png │ ├── 0765_005.png │ ├── 1012_041.png │ ├── 1040_032.png │ ├── 1060_146.png │ ├── 1060_195.png │ ├── 1060_223.png │ ├── 1063_086.png │ ├── 1078_082.png │ ├── 1079_023.png │ ├── 1112_023.png │ ├── 1124_024.png │ ├── 1124_039.png │ ├── 1132_108.png │ ├── 1156_004.png │ ├── 1164_010.png │ ├── 1175_032.png │ ├── 1176_003.png │ ├── 1194_021.png │ ├── 1201_273.png │ ├── 1201_293.png │ ├── 1238_006.png │ ├── 1249_072.png │ ├── 1289_014.png │ ├── 1295_064.png │ ├── 1339_086.png │ ├── 1343_073.png │ ├── 1353_032.png │ ├── 1356_083.png │ ├── 1356_119.png │ ├── 1360_074.png │ ├── 1368_074.png │ ├── 1384_058.png │ ├── 1384_097.png │ ├── 1412_006.png │ ├── 1415_048.png │ ├── 1445_046.png │ ├── 1464_021.png │ ├── 1484_028.png │ ├── 1486_156.png │ ├── 1495_021.png │ ├── 1539_012.png │ ├── 1550_007.png │ ├── 1551_123.png │ ├── 1551_152.png │ ├── 1552_032.png │ ├── 1553_021.png │ ├── 1556_004.png │ ├── 1556_006.png │ ├── 1558_040.png │ ├── 1580_295.png │ ├── 1589_015.png │ ├── 1624_063.png │ ├── 1634_022.png │ ├── 1634_330.png │ ├── 1634_335.png │ ├── 1654_004.png │ ├── 1662_034.png │ ├── 1662_053.png │ ├── 1662_085.png │ ├── 1665_133.png │ ├── 1672_069.png │ ├── 1674_088.png │ ├── 1674_138.png │ ├── 1675_199.png │ ├── 1675_209.png │ ├── 1676_008.png │ ├── 1676_356.png │ ├── 1696_204.png │ ├── 1696_302.png │ ├── 1717_086.png │ ├── 1719_007.png │ ├── 1723_194.png │ ├── 1723_250.png │ ├── 1740_002.png │ ├── 1742_157.png │ ├── 1777_016.png │ ├── 1786_032.png │ ├── 1788_011.png │ ├── 1796_095.png │ ├── 1813_081.png │ ├── 1818_005.png │ ├── 1830_014.png │ ├── 1852_024.png │ ├── 1852_095.png │ ├── 1896_199.png │ ├── 1896_369.png │ ├── 1896_414.png │ ├── 1901_014.png │ ├── 1901_029.png │ ├── 1939_011.png │ ├── 1999_019.png │ ├── 2010_019.png │ ├── 2029_339.png │ ├── 2029_438.png │ ├── 2029_470.png │ ├── 2029_489.png │ ├── 2042_004.png │ ├── 2070_034.png │ ├── 2092_068.png │ ├── 2093_061.png │ ├── 2117_040.png │ ├── 2117_329.png │ ├── 2117_344.png │ ├── 2135_012.png │ ├── 2136_083.png │ ├── 2306_093.png │ ├── 5001_024.png │ ├── 5001_025.png │ ├── 5001_032.png │ ├── 5008_029.png │ ├── 5017_041.png │ ├── 5028_029.png │ ├── 5045_074.png │ ├── 5065_041.png │ ├── 5067_007.png │ ├── 5086_072.png │ ├── 5095_019.png │ ├── 5099_068.png │ ├── 5103_020.png │ ├── 5109_001.png │ ├── 5112_044.png │ ├── 5117_023.png │ ├── 5140_040.png │ ├── 5170_020.png │ ├── 5171_016.png │ ├── 5182_078.png │ ├── 5191_015.png │ ├── 5192_089.png │ ├── 5195_054.png │ ├── 5195_077.png │ ├── 5244_103.png │ ├── 5248_035.png │ ├── 5252_009.png │ ├── 5265_137.png │ ├── 5303_003.png │ ├── 5333_017.png │ ├── 5347_145.png │ ├── 5347_192.png │ ├── 5361_015.png │ ├── 5365_159.png │ ├── 5366_142.png │ ├── 5367_007.png │ ├── 5373_008.png │ ├── 5375_004.png │ ├── 5380_053.png │ ├── 5385_003.png │ ├── 5385_012.png │ ├── 5408_004.png │ ├── 5412_028.png │ ├── 5415_006.png │ ├── 5417_044.png │ ├── 5435_166.png │ ├── 5449_105.png │ ├── 5515_011.png │ ├── 5575_112.png │ ├── 5589_017.png │ ├── 5592_012.png │ ├── 5593_036.png │ ├── 5593_060.png │ ├── 5611_007.png │ ├── 5611_010.png │ ├── 5611_013.png │ ├── 5622_013.png │ ├── 5625_007.png │ ├── 5625_015.png │ ├── 5649_040.png │ ├── 5649_063.png │ ├── 5649_076.png │ ├── 5661_024.png │ ├── 5670_054.png │ ├── 5673_020.png │ ├── 5673_050.png │ ├── 5675_015.png │ ├── 5680_016.png │ ├── 5680_035.png │ ├── 5685_032.png │ ├── 5727_091.png │ ├── 5727_096.png │ ├── 5727_105.png │ ├── 5727_109.png │ ├── 5731_009.png │ ├── 5809_003.png │ ├── 5814_092.png │ ├── 5820_160.png │ ├── 5830_049.png │ ├── 5830_144.png │ ├── 5830_158.png │ ├── 5830_164.png │ ├── 5830_191.png │ ├── 5830_240.png │ ├── 5830_462.png │ ├── 5842_099.png │ ├── 5848_023.png │ ├── 5856_026.png │ ├── 5881_166.png │ ├── 5913_002.png │ ├── 5921_071.png │ ├── 5925_025.png │ ├── 5926_018.png │ ├── 5935_149.png │ ├── 5955_103.png │ ├── 5956_026.png │ ├── 5963_008.png │ ├── 5992_072.png │ ├── 6008_014.png │ ├── 6114_062.png │ ├── 6286_013.png │ ├── 6294_118.png │ ├── 6294_128.png │ ├── 6294_160.png │ ├── 6294_166.png │ ├── 6346_024.png │ ├── 6347_112.png │ ├── 6415_046.png │ ├── 6504_018.png │ ├── 6546_011.png │ ├── 6546_016.png │ ├── 6575_007.png │ ├── 6577_020.png │ ├── 6578_052.png │ ├── 6580_018.png │ ├── 6580_091.png │ ├── 6580_125.png │ ├── 6581_209.png │ ├── 6583_055.png │ ├── 6585_484.png │ ├── 6585_486.png │ ├── 6585_593.png │ ├── 6790_011.png │ ├── 6814_006.png │ ├── 8005_125.png │ ├── 8013_494.png │ ├── 8024_015.png │ ├── 8025_067.png │ ├── 8031_232.png │ ├── 8095_046.png │ ├── 8209_010.png │ ├── 8232_013.png │ ├── 9500_023.png │ ├── 9500_034.png │ ├── 9501_022.png │ ├── 9501_032.png │ ├── 9501_043.png │ ├── 9502_055.png │ ├── 9502_061.png │ ├── 9503_001.png │ ├── 9503_027.png │ ├── 9503_031.png │ ├── 9504_025.png │ ├── 9506_017.png │ ├── 9507_030.png │ ├── 9508_056.png │ ├── 9508_064.png │ ├── 9508_065.png │ ├── 9508_067.png │ ├── 9509_040.png │ ├── 9509_042.png │ ├── 9509_045.png │ ├── 9510_031.png │ ├── 9510_037.png │ ├── 9510_041.png │ ├── 9511_031.png │ ├── 9512_043.png │ ├── 9513_030.png │ ├── 9514_046.png │ ├── 9514_049.png │ ├── 9515_022.png │ ├── 9515_023.png │ ├── 9515_024.png │ ├── 9516_001.png │ ├── 9516_041.png │ ├── 9517_037.png │ ├── 9517_045.png │ ├── 9518_015.png │ ├── 9518_018.png │ ├── 9519_034.png │ ├── 9519_045.png │ ├── 9519_063.png │ ├── 9520_037.png │ ├── 9520_041.png │ ├── 9521_052.png │ ├── 9522_041.png │ ├── 9522_055.png │ ├── 9523_038.png │ ├── 9525_037.png │ ├── 9525_043.png │ ├── 9526_017.png │ ├── 9526_028.png │ ├── 9527_018.png │ ├── 9527_024.png │ ├── 9528_043.png │ ├── 9528_061.png │ ├── 9529_050.png │ ├── 9530_051.png │ ├── 9531_070.png │ ├── 9531_073.png │ ├── 9532_146.png │ ├── 9533_038.png │ ├── 9533_039.png │ ├── 9534_001.png │ ├── 9534_028.png │ ├── 9534_058.png │ ├── 9535_027.png │ ├── 9536_010.png │ ├── 9536_036.png │ ├── 9537_032.png │ ├── 9537_038.png │ ├── 9538_012.png │ ├── 9538_018.png │ ├── 9538_022.png │ ├── 9538_031.png │ ├── 9540_040.png │ ├── 9541_023.png │ ├── 9541_028.png │ ├── 9542_025.png │ ├── 9542_032.png │ ├── 9545_026.png │ ├── 9545_036.png │ ├── 9546_030.png │ ├── 9548_031.png │ ├── 9548_034.png │ ├── 9548_035.png │ ├── 9549_009.png │ ├── 9549_023.png │ ├── 9549_030.png │ ├── 9550_050.png │ ├── 9550_056.png │ ├── 9551_062.png │ ├── 9552_001.png │ ├── 9552_038.png │ ├── 9552_039.png │ ├── 9553_023.png │ ├── 9554_028.png │ ├── 9555_015.png │ ├── 9556_021.png │ ├── 9557_020.png │ ├── 9557_035.png │ ├── 9560_036.png │ ├── 9560_038.png │ ├── 9561_026.png │ ├── 9561_044.png │ ├── 9561_049.png │ ├── 9562_024.png │ ├── 9562_053.png │ ├── 9563_061.png │ ├── 9563_080.png │ ├── 9563_104.png │ ├── 9565_029.png │ ├── 9565_038.png │ ├── 9566_029.png │ ├── 9566_031.png │ ├── 9566_032.png │ ├── 9567_052.png │ ├── 9567_077.png │ ├── 9568_033.png │ ├── 9568_063.png │ ├── 9569_017.png │ ├── 9569_024.png │ ├── 9569_026.png │ ├── 9569_027.png │ ├── 9570_027.png │ ├── 9570_030.png │ ├── 9571_020.png │ ├── 9572_040.png │ ├── 9573_040.png │ └── 9574_049.png ├── pdf │ └── SEC_Symantec_Form_10-k.pdf ├── train.csv ├── train │ └── sample.png ├── val.csv └── val │ └── sample.png ├── predict_new_image.txt ├── preprocess.py ├── start_training.sh └── 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Data inside `job_dir` will be stored under 3 | # `run_name`. 4 | run_name: table-area-detection-0.1 5 | # Base directory in which model checkpoints & summaries (for Tensorboard) will 6 | # be saved. 7 | job_dir: jobs/ 8 | save_checkpoint_secs: 10 9 | save_summaries_secs: 10 10 | 11 | # Number of epochs (complete dataset batches) to run. 12 | num_epochs: 10 13 | 14 | dataset: 15 | type: object_detection 16 | # From which directory to read the dataset. 17 | dir: tfdata/classes-table/ 18 | image_preprocessing: 19 | min_size: 600 20 | max_size: 1024 21 | data_augmentation: 22 | - flip: 23 | left_right: True 24 | up_down: True 25 | prob: 0.5 26 | 27 | model: 28 | type: fasterrcnn 29 | network: 30 | # Total number of classes to predict. 31 | num_classes: 1 32 | -------------------------------------------------------------------------------- /config100.yml: -------------------------------------------------------------------------------- 1 | train: 2 | run_name: table-area-detection-0.1 3 | job_dir: jobs/ 4 | save_checkpoint_secs: 10 5 | save_summaries_secs: 10 6 | num_epochs: 100 7 | dataset: 8 | type: object_detection 9 | dir: tfdata/ 10 | image_preprocessing: 11 | min_size: 600 12 | max_size: 1024 13 | data_augmentation: 14 | - 15 | flip: {left_right: true, up_down: true, prob: 0.5} 16 | model: 17 | type: fasterrcnn 18 | network: 19 | num_classes: 1 -------------------------------------------------------------------------------- /create_checkpoint.sh: -------------------------------------------------------------------------------- 1 | lumi checkpoint create config.yml 2 | -------------------------------------------------------------------------------- /create_records.sh: -------------------------------------------------------------------------------- 1 | lumi dataset transform --type csv --data-dir data/ --output-dir tfdata/ --split train --split val --only-classes=table 2 | -------------------------------------------------------------------------------- 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6294_128.png,603,2440,1873,3060,table 289 | 6294_160.png,193,636,2093,2136,table 290 | 6294_166.png,266,233,2960,1336,table 291 | 6346_024.png,453,806,2180,2423,table 292 | 6347_112.png,106,844,2492,1614,table 293 | 6415_046.png,203,260,2390,2786,table 294 | 6546_011.png,220,663,2766,1646,table 295 | 6546_016.png,100,676,2990,1310,table 296 | 6575_007.png,175,335,2345,2985,table 297 | 6577_020.png,370,486,3086,2196,table 298 | 6578_052.png,253,440,2240,2880,table 299 | 6580_018.png,243,460,2220,960,table 300 | 6580_091.png,306,400,2263,1560,table 301 | 6580_125.png,300,406,2983,1830,table 302 | 6581_209.png,86,523,2406,1803,table 303 | 6583_055.png,176,390,2216,1120,table 304 | 6583_055.png,183,1576,2206,2220,table 305 | 6585_484.png,273,390,3000,2110,table 306 | 6585_486.png,276,363,2993,2100,table 307 | 6585_593.png,310,430,3043,2140,table 308 | 6790_011.png,553,490,2680,1840,table 309 | 6814_006.png,100,380,2036,2713,table 310 | 8005_125.png,955,188,1471,982,table 311 | 8024_015.png,198,628,1932,1606,table 312 | 8025_067.png,1313,1123,2286,2966,table 313 | 8031_232.png,830,1421,1520,2060,table 314 | 8095_046.png,1564,1806,2204,3038,table 315 | 8209_010.png,752,646,1816,902,table 316 | 8232_013.png,156,2090,984,2418,table 317 | 9500_023.png,107,1370,1234,1594,table 318 | 9500_034.png,88,274,1248,742,table 319 | 9500_034.png,1230,1130,2374,1528,table 320 | 9501_022.png,216,2608,1068,3030,table 321 | 9501_032.png,1187,754,2307,1168,table 322 | 9501_032.png,1182,1962,2321,2274,table 323 | 9501_043.png,44,812,1124,991,table 324 | 9501_043.png,61,1278,1131,1570,table 325 | 9501_043.png,64,2712,1140,3154,table 326 | 9501_043.png,1154,502,2221,1081,table 327 | 9502_055.png,608,620,2314,938,table 328 | 9502_055.png,612,1252,2316,1460,table 329 | 9502_055.png,604,1536,2322,2214,table 330 | 9502_061.png,120,313,2270,2580,table 331 | 9503_001.png,200,786,2176,2676,table 332 | 9503_027.png,73,530,2346,2490,table 333 | 9504_025.png,75,1115,1110,1487,table 334 | 9506_017.png,1018,490,2231,861,table 335 | 9507_030.png,276,313,2313,2703,table 336 | 9508_056.png,196,416,2453,2353,table 337 | 9508_064.png,1345,425,2431,1122,table 338 | 9508_065.png,146,620,2376,986,table 339 | 9508_065.png,113,1160,2366,2076,table 340 | 9508_065.png,146,2326,2356,2630,table 341 | 9508_067.png,156,542,1258,1072,table 342 | 9508_067.png,156,1324,1232,2162,table 343 | 9508_067.png,1278,2084,2376,2680,table 344 | 9509_040.png,1300,2180,2410,2540,table 345 | 9509_042.png,120,1414,1238,1832,table 346 | 9509_042.png,1292,336,2410,754,table 347 | 9509_045.png,102,534,1226,1130,table 348 | 9509_045.png,114,2072,1202,2326,table 349 | 9509_045.png,94,2498,1200,2960,table 350 | 9510_031.png,88,2068,1178,2496,table 351 | 9510_031.png,90,2616,1176,2948,table 352 | 9510_031.png,1234,2080,2320,2394,table 353 | 9510_031.png,1208,2502,2294,2648,table 354 | 9510_037.png,78,1436,1190,2036,table 355 | 9510_037.png,90,2312,1184,2920,table 356 | 9510_037.png,1232,586,2322,928,table 357 | 9510_041.png,1240,470,2336,972,table 358 | 9510_041.png,1216,1078,2338,1664,table 359 | 9511_031.png,136,1934,1194,2184,table 360 | 9512_043.png,53,206,2310,2743,table 361 | 9513_030.png,226,706,2420,1450,table 362 | 9513_030.png,223,1773,2420,2300,table 363 | 9514_046.png,1284,1624,2378,1952,table 364 | 9514_046.png,1276,2282,2378,2874,table 365 | 9515_022.png,134,242,1620,1398,table 366 | 9515_023.png,136,232,1616,1340,table 367 | 9515_024.png,142,320,844,574,table 368 | 9515_024.png,142,1390,1630,2696,table 369 | 9516_001.png,540,368,2002,1606,table 370 | 9516_041.png,100,480,2280,3175,table 371 | 9517_037.png,220,1650,2256,2122,table 372 | 9517_045.png,140,386,1758,2048,table 373 | 9518_015.png,34,1126,1082,1532,table 374 | 9518_015.png,1208,1494,2284,2176,table 375 | 9518_018.png,205,1022,1281,1325,table 376 | 9518_018.png,208,2502,1275,2825,table 377 | 9519_034.png,636,440,2526,2940,table 378 | 9519_045.png,576,1740,2444,2230,table 379 | 9519_063.png,450,533,2353,1776,table 380 | 9519_063.png,470,1942,2336,2680,table 381 | 9520_037.png,494,824,1518,1258,table 382 | 9520_041.png,470,152,1471,662,table 383 | 9520_041.png,470,764,1471,1298,table 384 | 9520_041.png,1487,157,2500,665,table 385 | 9520_041.png,1487,765,2507,1311,table 386 | 9520_041.png,472,1884,2512,2532,table 387 | 9521_052.png,736,618,2420,1896,table 388 | 9521_052.png,740,2062,2418,2710,table 389 | 9522_041.png,86,456,1090,1348,table 390 | 9522_041.png,78,1610,1082,2058,table 391 | 9522_041.png,1134,632,2170,1616,table 392 | 9522_055.png,40,283,963,2626,table 393 | 9522_055.png,1144,522,2220,928,table 394 | 9525_037.png,1250,2675,2410,2931,table 395 | 9525_043.png,54,1114,1208,1364,table 396 | 9525_043.png,48,1860,1240,2716,table 397 | 9525_043.png,1226,318,2426,1548,table 398 | 9526_017.png,845,2668,2224,3060,table 399 | 9526_028.png,124,312,1276,1964,table 400 | 9526_028.png,1294,458,2418,702,table 401 | 9526_028.png,1288,2374,2424,2724,table 402 | 9527_018.png,486,420,2363,2440,table 403 | 9527_024.png,500,434,2352,870,table 404 | 9527_024.png,502,2712,2346,3002,table 405 | 9528_043.png,240,1450,2192,2008,table 406 | 9528_043.png,246,2182,2204,2846,table 407 | 9528_061.png,276,914,2212,1186,table 408 | 9528_061.png,276,2108,2242,2576,table 409 | 9528_061.png,312,2698,1834,2958,table 410 | 9529_050.png,72,342,2042,1158,table 411 | 9529_050.png,108,1372,2052,1620,table 412 | 9529_050.png,104,2234,2040,2512,table 413 | 9530_051.png,90,470,2394,1682,table 414 | 9531_070.png,166,368,2328,1088,table 415 | 9531_070.png,148,1100,2340,1788,table 416 | 9531_073.png,50,260,2336,2876,table 417 | 9532_146.png,563,490,2440,2853,table 418 | 9533_038.png,1278,454,2326,1358,table 419 | 9533_038.png,1270,1774,2328,2368,table -------------------------------------------------------------------------------- /data/train/sample.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/the-black-knight-01/Table-Detection-using-Deep-Learning/4083e11a457b1ddbab918c770dff07940e4b5343/data/train/sample.png -------------------------------------------------------------------------------- /data/val.csv: -------------------------------------------------------------------------------- 1 | image_id,xmin,ymin,xmax,ymax,label 2 | 9533_039.png,60,396,1113,2420,table 3 | 9533_039.png,1143,1126,2240,2230,table 4 | 9534_001.png,196,378,2146,956,table 5 | 9534_001.png,184,1028,2160,1636,table 6 | 9534_028.png,642,1388,1944,1981,table 7 | 9535_027.png,136,552,1168,1008,table 8 | 9535_027.png,124,1022,1168,1458,table 9 | 9535_027.png,1246,446,2302,686,table 10 | 9535_027.png,1216,712,2282,1334,table 11 | 9535_027.png,1242,1474,2280,1850,table 12 | 9536_010.png,302,1360,1238,1632,table 13 | 9536_036.png,1272,2270,2392,2588,table 14 | 9537_032.png,264,2148,1370,2476,table 15 | 9537_038.png,256,650,1363,2986,table 16 | 9537_038.png,1393,653,2526,2236,table 17 | 9538_012.png,262,286,2264,1524,table 18 | 9538_018.png,274,1912,2252,2354,table 19 | 9538_022.png,230,273,2303,3023,table 20 | 9538_031.png,184,732,2142,1314,table 21 | 9540_040.png,548,1164,2496,1970,table 22 | 9540_040.png,560,2426,2390,3276,table 23 | 9541_023.png,83,483,2353,2163,table 24 | 9541_028.png,162,500,2406,1274,table 25 | 9541_028.png,148,1668,2392,2786,table 26 | 9542_025.png,380,420,2160,1910,table 27 | 9542_032.png,148,750,1886,2012,table 28 | 9545_026.png,690,380,2486,2063,table 29 | 9545_036.png,670,516,2490,2023,table 30 | 9545_036.png,693,2586,2496,3193,table 31 | 9546_030.png,203,370,2466,2313,table 32 | 9548_034.png,376,1058,2254,1462,table 33 | 9548_034.png,330,2034,2282,2542,table 34 | 9548_035.png,138,918,2098,1362,table 35 | 9548_035.png,152,1464,2104,1784,table 36 | 9548_035.png,154,1886,1934,2394,table 37 | 9549_009.png,1282,337,2302,597,table 38 | 9549_009.png,1278,688,2301,907,table 39 | 9549_023.png,193,340,2360,2920,table 40 | 9549_030.png,232,892,1270,1286,table 41 | 9549_030.png,236,1476,1276,2366,table 42 | 9549_030.png,1348,2120,2432,2948,table 43 | 9550_050.png,972,486,3024,800,table 44 | 9550_050.png,954,908,2734,1468,table 45 | 9550_050.png,970,1624,3054,1832,table 46 | 9550_056.png,203,383,3050,1873,table 47 | 9551_062.png,303,536,2263,2996,table 48 | 9552_001.png,812,488,2314,1900,table 49 | 9552_038.png,80,346,2386,2980,table 50 | 9552_039.png,76,380,2336,2700,table 51 | 9553_023.png,132,776,1206,1788,table 52 | 9553_023.png,138,2166,1202,3024,table 53 | 9554_028.png,176,680,2390,2623,table 54 | 9555_015.png,10,380,1786,1606,table 55 | 9555_015.png,10,1790,1783,2803,table 56 | 9556_021.png,126,1942,1174,2460,table 57 | 9556_021.png,1220,940,2282,1352,table 58 | 9556_021.png,1208,1370,2342,1872,table 59 | 9557_020.png,283,513,2163,2396,table 60 | 9557_035.png,310,810,2092,1528,table 61 | 9560_038.png,173,246,2330,2510,table 62 | 9561_026.png,158,1468,2252,2964,table 63 | 9561_044.png,168,456,2218,932,table 64 | 9561_044.png,168,1236,2222,1890,table 65 | 9561_049.png,124,854,2188,1564,table 66 | 9562_024.png,274,594,1300,817,table 67 | 9562_053.png,20,403,2350,2333,table 68 | 9563_061.png,36,528,2046,1234,table 69 | 9563_061.png,276,1868,1732,2126,table 70 | 9563_080.png,532,2438,2062,2886,table 71 | 9563_104.png,274,904,2318,2154,table 72 | 9565_029.png,50,273,2093,2903,table 73 | 9565_038.png,160,1475,1190,1992,table 74 | 9566_029.png,40,530,2216,2903,table 75 | 9566_031.png,30,536,2176,2094,table 76 | 9566_032.png,314,2212,1370,2742,table 77 | 9566_032.png,1396,1168,2452,1872,table 78 | 9567_052.png,202,284,1247,1005,table 79 | 9567_052.png,207,1420,1234,1791,table 80 | 9567_052.png,1281,282,2334,545,table 81 | 9567_052.png,192,1878,2338,3056,table 82 | 9567_077.png,158,330,2268,1630,table 83 | 9567_077.png,156,2338,1192,2942,table 84 | 9568_033.png,278,420,2372,1448,table 85 | 9568_033.png,268,2000,1308,2786,table 86 | 9568_063.png,262,406,2332,1804,table 87 | 9568_063.png,252,1866,2062,2966,table 88 | 9569_017.png,243,446,2156,2926,table 89 | 9569_024.png,490,446,2370,2286,table 90 | 9569_026.png,530,453,2350,2476,table 91 | 9569_027.png,460,450,2310,2760,table 92 | 9570_027.png,50,386,2386,2873,table 93 | 9570_030.png,160,2032,1278,2386,table 94 | 9570_030.png,1338,2082,2460,2328,table 95 | 9571_020.png,36,70,2490,500,table 96 | 9572_040.png,330,156,2440,2250,table 97 | 9573_040.png,210,706,1256,1042,table 98 | 9573_040.png,1282,420,2326,864,table 99 | 9573_040.png,202,1638,1232,2070,table 100 | 9573_040.png,1266,2392,2306,2698,table 101 | 9574_049.png,236,356,3063,1580,table -------------------------------------------------------------------------------- /data/val/sample.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/the-black-knight-01/Table-Detection-using-Deep-Learning/4083e11a457b1ddbab918c770dff07940e4b5343/data/val/sample.png -------------------------------------------------------------------------------- /predict_new_image.txt: -------------------------------------------------------------------------------- 1 | lumi predict --checkpoint c2155084dca6 data/val/9541_023.png 2 | -------------------------------------------------------------------------------- /preprocess.py: -------------------------------------------------------------------------------- 1 | 2 | import os 3 | import cv2 4 | import pandas as pd 5 | 6 | root_dir = os.getcwd() 7 | file_list = ['train.csv', 'val.csv'] 8 | image_source_dir = os.path.join(root_dir, 'data/images/') 9 | data_root = os.path.join(root_dir, 'data') 10 | for file in file_list: 11 | 12 | image_target_dir = os.path.join(data_root, file.split(".")[0]) 13 | 14 | if not os.path.exists(image_target_dir): 15 | os.mkdir(image_target_dir) 16 | 17 | # read list of image files to process from file 18 | image_list = pd.read_csv(os.path.join(data_root, file), header=None)[0] 19 | image_list = image_list[1:] 20 | print("Start preprocessing images") 21 | for image in image_list: 22 | # open image file 23 | img = cv2.imread(os.path.join(image_source_dir, image)) 24 | img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 25 | 26 | # perform transformations on image 27 | b = cv2.distanceTransform(img, distanceType=cv2.DIST_L2, maskSize=5) 28 | g = cv2.distanceTransform(img, distanceType=cv2.DIST_L1, maskSize=5) 29 | r = cv2.distanceTransform(img, distanceType=cv2.DIST_C, maskSize=5) 30 | 31 | # merge the transformed channels back to an image 32 | transformed_image = cv2.merge((b, g, r)) 33 | target_file = os.path.join(image_target_dir, image) 34 | print("Writing target file {}".format(target_file)) 35 | cv2.imwrite(target_file, transformed_image) 36 | print("Finished preprocessing images") 37 | 38 | -------------------------------------------------------------------------------- /start_training.sh: -------------------------------------------------------------------------------- 1 | lumi train -c config.yml 2 | -------------------------------------------------------------------------------- /start_webbserver.sh: -------------------------------------------------------------------------------- 1 | lumi server web --checkpoint c2155084dca6 2 | --------------------------------------------------------------------------------