{"cells":[{"metadata":{},"cell_type":"markdown","source":"#Image Generator"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport os\nprint(len(os.listdir(\"../input/train\")))\n\n# Any results you write to the current directory are saved as output.","execution_count":1,"outputs":[{"output_type":"stream","text":"25001\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"os.mkdir(\"modifiedtrain\")\nos.mkdir(\"modifiedtrain/cat\")\nos.mkdir(\"modifiedtrain/dog\")","execution_count":2,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"os.listdir(\"modifiedtrain\")","execution_count":3,"outputs":[{"output_type":"execute_result","execution_count":3,"data":{"text/plain":"['dog', 'cat']"},"metadata":{}}]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"from shutil import copyfile\nfor file in os.listdir(\"../input/train\"):\n    name=file.split('.')[0]\n    filename=\"../input/train/\"+file\n    if name=='cat':\n        copyfile(filename,\"modifiedtrain/cat/\"+file)\n    elif name=='dog':\n        copyfile(filename,\"modifiedtrain/dog/\"+file)\n    \n    ","execution_count":5,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"os.listdir(\"modifiedtrain/dog/\")","execution_count":6,"outputs":[{"output_type":"execute_result","execution_count":6,"data":{"text/plain":"['dog.11162.jpg',\n 'dog.153.jpg',\n 'dog.9017.jpg',\n 'dog.3569.jpg',\n 'dog.7438.jpg',\n 'dog.3379.jpg',\n 'dog.9716.jpg',\n 'dog.1524.jpg',\n 'dog.3537.jpg',\n 'dog.4659.jpg',\n 'dog.5185.jpg',\n 'dog.5646.jpg',\n 'dog.5172.jpg',\n 'dog.7081.jpg',\n 'dog.8583.jpg',\n 'dog.7058.jpg',\n 'dog.9828.jpg',\n 'dog.7640.jpg',\n 'dog.11460.jpg',\n 'dog.1717.jpg',\n 'dog.1852.jpg',\n 'dog.9527.jpg',\n 'dog.8686.jpg',\n 'dog.2560.jpg',\n 'dog.1238.jpg',\n 'dog.735.jpg',\n 'dog.2767.jpg',\n 'dog.7785.jpg',\n 'dog.11957.jpg',\n 'dog.3258.jpg',\n 'dog.10373.jpg',\n 'dog.11188.jpg',\n 'dog.900.jpg',\n 'dog.12337.jpg',\n 'dog.567.jpg',\n 'dog.1622.jpg',\n 'dog.8623.jpg',\n 'dog.7190.jpg',\n 'dog.5093.jpg',\n 'dog.2125.jpg',\n 'dog.10125.jpg',\n 'dog.11580.jpg',\n 'dog.6358.jpg',\n 'dog.631.jpg',\n 'dog.7209.jpg',\n 'dog.7128.jpg',\n 'dog.11832.jpg',\n 'dog.7520.jpg',\n 'dog.3648.jpg',\n 'dog.10468.jpg',\n 'dog.11747.jpg',\n 'dog.1514.jpg',\n 'dog.7621.jpg',\n 'dog.3292.jpg',\n 'dog.3716.jpg',\n 'dog.12237.jpg',\n 'dog.10929.jpg',\n 'dog.1488.jpg',\n 'dog.2109.jpg',\n 'dog.1343.jpg',\n 'dog.5509.jpg',\n 'dog.2315.jpg',\n 'dog.9851.jpg',\n 'dog.12102.jpg',\n 'dog.8187.jpg',\n 'dog.604.jpg',\n 'dog.4115.jpg',\n 'dog.10502.jpg',\n 'dog.3699.jpg',\n 'dog.2695.jpg',\n 'dog.5266.jpg',\n 'dog.360.jpg',\n 'dog.6803.jpg',\n 'dog.1481.jpg',\n 'dog.1871.jpg',\n 'dog.9636.jpg',\n 'dog.4627.jpg',\n 'dog.9285.jpg',\n 'dog.11676.jpg',\n 'dog.8455.jpg',\n 'dog.807.jpg',\n 'dog.11559.jpg',\n 'dog.4155.jpg',\n 'dog.4124.jpg',\n 'dog.9143.jpg',\n 'dog.7353.jpg',\n 'dog.9583.jpg',\n 'dog.3099.jpg',\n 'dog.710.jpg',\n 'dog.4975.jpg',\n 'dog.9531.jpg',\n 'dog.4503.jpg',\n 'dog.2794.jpg',\n 'dog.11373.jpg',\n 'dog.1118.jpg',\n 'dog.198.jpg',\n 'dog.2625.jpg',\n 'dog.5202.jpg',\n 'dog.9034.jpg',\n 'dog.12062.jpg',\n 'dog.2914.jpg',\n 'dog.11809.jpg',\n 'dog.643.jpg',\n 'dog.7567.jpg',\n 'dog.3597.jpg',\n 'dog.4406.jpg',\n 'dog.11806.jpg',\n 'dog.5276.jpg',\n 'dog.5178.jpg',\n 'dog.9648.jpg',\n 'dog.12494.jpg',\n 'dog.6045.jpg',\n 'dog.10072.jpg',\n 'dog.10063.jpg',\n 'dog.1289.jpg',\n 'dog.7481.jpg',\n 'dog.6848.jpg',\n 'dog.11231.jpg',\n 'dog.3048.jpg',\n 'dog.10171.jpg',\n 'dog.7395.jpg',\n 'dog.11624.jpg',\n 'dog.6927.jpg',\n 'dog.120.jpg',\n 'dog.4832.jpg',\n 'dog.1820.jpg',\n 'dog.1117.jpg',\n 'dog.2292.jpg',\n 'dog.6833.jpg',\n 'dog.10119.jpg',\n 'dog.6649.jpg',\n 'dog.278.jpg',\n 'dog.2134.jpg',\n 'dog.10098.jpg',\n 'dog.1917.jpg',\n 'dog.348.jpg',\n 'dog.10697.jpg',\n 'dog.7923.jpg',\n 'dog.6390.jpg',\n 'dog.11965.jpg',\n 'dog.10246.jpg',\n 'dog.11660.jpg',\n 'dog.2615.jpg',\n 'dog.7519.jpg',\n 'dog.2713.jpg',\n 'dog.13.jpg',\n 'dog.311.jpg',\n 'dog.2704.jpg',\n 'dog.3183.jpg',\n 'dog.1974.jpg',\n 'dog.3555.jpg',\n 'dog.9120.jpg',\n 'dog.8355.jpg',\n 'dog.9102.jpg',\n 'dog.213.jpg',\n 'dog.3577.jpg',\n 'dog.4772.jpg',\n 'dog.12360.jpg',\n 'dog.7090.jpg',\n 'dog.4289.jpg',\n 'dog.11052.jpg',\n 'dog.7865.jpg',\n 'dog.8113.jpg',\n 'dog.5935.jpg',\n 'dog.1127.jpg',\n 'dog.11248.jpg',\n 'dog.10937.jpg',\n 'dog.4933.jpg',\n 'dog.3135.jpg',\n 'dog.787.jpg',\n 'dog.1893.jpg',\n 'dog.11128.jpg',\n 'dog.3651.jpg',\n 'dog.11501.jpg',\n 'dog.3954.jpg',\n 'dog.6137.jpg',\n 'dog.5865.jpg',\n 'dog.6258.jpg',\n 'dog.8562.jpg',\n 'dog.8594.jpg',\n 'dog.7965.jpg',\n 'dog.5999.jpg',\n 'dog.1810.jpg',\n 'dog.9886.jpg',\n 'dog.1090.jpg',\n 'dog.910.jpg',\n 'dog.5550.jpg',\n 'dog.4805.jpg',\n 'dog.1302.jpg',\n 'dog.20.jpg',\n 'dog.7347.jpg',\n 'dog.3557.jpg',\n 'dog.9785.jpg',\n 'dog.10290.jpg',\n 'dog.960.jpg',\n 'dog.10348.jpg',\n 'dog.11793.jpg',\n 'dog.4825.jpg',\n 'dog.6234.jpg',\n 'dog.12266.jpg',\n 'dog.67.jpg',\n 'dog.8062.jpg',\n 'dog.5046.jpg',\n 'dog.6632.jpg',\n 'dog.5878.jpg',\n 'dog.5004.jpg',\n 'dog.7524.jpg',\n 'dog.8318.jpg',\n 'dog.527.jpg',\n 'dog.1444.jpg',\n 'dog.1948.jpg',\n 'dog.6454.jpg',\n 'dog.12179.jpg',\n 'dog.5944.jpg',\n 'dog.3218.jpg',\n 'dog.4724.jpg',\n 'dog.4363.jpg',\n 'dog.7374.jpg',\n 'dog.3520.jpg',\n 'dog.9772.jpg',\n 'dog.8894.jpg',\n 'dog.4273.jpg',\n 'dog.10759.jpg',\n 'dog.1403.jpg',\n 'dog.5416.jpg',\n 'dog.2907.jpg',\n 'dog.2481.jpg',\n 'dog.4541.jpg',\n 'dog.482.jpg',\n 'dog.10136.jpg',\n 'dog.3300.jpg',\n 'dog.10695.jpg',\n 'dog.10487.jpg',\n 'dog.3540.jpg',\n 'dog.4224.jpg',\n 'dog.7587.jpg',\n 'dog.9680.jpg',\n 'dog.11407.jpg',\n 'dog.9602.jpg',\n 'dog.1983.jpg',\n 'dog.58.jpg',\n 'dog.7928.jpg',\n 'dog.4276.jpg',\n 'dog.11376.jpg',\n 'dog.3460.jpg',\n 'dog.334.jpg',\n 'dog.11436.jpg',\n 'dog.498.jpg',\n 'dog.3580.jpg',\n 'dog.4217.jpg',\n 'dog.9320.jpg',\n 'dog.3397.jpg',\n 'dog.7564.jpg',\n 'dog.7359.jpg',\n 'dog.1635.jpg',\n 'dog.6379.jpg',\n 'dog.10906.jpg',\n 'dog.757.jpg',\n 'dog.3508.jpg',\n 'dog.3321.jpg',\n 'dog.11834.jpg',\n 'dog.10132.jpg',\n 'dog.3344.jpg',\n 'dog.11496.jpg',\n 'dog.9326.jpg',\n 'dog.11946.jpg',\n 'dog.11589.jpg',\n 'dog.1879.jpg',\n 'dog.493.jpg',\n 'dog.10554.jpg',\n 'dog.2780.jpg',\n 'dog.10010.jpg',\n 'dog.0.jpg',\n 'dog.3260.jpg',\n 'dog.10826.jpg',\n 'dog.7218.jpg',\n 'dog.2462.jpg',\n 'dog.12034.jpg',\n 'dog.737.jpg',\n 'dog.10299.jpg',\n 'dog.11159.jpg',\n 'dog.5177.jpg',\n 'dog.6129.jpg',\n 'dog.4407.jpg',\n 'dog.7539.jpg',\n 'dog.8221.jpg',\n 'dog.9175.jpg',\n 'dog.8842.jpg',\n 'dog.3587.jpg',\n 'dog.2309.jpg',\n 'dog.6844.jpg',\n 'dog.10910.jpg',\n 'dog.1684.jpg',\n 'dog.1052.jpg',\n 'dog.5715.jpg',\n 'dog.3804.jpg',\n 'dog.9751.jpg',\n 'dog.518.jpg',\n 'dog.302.jpg',\n 'dog.6267.jpg',\n 'dog.511.jpg',\n 'dog.1442.jpg',\n 'dog.10330.jpg',\n 'dog.345.jpg',\n 'dog.4680.jpg',\n 'dog.1273.jpg',\n 'dog.7718.jpg',\n 'dog.8061.jpg',\n 'dog.369.jpg',\n 'dog.8163.jpg',\n 'dog.4275.jpg',\n 'dog.8534.jpg',\n 'dog.9390.jpg',\n 'dog.4697.jpg',\n 'dog.11005.jpg',\n 'dog.9290.jpg',\n 'dog.3757.jpg',\n 'dog.6008.jpg',\n 'dog.5344.jpg',\n 'dog.952.jpg',\n 'dog.11082.jpg',\n 'dog.3604.jpg',\n 'dog.6599.jpg',\n 'dog.2232.jpg',\n 'dog.821.jpg',\n 'dog.284.jpg',\n 'dog.4102.jpg',\n 'dog.4223.jpg',\n 'dog.3697.jpg',\n 'dog.6075.jpg',\n 'dog.8871.jpg',\n 'dog.8606.jpg',\n 'dog.9835.jpg',\n 'dog.9797.jpg',\n 'dog.3910.jpg',\n 'dog.4181.jpg',\n 'dog.4199.jpg',\n 'dog.10617.jpg',\n 'dog.12014.jpg',\n 'dog.12082.jpg',\n 'dog.7502.jpg',\n 'dog.10643.jpg',\n 'dog.10305.jpg',\n 'dog.3339.jpg',\n 'dog.3780.jpg',\n 'dog.8814.jpg',\n 'dog.4349.jpg',\n 'dog.9377.jpg',\n 'dog.564.jpg',\n 'dog.9673.jpg',\n 'dog.12180.jpg',\n 'dog.4057.jpg',\n 'dog.6326.jpg',\n 'dog.3659.jpg',\n 'dog.6767.jpg',\n 'dog.138.jpg',\n 'dog.10326.jpg',\n 'dog.4386.jpg',\n 'dog.179.jpg',\n 'dog.7938.jpg',\n 'dog.3600.jpg',\n 'dog.12328.jpg',\n 'dog.4490.jpg',\n 'dog.7379.jpg',\n 'dog.4372.jpg',\n 'dog.11581.jpg',\n 'dog.4298.jpg',\n 'dog.2229.jpg',\n 'dog.4453.jpg',\n 'dog.3898.jpg',\n 'dog.2167.jpg',\n 'dog.6347.jpg',\n 'dog.3408.jpg',\n 'dog.423.jpg',\n 'dog.7245.jpg',\n 'dog.3117.jpg',\n 'dog.9337.jpg',\n 'dog.7446.jpg',\n 'dog.8903.jpg',\n 'dog.9062.jpg',\n 'dog.1775.jpg',\n 'dog.4388.jpg',\n 'dog.5053.jpg',\n 'dog.8679.jpg',\n 'dog.10660.jpg',\n 'dog.3454.jpg',\n 'dog.2314.jpg',\n 'dog.6253.jpg',\n 'dog.2474.jpg',\n 'dog.12155.jpg',\n 'dog.1969.jpg',\n 'dog.1922.jpg',\n 'dog.9694.jpg',\n 'dog.12460.jpg',\n 'dog.11124.jpg',\n 'dog.3978.jpg',\n 'dog.570.jpg',\n 'dog.11863.jpg',\n 'dog.5362.jpg',\n 'dog.11693.jpg',\n 'dog.11518.jpg',\n 'dog.1477.jpg',\n 'dog.583.jpg',\n 'dog.8694.jpg',\n 'dog.4424.jpg',\n 'dog.10927.jpg',\n 'dog.6346.jpg',\n 'dog.7941.jpg',\n 'dog.5909.jpg',\n 'dog.7234.jpg',\n 'dog.5962.jpg',\n 'dog.12493.jpg',\n 'dog.8958.jpg',\n 'dog.6388.jpg',\n 'dog.9211.jpg',\n 'dog.7850.jpg',\n 'dog.11263.jpg',\n 'dog.6481.jpg',\n 'dog.11130.jpg',\n 'dog.9854.jpg',\n 'dog.3470.jpg',\n 'dog.7588.jpg',\n 'dog.1424.jpg',\n 'dog.5838.jpg',\n 'dog.11221.jpg',\n 'dog.11926.jpg',\n 'dog.3603.jpg',\n 'dog.2047.jpg',\n 'dog.5231.jpg',\n 'dog.8513.jpg',\n 'dog.11542.jpg',\n 'dog.4233.jpg',\n 'dog.10539.jpg',\n 'dog.3669.jpg',\n 'dog.4582.jpg',\n 'dog.1686.jpg',\n 'dog.8267.jpg',\n 'dog.11779.jpg',\n 'dog.5723.jpg',\n 'dog.8760.jpg',\n 'dog.8644.jpg',\n 'dog.6185.jpg',\n 'dog.5561.jpg',\n 'dog.2284.jpg',\n 'dog.10141.jpg',\n 'dog.4487.jpg',\n 'dog.10438.jpg',\n 'dog.7737.jpg',\n 'dog.7816.jpg',\n 'dog.12024.jpg',\n 'dog.4661.jpg',\n 'dog.11566.jpg',\n 'dog.11103.jpg',\n 'dog.91.jpg',\n 'dog.4588.jpg',\n 'dog.3527.jpg',\n 'dog.6801.jpg',\n 'dog.6782.jpg',\n 'dog.9223.jpg',\n 'dog.4063.jpg',\n 'dog.5831.jpg',\n 'dog.8374.jpg',\n 'dog.1101.jpg',\n 'dog.5204.jpg',\n 'dog.10350.jpg',\n 'dog.8071.jpg',\n 'dog.12047.jpg',\n 'dog.8859.jpg',\n 'dog.11341.jpg',\n 'dog.7300.jpg',\n 'dog.4896.jpg',\n 'dog.2374.jpg',\n 'dog.7007.jpg',\n 'dog.4720.jpg',\n 'dog.613.jpg',\n 'dog.5163.jpg',\n 'dog.7339.jpg',\n 'dog.8077.jpg',\n 'dog.11271.jpg',\n 'dog.11882.jpg',\n 'dog.12317.jpg',\n 'dog.3798.jpg',\n 'dog.11499.jpg',\n 'dog.2724.jpg',\n 'dog.10528.jpg',\n 'dog.1278.jpg',\n 'dog.10587.jpg',\n 'dog.12052.jpg',\n 'dog.12105.jpg',\n 'dog.10868.jpg',\n 'dog.3026.jpg',\n 'dog.6028.jpg',\n 'dog.5674.jpg',\n 'dog.2866.jpg',\n 'dog.6957.jpg',\n 'dog.12116.jpg',\n 'dog.5390.jpg',\n 'dog.2751.jpg',\n 'dog.1697.jpg',\n 'dog.1548.jpg',\n 'dog.11776.jpg',\n 'dog.4327.jpg',\n 'dog.670.jpg',\n 'dog.12178.jpg',\n 'dog.1600.jpg',\n 'dog.10211.jpg',\n 'dog.421.jpg',\n 'dog.2643.jpg',\n 'dog.2386.jpg',\n 'dog.3185.jpg',\n 'dog.10421.jpg',\n 'dog.12020.jpg',\n 'dog.9181.jpg',\n 'dog.8883.jpg',\n 'dog.6865.jpg',\n 'dog.12314.jpg',\n 'dog.1578.jpg',\n 'dog.1625.jpg',\n 'dog.4271.jpg',\n 'dog.5055.jpg',\n 'dog.3106.jpg',\n 'dog.273.jpg',\n 'dog.11584.jpg',\n 'dog.8975.jpg',\n 'dog.10472.jpg',\n 'dog.12498.jpg',\n 'dog.1103.jpg',\n 'dog.6161.jpg',\n 'dog.943.jpg',\n 'dog.10285.jpg',\n 'dog.7414.jpg',\n 'dog.340.jpg',\n 'dog.3161.jpg',\n 'dog.10292.jpg',\n 'dog.8343.jpg',\n 'dog.7242.jpg',\n 'dog.3911.jpg',\n 'dog.12469.jpg',\n 'dog.4846.jpg',\n 'dog.3970.jpg',\n 'dog.10687.jpg',\n 'dog.9007.jpg',\n 'dog.6021.jpg',\n 'dog.2354.jpg',\n 'dog.346.jpg',\n 'dog.7531.jpg',\n 'dog.8646.jpg',\n 'dog.3094.jpg',\n 'dog.11608.jpg',\n 'dog.4729.jpg',\n 'dog.7284.jpg',\n 'dog.8649.jpg',\n 'dog.4861.jpg',\n 'dog.5716.jpg',\n 'dog.10951.jpg',\n 'dog.11698.jpg',\n 'dog.8652.jpg',\n 'dog.6825.jpg',\n 'dog.277.jpg',\n 'dog.5920.jpg',\n 'dog.5320.jpg',\n 'dog.9812.jpg',\n 'dog.7108.jpg',\n 'dog.9415.jpg',\n 'dog.12288.jpg',\n 'dog.266.jpg',\n 'dog.6729.jpg',\n 'dog.8546.jpg',\n 'dog.4116.jpg',\n 'dog.1794.jpg',\n 'dog.6013.jpg',\n 'dog.10900.jpg',\n 'dog.6845.jpg',\n 'dog.4779.jpg',\n 'dog.10269.jpg',\n 'dog.771.jpg',\n 'dog.969.jpg',\n 'dog.455.jpg',\n 'dog.2353.jpg',\n 'dog.5931.jpg',\n 'dog.289.jpg',\n 'dog.7676.jpg',\n 'dog.2376.jpg',\n 'dog.12466.jpg',\n 'dog.1281.jpg',\n 'dog.6993.jpg',\n 'dog.11792.jpg',\n 'dog.4006.jpg',\n 'dog.870.jpg',\n 'dog.8412.jpg',\n 'dog.8995.jpg',\n 'dog.4796.jpg',\n 'dog.4038.jpg',\n 'dog.1658.jpg',\n 'dog.5726.jpg',\n 'dog.840.jpg',\n 'dog.9774.jpg',\n 'dog.8676.jpg',\n 'dog.8847.jpg',\n 'dog.2911.jpg',\n 'dog.7091.jpg',\n 'dog.6777.jpg',\n 'dog.6063.jpg',\n 'dog.11040.jpg',\n 'dog.6626.jpg',\n 'dog.5462.jpg',\n 'dog.12434.jpg',\n 'dog.3850.jpg',\n 'dog.1593.jpg',\n 'dog.8122.jpg',\n 'dog.9214.jpg',\n 'dog.8848.jpg',\n 'dog.6385.jpg',\n 'dog.11959.jpg',\n 'dog.11163.jpg',\n 'dog.1680.jpg',\n 'dog.9291.jpg',\n 'dog.8541.jpg',\n 'dog.203.jpg',\n 'dog.2558.jpg',\n 'dog.4921.jpg',\n 'dog.2832.jpg',\n 'dog.6140.jpg',\n 'dog.8033.jpg',\n 'dog.7376.jpg',\n 'dog.263.jpg',\n 'dog.1831.jpg',\n 'dog.10591.jpg',\n 'dog.5332.jpg',\n 'dog.5707.jpg',\n 'dog.6710.jpg',\n 'dog.1392.jpg',\n 'dog.8202.jpg',\n 'dog.9576.jpg',\n 'dog.9833.jpg',\n 'dog.12120.jpg',\n 'dog.3929.jpg',\n 'dog.4999.jpg',\n 'dog.6759.jpg',\n 'dog.6861.jpg',\n 'dog.79.jpg',\n 'dog.7902.jpg',\n 'dog.1153.jpg',\n 'dog.7847.jpg',\n 'dog.1888.jpg',\n 'dog.12041.jpg',\n 'dog.5488.jpg',\n 'dog.1355.jpg',\n 'dog.3652.jpg',\n 'dog.10223.jpg',\n 'dog.800.jpg',\n 'dog.10589.jpg',\n 'dog.4348.jpg',\n 'dog.2707.jpg',\n 'dog.10029.jpg',\n 'dog.6190.jpg',\n 'dog.10336.jpg',\n 'dog.2423.jpg',\n 'dog.10308.jpg',\n 'dog.8681.jpg',\n 'dog.78.jpg',\n 'dog.2784.jpg',\n 'dog.4628.jpg',\n 'dog.12282.jpg',\n 'dog.3006.jpg',\n 'dog.1125.jpg',\n 'dog.2427.jpg',\n 'dog.1093.jpg',\n 'dog.2804.jpg',\n 'dog.4457.jpg',\n 'dog.10995.jpg',\n 'dog.1003.jpg',\n 'dog.4412.jpg',\n 'dog.9059.jpg',\n 'dog.6269.jpg',\n 'dog.3511.jpg',\n 'dog.3633.jpg',\n 'dog.9037.jpg',\n 'dog.9537.jpg',\n 'dog.294.jpg',\n 'dog.11636.jpg',\n 'dog.8837.jpg',\n 'dog.8219.jpg',\n 'dog.6071.jpg',\n 'dog.5428.jpg',\n 'dog.11861.jpg',\n 'dog.7615.jpg',\n 'dog.847.jpg',\n 'dog.1316.jpg',\n 'dog.5520.jpg',\n 'dog.9116.jpg',\n 'dog.7326.jpg',\n 'dog.343.jpg',\n 'dog.6706.jpg',\n 'dog.9305.jpg',\n 'dog.11685.jpg',\n 'dog.4017.jpg',\n 'dog.9323.jpg',\n 'dog.11821.jpg',\n 'dog.5599.jpg',\n 'dog.9948.jpg',\n 'dog.1306.jpg',\n 'dog.1755.jpg',\n 'dog.7062.jpg',\n 'dog.6399.jpg',\n 'dog.1962.jpg',\n 'dog.8030.jpg',\n 'dog.6444.jpg',\n 'dog.10128.jpg',\n 'dog.7643.jpg',\n 'dog.7912.jpg',\n 'dog.4676.jpg',\n 'dog.11548.jpg',\n 'dog.12419.jpg',\n 'dog.1279.jpg',\n 'dog.2052.jpg',\n 'dog.11415.jpg',\n 'dog.2728.jpg',\n 'dog.11168.jpg',\n 'dog.9422.jpg',\n 'dog.4685.jpg',\n 'dog.7719.jpg',\n 'dog.2811.jpg',\n 'dog.4868.jpg',\n 'dog.8586.jpg',\n 'dog.11564.jpg',\n 'dog.5830.jpg',\n 'dog.1947.jpg',\n 'dog.10391.jpg',\n 'dog.7792.jpg',\n 'dog.5124.jpg',\n 'dog.10730.jpg',\n 'dog.9541.jpg',\n 'dog.9551.jpg',\n 'dog.1223.jpg',\n 'dog.11421.jpg',\n 'dog.6695.jpg',\n 'dog.558.jpg',\n 'dog.1379.jpg',\n 'dog.5983.jpg',\n 'dog.3549.jpg',\n 'dog.10068.jpg',\n 'dog.188.jpg',\n 'dog.2340.jpg',\n 'dog.8618.jpg',\n 'dog.10796.jpg',\n 'dog.1818.jpg',\n 'dog.11713.jpg',\n 'dog.8376.jpg',\n 'dog.8162.jpg',\n 'dog.4998.jpg',\n 'dog.2566.jpg',\n 'dog.2418.jpg',\n 'dog.4820.jpg',\n 'dog.10448.jpg',\n 'dog.8448.jpg',\n 'dog.590.jpg',\n 'dog.10752.jpg',\n 'dog.12303.jpg',\n 'dog.6605.jpg',\n 'dog.11876.jpg',\n 'dog.2910.jpg',\n 'dog.12326.jpg',\n 'dog.9032.jpg',\n 'dog.1073.jpg',\n 'dog.4694.jpg',\n 'dog.9808.jpg',\n 'dog.5203.jpg',\n 'dog.11973.jpg',\n 'dog.8738.jpg',\n 'dog.4324.jpg',\n 'dog.11102.jpg',\n 'dog.2543.jpg',\n 'dog.5840.jpg',\n 'dog.9505.jpg',\n 'dog.11242.jpg',\n 'dog.6643.jpg',\n 'dog.2488.jpg',\n 'dog.6340.jpg',\n 'dog.10926.jpg',\n 'dog.10328.jpg',\n 'dog.5417.jpg',\n 'dog.4574.jpg',\n 'dog.9273.jpg',\n 'dog.8962.jpg',\n 'dog.2648.jpg',\n 'dog.3753.jpg',\n 'dog.7698.jpg',\n 'dog.2394.jpg',\n 'dog.4392.jpg',\n 'dog.7181.jpg',\n 'dog.9843.jpg',\n 'dog.11778.jpg',\n 'dog.9352.jpg',\n 'dog.342.jpg',\n 'dog.8039.jpg',\n 'dog.7506.jpg',\n 'dog.6620.jpg',\n 'dog.7144.jpg',\n 'dog.10946.jpg',\n 'dog.9440.jpg',\n 'dog.2628.jpg',\n 'dog.5934.jpg',\n 'dog.5282.jpg',\n 'dog.210.jpg',\n 'dog.12028.jpg',\n 'dog.5739.jpg',\n 'dog.11810.jpg',\n 'dog.6728.jpg',\n 'dog.9569.jpg',\n 'dog.8121.jpg',\n 'dog.11280.jpg',\n 'dog.8124.jpg',\n 'dog.2344.jpg',\n 'dog.10772.jpg',\n 'dog.10002.jpg',\n 'dog.8131.jpg',\n 'dog.10352.jpg',\n 'dog.5355.jpg',\n 'dog.9095.jpg',\n 'dog.9857.jpg',\n 'dog.6596.jpg',\n 'dog.6837.jpg',\n 'dog.9234.jpg',\n 'dog.7375.jpg',\n 'dog.10865.jpg',\n 'dog.10624.jpg',\n 'dog.12262.jpg',\n 'dog.387.jpg',\n 'dog.10514.jpg',\n 'dog.9038.jpg',\n 'dog.1261.jpg',\n 'dog.267.jpg',\n 'dog.1374.jpg',\n 'dog.1340.jpg',\n 'dog.10652.jpg',\n 'dog.10521.jpg',\n 'dog.7306.jpg',\n 'dog.10720.jpg',\n 'dog.7499.jpg',\n 'dog.2959.jpg',\n 'dog.374.jpg',\n 'dog.1581.jpg',\n 'dog.4204.jpg',\n 'dog.12331.jpg',\n 'dog.6856.jpg',\n 'dog.6449.jpg',\n 'dog.824.jpg',\n 'dog.8957.jpg',\n 'dog.8479.jpg',\n 'dog.6301.jpg',\n 'dog.3890.jpg',\n 'dog.5127.jpg',\n 'dog.10719.jpg',\n 'dog.11712.jpg',\n 'dog.8642.jpg',\n 'dog.3462.jpg',\n 'dog.9123.jpg',\n 'dog.2480.jpg',\n 'dog.1806.jpg',\n 'dog.5262.jpg',\n 'dog.5499.jpg',\n 'dog.8252.jpg',\n 'dog.7778.jpg',\n 'dog.5192.jpg',\n 'dog.10339.jpg',\n 'dog.4488.jpg',\n 'dog.9500.jpg',\n 'dog.10709.jpg',\n 'dog.5353.jpg',\n 'dog.7982.jpg',\n 'dog.62.jpg',\n 'dog.2960.jpg',\n 'dog.494.jpg',\n 'dog.11357.jpg',\n 'dog.9061.jpg',\n 'dog.3742.jpg',\n 'dog.9661.jpg',\n 'dog.9414.jpg',\n 'dog.752.jpg',\n 'dog.6394.jpg',\n 'dog.8426.jpg',\n 'dog.4177.jpg',\n 'dog.3916.jpg',\n 'dog.28.jpg',\n 'dog.2516.jpg',\n 'dog.1688.jpg',\n 'dog.3119.jpg',\n 'dog.11085.jpg',\n 'dog.899.jpg',\n 'dog.1564.jpg',\n 'dog.8675.jpg',\n 'dog.10479.jpg',\n 'dog.4901.jpg',\n 'dog.8924.jpg',\n 'dog.3370.jpg',\n 'dog.11116.jpg',\n 'dog.632.jpg',\n 'dog.5785.jpg',\n 'dog.4249.jpg',\n 'dog.149.jpg',\n 'dog.5975.jpg',\n 'dog.7263.jpg',\n 'dog.6781.jpg',\n 'dog.11458.jpg',\n 'dog.5007.jpg',\n 'dog.8245.jpg',\n 'dog.11100.jpg',\n 'dog.808.jpg',\n 'dog.5972.jpg',\n 'dog.6215.jpg',\n 'dog.10009.jpg',\n 'dog.8056.jpg',\n 'dog.5003.jpg',\n 'dog.7572.jpg',\n 'dog.10255.jpg',\n 'dog.5100.jpg',\n 'dog.5496.jpg',\n 'dog.4478.jpg',\n 'dog.6033.jpg',\n 'dog.2600.jpg',\n 'dog.5414.jpg',\n 'dog.5596.jpg',\n 'dog.11115.jpg',\n 'dog.9679.jpg',\n 'dog.11129.jpg',\n 'dog.6527.jpg',\n 'dog.9162.jpg',\n 'dog.3545.jpg',\n 'dog.10893.jpg',\n 'dog.4926.jpg',\n 'dog.7314.jpg',\n 'dog.5482.jpg',\n 'dog.5357.jpg',\n 'dog.9357.jpg',\n 'dog.6117.jpg',\n 'dog.2249.jpg',\n 'dog.10678.jpg',\n 'dog.5670.jpg',\n 'dog.5562.jpg',\n 'dog.7271.jpg',\n 'dog.11642.jpg',\n 'dog.8865.jpg',\n 'dog.983.jpg',\n 'dog.1647.jpg',\n 'dog.3691.jpg',\n 'dog.9184.jpg',\n 'dog.3455.jpg',\n 'dog.6228.jpg',\n 'dog.10161.jpg',\n 'dog.11853.jpg',\n 'dog.5447.jpg',\n 'dog.2178.jpg',\n 'dog.1713.jpg',\n 'dog.3064.jpg',\n 'dog.10802.jpg',\n 'dog.8768.jpg',\n 'dog.11788.jpg',\n 'dog.9681.jpg',\n 'dog.11380.jpg',\n 'dog.6726.jpg',\n 'dog.4587.jpg',\n 'dog.3304.jpg',\n 'dog.7101.jpg',\n 'dog.7712.jpg',\n 'dog.6049.jpg',\n 'dog.11512.jpg',\n 'dog.7612.jpg',\n 'dog.7014.jpg',\n 'dog.11534.jpg',\n 'dog.5621.jpg',\n 'dog.3475.jpg',\n 'dog.4436.jpg',\n 'dog.4839.jpg',\n 'dog.2335.jpg',\n 'dog.7797.jpg',\n 'dog.2459.jpg',\n 'dog.11096.jpg',\n 'dog.2676.jpg',\n 'dog.4004.jpg',\n 'dog.2991.jpg',\n 'dog.9324.jpg',\n 'dog.7011.jpg',\n 'dog.4886.jpg',\n 'dog.9480.jpg',\n 'dog.1669.jpg',\n 'dog.8849.jpg',\n 'dog.12386.jpg',\n 'dog.10685.jpg',\n 'dog.6342.jpg',\n 'dog.6285.jpg',\n 'dog.10446.jpg',\n 'dog.3157.jpg',\n 'dog.4570.jpg',\n 'dog.696.jpg',\n 'dog.3376.jpg',\n 'dog.9758.jpg',\n 'dog.8466.jpg',\n 'dog.8651.jpg',\n 'dog.4675.jpg',\n ...]"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"%pylab inline\nimport matplotlib.pyplot as plt\nfrom PIL import Image\nimage = Image.open('modifiedtrain/dog/dog.411.jpg')\nplt.imshow(image)\nplt.show()","execution_count":7,"outputs":[{"output_type":"stream","text":"Populating the interactive namespace from numpy and matplotlib\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"import tensorflow as tf\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator","execution_count":8,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_datagen=ImageDataGenerator(rescale=1./255)\n","execution_count":9,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_generator=train_datagen.flow_from_directory(\"modifiedtrain/\",batch_size=20,target_size=(150,150),\n                                                  class_mode='binary')","execution_count":10,"outputs":[{"output_type":"stream","text":"Found 25000 images belonging to 2 classes.\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"model=tf.keras.models.Sequential([\n    tf.keras.layers.Conv2D(16,(3,3),activation='relu',input_shape=(150,150,3)),\n    tf.keras.layers.MaxPool2D(2,2),\n    tf.keras.layers.Conv2D(32,(3,3),activation='relu'),\n    tf.keras.layers.MaxPool2D(2,2),\n    tf.keras.layers.Conv2D(64,(3,3),activation='relu'),\n    tf.keras.layers.MaxPool2D(2,2),\n    tf.keras.layers.Flatten(),\n    tf.keras.layers.Dense(512,activation='relu'),\n    tf.keras.layers.Dense(1,activation='sigmoid')\n])","execution_count":11,"outputs":[{"output_type":"stream","text":"WARNING:tensorflow:From /opt/conda/lib/python3.6/site-packages/tensorflow/python/ops/resource_variable_ops.py:435: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\nInstructions for updating:\nColocations handled automatically by placer.\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"model.summary()","execution_count":12,"outputs":[{"output_type":"stream","text":"_________________________________________________________________\nLayer (type)                 Output Shape              Param #   \n=================================================================\nconv2d (Conv2D)              (None, 148, 148, 16)      448       \n_________________________________________________________________\nmax_pooling2d (MaxPooling2D) (None, 74, 74, 16)        0         \n_________________________________________________________________\nconv2d_1 (Conv2D)            (None, 72, 72, 32)        4640      \n_________________________________________________________________\nmax_pooling2d_1 (MaxPooling2 (None, 36, 36, 32)        0         \n_________________________________________________________________\nconv2d_2 (Conv2D)            (None, 34, 34, 64)        18496     \n_________________________________________________________________\nmax_pooling2d_2 (MaxPooling2 (None, 17, 17, 64)        0         \n_________________________________________________________________\nflatten (Flatten)            (None, 18496)             0         \n_________________________________________________________________\ndense (Dense)                (None, 512)               9470464   \n_________________________________________________________________\ndense_1 (Dense)              (None, 1)                 513       \n=================================================================\nTotal params: 9,494,561\nTrainable params: 9,494,561\nNon-trainable params: 0\n_________________________________________________________________\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from tensorflow.keras.optimizers import RMSprop\n\nmodel.compile(loss='binary_crossentropy',optimizer=RMSprop(lr=0.001),metrics=['accuracy'])","execution_count":13,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":""},{"metadata":{"trusted":true},"cell_type":"code","source":"history=model.fit_generator(train_generator,steps_per_epoch=100,epochs=1)","execution_count":14,"outputs":[{"output_type":"stream","text":"WARNING:tensorflow:From /opt/conda/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\nInstructions for updating:\nUse tf.cast instead.\n1250/1250 [==============================] - 126s 101ms/step - loss: 0.8280 - acc: 0.6989s - loss:  - ETA: 5s - loss: 0.8414 - \n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_datagen = ImageDataGenerator(\n      rescale=1./255,\n      rotation_range=40,\n      width_shift_range=0.2,\n      height_shift_range=0.2,\n      shear_range=0.2,\n      zoom_range=0.2,\n      horizontal_flip=True,\n      fill_mode='nearest')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_generator=train_datagen.flow_from_directory(\"modifiedtrain/\",batch_size=20,target_size=(150,150),\n                                                  class_mode='binary')","execution_count":19,"outputs":[{"output_type":"stream","text":"Found 25000 images belonging to 2 classes.\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"history=model.fit_generator(train_generator,steps_per_epoch=100,epochs=5)","execution_count":20,"outputs":[{"output_type":"stream","text":"Epoch 1/5\n","name":"stdout"},{"output_type":"error","ename":"ValueError","evalue":"Error when checking input: expected input_1 to have shape (256, 256, 3) but got array with shape (150, 150, 3)","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)","\u001b[0;32m<ipython-input-20-21217898722c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mhistory\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit_generator\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_generator\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0msteps_per_epoch\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mepochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py\u001b[0m in \u001b[0;36mfit_generator\u001b[0;34m(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)\u001b[0m\n\u001b[1;32m   1424\u001b[0m         \u001b[0muse_multiprocessing\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muse_multiprocessing\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1425\u001b[0m         \u001b[0mshuffle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mshuffle\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1426\u001b[0;31m         initial_epoch=initial_epoch)\n\u001b[0m\u001b[1;32m   1427\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1428\u001b[0m   def evaluate_generator(self,\n","\u001b[0;32m/opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/engine/training_generator.py\u001b[0m in \u001b[0;36mmodel_iteration\u001b[0;34m(model, data, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch, mode, batch_size, **kwargs)\u001b[0m\n\u001b[1;32m    189\u001b[0m       \u001b[0mprogbar\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_batch_begin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch_logs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    190\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 191\u001b[0;31m       \u001b[0mbatch_outs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbatch_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mbatch_data\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    192\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch_outs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    193\u001b[0m         \u001b[0mbatch_outs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mbatch_outs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py\u001b[0m in \u001b[0;36mtrain_on_batch\u001b[0;34m(self, x, y, sample_weight, class_weight, reset_metrics)\u001b[0m\n\u001b[1;32m   1173\u001b[0m     \u001b[0;31m# Validate and standardize user data.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1174\u001b[0m     x, y, sample_weights = self._standardize_user_data(\n\u001b[0;32m-> 1175\u001b[0;31m         x, y, sample_weight=sample_weight, class_weight=class_weight)\n\u001b[0m\u001b[1;32m   1176\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1177\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_eagerly\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py\u001b[0m in \u001b[0;36m_standardize_user_data\u001b[0;34m(self, x, y, sample_weight, class_weight, batch_size, check_steps, steps_name, steps, validation_split, shuffle)\u001b[0m\n\u001b[1;32m   2380\u001b[0m         \u001b[0mfeed_input_shapes\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2381\u001b[0m         \u001b[0mcheck_batch_axis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0;31m# Don't enforce the batch size.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2382\u001b[0;31m         exception_prefix='input')\n\u001b[0m\u001b[1;32m   2383\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2384\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0my\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/engine/training_utils.py\u001b[0m in \u001b[0;36mstandardize_input_data\u001b[0;34m(data, names, shapes, check_batch_axis, exception_prefix)\u001b[0m\n\u001b[1;32m    360\u001b[0m                 \u001b[0;34m'Error when checking '\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mexception_prefix\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m': expected '\u001b[0m \u001b[0;34m+\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    361\u001b[0m                 \u001b[0mnames\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m' to have shape '\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 362\u001b[0;31m                 ' but got array with shape ' + str(data_shape))\n\u001b[0m\u001b[1;32m    363\u001b[0m   \u001b[0;32mreturn\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    364\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: Error when checking input: expected input_1 to have shape (256, 256, 3) but got array with shape (150, 150, 3)"]}]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\n\nfrom tensorflow.keras import layers\nfrom tensorflow.keras import Model\n!wget --no-check-certificate \\\n    https://storage.googleapis.com/mledu-datasets/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5 \\\n    -O /tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5\n  \nfrom tensorflow.keras.applications.inception_v3 import InceptionV3\n\nlocal_weights_file = '/tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5'\n\npre_trained_model = InceptionV3(input_shape = (256, 256, 3), \n                                include_top = False, \n                                weights = None)\n\npre_trained_model.load_weights(local_weights_file)\n\nfor layer in pre_trained_model.layers:\n  layer.trainable = False\n  \n# pre_trained_model.summary()\n\nlast_layer = pre_trained_model.get_layer('mixed7')\nprint('last layer output shape: ', last_layer.output_shape)\nlast_output = last_layer.output","execution_count":15,"outputs":[{"output_type":"stream","text":"--2019-06-09 18:55:24--  https://storage.googleapis.com/mledu-datasets/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5\nResolving storage.googleapis.com (storage.googleapis.com)... 172.217.214.128, 2607:f8b0:4001:c05::80\nConnecting to storage.googleapis.com (storage.googleapis.com)|172.217.214.128|:443... connected.\nHTTP request sent, awaiting response... 200 OK\nLength: 87910968 (84M) [application/x-hdf]\nSaving to: ‘/tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5’\n\n/tmp/inception_v3_w 100%[===================>]  83.84M   115MB/s    in 0.7s    \n\n2019-06-09 18:55:25 (115 MB/s) - ‘/tmp/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5’ saved [87910968/87910968]\n\nlast layer output shape:  (None, 14, 14, 768)\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from tensorflow.keras.optimizers import RMSprop\n\n# Flatten the output layer to 1 dimension\nx = layers.Flatten()(last_output)\n# Add a fully connected layer with 1,024 hidden units and ReLU activation\nx = layers.Dense(1024, activation='relu')(x)\n# Add a dropout rate of 0.2\nx = layers.Dropout(0.2)(x)                  \n# Add a final sigmoid layer for classification\nx = layers.Dense  (1, activation='sigmoid')(x)           \n\nmodel = Model( pre_trained_model.input, x) \n\nmodel.compile(optimizer = RMSprop(lr=0.0001), \n              loss = 'binary_crossentropy', \n              metrics = ['acc'])","execution_count":16,"outputs":[{"output_type":"stream","text":"WARNING:tensorflow:From /opt/conda/lib/python3.6/site-packages/tensorflow/python/keras/layers/core.py:143: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\nInstructions for updating:\nPlease use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"from tensorflow.keras.preprocessing.image import ImageDataGenerator\ntrain_datagen = ImageDataGenerator(\n      rescale=1./255,\n      rotation_range=40,\n      width_shift_range=0.2,\n      height_shift_range=0.2,\n      shear_range=0.2,\n      zoom_range=0.2,\n      horizontal_flip=True,\n      fill_mode='nearest')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_generator=train_datagen.flow_from_directory(\"modifiedtrain/\",batch_size=20,target_size=(256,256),\n                                                  class_mode='binary')","execution_count":21,"outputs":[{"output_type":"stream","text":"Found 25000 images belonging to 2 classes.\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"history=model.fit_generator(train_generator,steps_per_epoch=100,epochs=1)","execution_count":22,"outputs":[{"output_type":"stream","text":"1250/1250 [==============================] - 173s 138ms/step - loss: 0.1857 - acc: 0.9509\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"model.save('model.h5')","execution_count":23,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import matplotlib.pyplot as plt\nacc = history.history['acc']\nloss = history.history['loss']\nepochs = range(len(acc))\n\nplt.plot(epochs, acc, 'r', label='Training accuracy')\nplt.legend(loc=0)\nplt.figure()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"plt.plot(epochs, loss, 'b', label='Training loss')\nplt.legend(loc=0)\nplt.figure()","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}