{"cells":[{"metadata":{"trusted":true},"cell_type":"code","source":"\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.model_selection import train_test_split\nimport numpy as np\nimport cv2 \nimport matplotlib.pyplot as plt\nimport os\nfrom sklearn.metrics import accuracy_score\nfrom os.path import join, basename\nfrom os import listdir\nfrom PIL import Image \nfrom PIL import ImageFilter\nfrom sklearn.svm import LinearSVC, SVC\nfrom sklearn.metrics import accuracy_score\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"dataset_train = \"../input/2019-fall-pr-project/train/train/\"\nprint(listdir(dataset_train))\ntrain_imgs = [join(dataset_train,f) for f in listdir(dataset_train)] #상대경로\n\nresize=[]\n\nfor i in train_imgs:\n  img = cv2.imread(i)\n  img1=cv2.resize(img,dsize=(32,32))\n  b = np.reshape(img1, (1,np.product(img1.shape)))\n  resize.append(b[0,:])\n\nlabels=[] \nprint(os.listdir(dataset_train))\nfor i in os.listdir(dataset_train):\n  if 'dog' in i:\n    labels.append('1')\n  else:\n    labels.append('0')\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"resize1, subtestImage, label1, subtestLabel = train_test_split(resize, labels, test_size=0.25, random_state=42)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"clf=LinearSVC(C=1E5,class_weight='balanced')\nclf.fit(subtestImage[0:4000], subtestLabel[0:4000])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"label3=clf.predict(resize1[0:500])\naccuracy_score(label1[0:500],label3)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"\ndataset_test = \"../input/2019-fall-pr-project/test1/test1/\"\ntest_imgs = [join(dataset_test,f) for f in listdir(dataset_test)]\ntest_size=[]\nfor i in test_imgs:\n  img = cv2.imread(i)\n  img1=cv2.resize(img,dsize=(32,32)) #32,32 사이즈로 변경\n  b = np.reshape(img1, (1,np.product(img1.shape))) #1d vector로 변경\n  test_size.append(b[0,:])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"result=clf.predict(test_size)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd\ns = pd.Series(result)\ndata={'id':range(1,5001),'label':s}\ndf = pd.DataFrame(data)\ndf.index += 1 \ndf.to_csv('results-yk-v2.csv',index=True,index_label='id', header=True,columns=[\"label\"])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":1}