{"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_minor":4,"nbformat":4,"cells":[{"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\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 read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-03-26T10:06:41.676853Z","iopub.execute_input":"2023-03-26T10:06:41.677206Z","iopub.status.idle":"2023-03-26T10:06:41.687268Z","shell.execute_reply.started":"2023-03-26T10:06:41.677178Z","shell.execute_reply":"2023-03-26T10:06:41.684700Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"TEST1_DIR = 'test1'\nTRAIN_DIR = 'train'\nINPUT_DIR = '../input/dogs-vs-cats'\nOUTPUT_DIR = '/output/'","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:06:41.689918Z","iopub.execute_input":"2023-03-26T10:06:41.690676Z","iopub.status.idle":"2023-03-26T10:06:41.709244Z","shell.execute_reply.started":"2023-03-26T10:06:41.690632Z","shell.execute_reply":"2023-03-26T10:06:41.706972Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import zipfile\n\nzip_files = ['test1', 'train']\n\nfor zip_file in zip_files:\n    with zipfile.ZipFile(\"../input/dogs-vs-cats/{}.zip\".format(zip_file),\"r\") as z:\n        z.extractall(\".\")\n        print(\"{} unzipped\".format(zip_file))","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:06:41.713220Z","iopub.execute_input":"2023-03-26T10:06:41.713798Z","iopub.status.idle":"2023-03-26T10:06:55.210472Z","shell.execute_reply.started":"2023-03-26T10:06:41.713760Z","shell.execute_reply":"2023-03-26T10:06:55.209564Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"file_names = os.listdir(TRAIN_DIR)\nprint('There are {} number of images in directory.'.format(len(file_names)))","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:06:55.211713Z","iopub.execute_input":"2023-03-26T10:06:55.212993Z","iopub.status.idle":"2023-03-26T10:06:55.230590Z","shell.execute_reply.started":"2023-03-26T10:06:55.212931Z","shell.execute_reply":"2023-03-26T10:06:55.229012Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def to_dataframe(file_names):\n    files, labels = list(), list()\n    for file in file_names:\n        files.append(file)\n        labels.append(file[:3])\n    df = pd.DataFrame({'filename':files, 'label':labels})\n    return df\n\ndf = to_dataframe(file_names)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:06:55.231732Z","iopub.execute_input":"2023-03-26T10:06:55.231976Z","iopub.status.idle":"2023-03-26T10:06:55.252658Z","shell.execute_reply.started":"2023-03-26T10:06:55.231952Z","shell.execute_reply":"2023-03-26T10:06:55.250715Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df.head()","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:06:55.254317Z","iopub.execute_input":"2023-03-26T10:06:55.254781Z","iopub.status.idle":"2023-03-26T10:06:55.281529Z","shell.execute_reply.started":"2023-03-26T10:06:55.254742Z","shell.execute_reply":"2023-03-26T10:06:55.280190Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"cat = [file for file in file_names if file[:3]=='cat'] # cat images\nprint(\"Images for cat =\",len(cat))\ndog = [file for file in file_names if file[:3]=='dog'] # dog images\nprint(\"Images for dog =\",len(dog))","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:06:55.284533Z","iopub.execute_input":"2023-03-26T10:06:55.284891Z","iopub.status.idle":"2023-03-26T10:06:55.297903Z","shell.execute_reply.started":"2023-03-26T10:06:55.284860Z","shell.execute_reply":"2023-03-26T10:06:55.296872Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import cv2 \nimport matplotlib.pyplot as plt\nimport matplotlib.image as img\nimport random\n\nplt.figure(figsize = (16,8))\nindex = random.randint(1,12000)\nfor i, c in enumerate(range(index, index + 5), start=1):\n    im = img.imread('./train/'+cat[c])\n    plt.subplot(2,5,i)\n    plt.imshow(im)\n    \nfor i, c in enumerate(range(index,index + 5), start=6):\n    im = img.imread('./train/'+dog[c])\n    plt.subplot(2,5,i)\n    plt.imshow(im)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:06:55.299288Z","iopub.execute_input":"2023-03-26T10:06:55.300013Z","iopub.status.idle":"2023-03-26T10:06:56.855829Z","shell.execute_reply.started":"2023-03-26T10:06:55.299944Z","shell.execute_reply":"2023-03-26T10:06:56.854909Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Resizing Images\n","metadata":{}},{"cell_type":"code","source":"from PIL import Image, ImageFilter, ImageEnhance\nresized_images=[]\nfor file in file_names:\n    img=Image.open('./train/'+file)\n    resized_images.append(img.resize((64,64)))\n    \nfig, ax = plt.subplots(1, 2, figsize=(15, 5));\nimg=Image.open('./train/'+file_names[0])\nax[0].imshow(img)\nax[1].imshow(resized_images[0])","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:06:56.860144Z","iopub.execute_input":"2023-03-26T10:06:56.860918Z","iopub.status.idle":"2023-03-26T10:08:23.827664Z","shell.execute_reply.started":"2023-03-26T10:06:56.860826Z","shell.execute_reply":"2023-03-26T10:08:23.825874Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Convert images to grey scale\n","metadata":{}},{"cell_type":"code","source":"fig, ax = plt.subplots(1, 2, figsize=(15, 5));\n\nimg=resized_images[25]\nax[0].imshow(img);\n\ngrey_scale_img = img.convert('LA')\nax[1].imshow(grey_scale_img);","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:08:23.828860Z","iopub.execute_input":"2023-03-26T10:08:23.829140Z","iopub.status.idle":"2023-03-26T10:08:24.140727Z","shell.execute_reply.started":"2023-03-26T10:08:23.829113Z","shell.execute_reply":"2023-03-26T10:08:24.139487Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Edge Detection","metadata":{}},{"cell_type":"code","source":"fig, ax = plt.subplots(1, 2, figsize=(15, 5));\n\nimg=resized_images[100]\nimage = img.convert(\"L\")\n\nimage = image.filter(ImageFilter.FIND_EDGES)\nax[0].imshow(img);\nax[1].imshow(image);","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:08:24.142791Z","iopub.execute_input":"2023-03-26T10:08:24.143191Z","iopub.status.idle":"2023-03-26T10:08:24.454885Z","shell.execute_reply.started":"2023-03-26T10:08:24.143164Z","shell.execute_reply":"2023-03-26T10:08:24.453302Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from numpy import asarray\nplt.figure(figsize=(15,15))\n# Read the original image\nimg=resized_images[105]\nimg=asarray(img)\n\n# Blur the image for better edge detection\nimg_blur = cv2.GaussianBlur(img, (3,3), 0) \n \n# Sobel Edge Detection\nsobelx = cv2.Sobel(src=img_blur, ddepth=cv2.CV_16S, dx=1, dy=0, ksize=3) # Sobel Edge Detection on the X axis\nsobely = cv2.Sobel(src=img_blur, ddepth=cv2.CV_16S, dx=0, dy=1, ksize=3) # Sobel Edge Detection on the Y axis\nsobelxy = cv2.Sobel(src=img_blur, ddepth=cv2.CV_16S, dx=1, dy=1, ksize=5) # Combined X and Y Sobel Edge Detection\n# Laplacian Edge detection\nlaplacian = cv2.Laplacian(img,ksize=3, ddepth=cv2.CV_16S)\n# Canny Edge Detection\ncanny = cv2.Canny(image=img_blur, threshold1=100, threshold2=200) # Canny Edge Detection\n\nplt.subplot(3,2,1),plt.imshow(img)\nplt.title('Original'), plt.xticks([]), plt.yticks([])\n\nplt.subplot(3,2,2),plt.imshow(laplacian)\nplt.title('Laplacian'), plt.xticks([]), plt.yticks([])\n\nplt.subplot(3,2,3),plt.imshow(canny)\nplt.title('Canny'), plt.xticks([]), plt.yticks([])\n\nplt.subplot(3,2,4),plt.imshow(sobelxy)\nplt.title('Sobel XY'), plt.xticks([]), plt.yticks([])\n\nplt.subplot(3,2,5),plt.imshow(sobelx)\nplt.title('Sobel X'), plt.xticks([]), plt.yticks([])\n\nplt.subplot(3,2,6),plt.imshow(sobely)\nplt.title('Sobel Y'), plt.xticks([]), plt.yticks([]);","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:08:24.456717Z","iopub.execute_input":"2023-03-26T10:08:24.457005Z","iopub.status.idle":"2023-03-26T10:08:25.051232Z","shell.execute_reply.started":"2023-03-26T10:08:24.456977Z","shell.execute_reply":"2023-03-26T10:08:25.049285Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Gaussian 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"}}},{"cell_type":"code","source":"img=resized_images[50]\nimg=asarray(img)\n\nblur = cv2.GaussianBlur(img,(5,5),0)\n\nfig, ax = plt.subplots(1, 2, figsize=(15, 5));\nplt.suptitle('RESULT', x=0.5, y=0.8)\nplt.tight_layout()\n\nax[0].set_title('ORIGINAL', fontsize=12)\nax[1].set_title('GAUSSIAN BLUR', fontsize=12)\n\nax[0].imshow(img);\nax[1].imshow(blur);","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:08:25.053360Z","iopub.execute_input":"2023-03-26T10:08:25.054593Z","iopub.status.idle":"2023-03-26T10:08:25.414221Z","shell.execute_reply.started":"2023-03-26T10:08:25.054541Z","shell.execute_reply":"2023-03-26T10:08:25.413218Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"filenames = os.listdir(TRAIN_DIR)\nfilenames[:5]\n","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:08:25.415525Z","iopub.execute_input":"2023-03-26T10:08:25.416562Z","iopub.status.idle":"2023-03-26T10:08:25.436801Z","shell.execute_reply.started":"2023-03-26T10:08:25.416489Z","shell.execute_reply":"2023-03-26T10:08:25.435062Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"labels = [1 if filename.startswith('dog') else 0 for filename in filenames]\nlabels[:5]","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:08:25.438213Z","iopub.execute_input":"2023-03-26T10:08:25.438476Z","iopub.status.idle":"2023-03-26T10:08:25.449728Z","shell.execute_reply.started":"2023-03-26T10:08:25.438443Z","shell.execute_reply":"2023-03-26T10:08:25.448377Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"df = pd.DataFrame({\n    'filename': filenames,\n    'category': labels\n})\n\ndf.head()\n","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:08:25.451699Z","iopub.execute_input":"2023-03-26T10:08:25.452013Z","iopub.status.idle":"2023-03-26T10:08:25.474113Z","shell.execute_reply.started":"2023-03-26T10:08:25.451983Z","shell.execute_reply":"2023-03-26T10:08:25.472941Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"ax = df.category.value_counts().plot.bar(color=['dodgerblue', 'slategray'])\nplt.title('Dogs and Cats images count')\nplt.xlabel('Dog = 1 - Cat = 0')\nplt.ylabel('samples count')\nax.set_xticklabels(['Dog', 'Cat'], rotation=0, fontsize=11)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:08:25.475901Z","iopub.execute_input":"2023-03-26T10:08:25.476146Z","iopub.status.idle":"2023-03-26T10:08:25.679020Z","shell.execute_reply.started":"2023-03-26T10:08:25.476114Z","shell.execute_reply":"2023-03-26T10:08:25.677111Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def load_images_from_dir(dir_location, filenames):\n    return [np.array(Image.open('{}/{}'.format(dir_location, filename)).resize((64, 64))) for filename in filenames]\n    \nimages = np.array(load_images_from_dir(TRAIN_DIR, filenames))\nimages.shape\n\n# Dimesion Reduction\n# Pixel * Pixel * RGB\nprint(images[0].shape)\nh, w, d = images[0].shape\nimages_resized = np.array([np.reshape(img, (w*h*d)) for img in images])\nimages_resized.shape","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:08:25.680724Z","iopub.execute_input":"2023-03-26T10:08:25.681325Z","iopub.status.idle":"2023-03-26T10:09:52.828682Z","shell.execute_reply.started":"2023-03-26T10:08:25.681289Z","shell.execute_reply":"2023-03-26T10:09:52.827488Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Dimesion Reduction\nprint(images[0].shape)\nh, w, d = images[0].shape\nimages_resized = np.array([np.reshape(img, (w*h*d)) for img in images])\nprint(images_resized.shape)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:09:52.829813Z","iopub.execute_input":"2023-03-26T10:09:52.830049Z","iopub.status.idle":"2023-03-26T10:09:52.967929Z","shell.execute_reply.started":"2023-03-26T10:09:52.830024Z","shell.execute_reply":"2023-03-26T10:09:52.966822Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"**Comparing classification models.**","metadata":{}},{"cell_type":"code","source":"from sklearn.tree import plot_tree\nfrom sklearn.preprocessing import PolynomialFeatures","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:09:52.969407Z","iopub.execute_input":"2023-03-26T10:09:52.969713Z","iopub.status.idle":"2023-03-26T10:09:53.124045Z","shell.execute_reply.started":"2023-03-26T10:09:52.969686Z","shell.execute_reply":"2023-03-26T10:09:53.121906Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Decision Tree","metadata":{}},{"cell_type":"code","source":"from sklearn.tree import DecisionTreeClassifier\ntree = DecisionTreeClassifier(max_depth=4)\ntree.fit(images_resized, labels)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:09:53.125933Z","iopub.execute_input":"2023-03-26T10:09:53.126831Z","iopub.status.idle":"2023-03-26T10:11:59.558997Z","shell.execute_reply.started":"2023-03-26T10:09:53.126802Z","shell.execute_reply":"2023-03-26T10:11:59.557740Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"tree.score(images_resized, labels)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:11:59.560845Z","iopub.execute_input":"2023-03-26T10:11:59.561283Z","iopub.status.idle":"2023-03-26T10:11:59.948326Z","shell.execute_reply.started":"2023-03-26T10:11:59.561246Z","shell.execute_reply":"2023-03-26T10:11:59.946816Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plot_tree(tree)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:11:59.950032Z","iopub.execute_input":"2023-03-26T10:11:59.950441Z","iopub.status.idle":"2023-03-26T10:12:01.345757Z","shell.execute_reply.started":"2023-03-26T10:11:59.950402Z","shell.execute_reply":"2023-03-26T10:12:01.344608Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Random Forest","metadata":{}},{"cell_type":"code","source":"from sklearn.ensemble import RandomForestClassifier\nforest = RandomForestClassifier()\nforest.fit(images_resized, labels)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:12:01.347035Z","iopub.execute_input":"2023-03-26T10:12:01.347324Z","iopub.status.idle":"2023-03-26T10:17:20.607086Z","shell.execute_reply.started":"2023-03-26T10:12:01.347296Z","shell.execute_reply":"2023-03-26T10:17:20.606073Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"forest.score(images_resized, labels)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:17:20.608686Z","iopub.execute_input":"2023-03-26T10:17:20.609378Z","iopub.status.idle":"2023-03-26T10:17:22.823203Z","shell.execute_reply.started":"2023-03-26T10:17:20.609338Z","shell.execute_reply":"2023-03-26T10:17:22.821816Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Testing","metadata":{}},{"cell_type":"code","source":"test_filenames = os.listdir(TEST1_DIR)\ntest_images = np.array(load_images_from_dir(TEST1_DIR, test_filenames))\ntest_images.shape","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:17:22.825751Z","iopub.execute_input":"2023-03-26T10:17:22.827442Z","iopub.status.idle":"2023-03-26T10:18:07.078082Z","shell.execute_reply.started":"2023-03-26T10:17:22.827380Z","shell.execute_reply":"2023-03-26T10:18:07.076398Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_images_resized = np.array([np.reshape(img, (w*h*d)) for img in test_images])\ntest_images_resized.shape","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:18:07.086003Z","iopub.execute_input":"2023-03-26T10:18:07.086385Z","iopub.status.idle":"2023-03-26T10:18:07.160820Z","shell.execute_reply.started":"2023-03-26T10:18:07.086353Z","shell.execute_reply":"2023-03-26T10:18:07.159550Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Comparing Predictions","metadata":{}},{"cell_type":"code","source":"filenames = os.listdir(TEST1_DIR)\ntest_labels = [1 if filename.startswith('dog') else 0 for filename in filenames]","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:18:07.161964Z","iopub.execute_input":"2023-03-26T10:18:07.162386Z","iopub.status.idle":"2023-03-26T10:18:07.177286Z","shell.execute_reply.started":"2023-03-26T10:18:07.162348Z","shell.execute_reply":"2023-03-26T10:18:07.175672Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"tree_predictions = tree.predict(test_images_resized)\n# tree_predictions\nfrom sklearn.metrics import accuracy_score\nscore = accuracy_score(tree_predictions, test_labels)\n# tree.score(tree_predictions, test_labels)\nprint(score)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:18:07.179203Z","iopub.execute_input":"2023-03-26T10:18:07.179528Z","iopub.status.idle":"2023-03-26T10:18:07.365947Z","shell.execute_reply.started":"2023-03-26T10:18:07.179475Z","shell.execute_reply":"2023-03-26T10:18:07.364020Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"forest_predictions = forest.predict(test_images_resized)\n\nscore = accuracy_score(forest_predictions, test_labels)\nscore","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:18:07.368159Z","iopub.execute_input":"2023-03-26T10:18:07.368593Z","iopub.status.idle":"2023-03-26T10:18:08.515300Z","shell.execute_reply.started":"2023-03-26T10:18:07.368555Z","shell.execute_reply":"2023-03-26T10:18:08.513583Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.neighbors import KNeighborsClassifier\n\nKNN = KNeighborsClassifier(n_neighbors= 5)\n","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:18:08.516770Z","iopub.execute_input":"2023-03-26T10:18:08.517072Z","iopub.status.idle":"2023-03-26T10:18:08.524627Z","shell.execute_reply.started":"2023-03-26T10:18:08.517044Z","shell.execute_reply":"2023-03-26T10:18:08.522389Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"KNN.fit(images_resized, labels)\nKNN.score(images_resized, labels)\n","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:18:08.526621Z","iopub.execute_input":"2023-03-26T10:18:08.526930Z","iopub.status.idle":"2023-03-26T10:21:28.995023Z","shell.execute_reply.started":"2023-03-26T10:18:08.526902Z","shell.execute_reply":"2023-03-26T10:21:28.993677Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"K_predictions = KNN.predict(test_images_resized)\n\nscore = accuracy_score(forest_predictions, test_labels)\nprint(score)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:21:28.997080Z","iopub.execute_input":"2023-03-26T10:21:28.997584Z","iopub.status.idle":"2023-03-26T10:23:08.255395Z","shell.execute_reply.started":"2023-03-26T10:21:28.997546Z","shell.execute_reply":"2023-03-26T10:23:08.253477Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.svm import SVC\nSVM = SVC(max_iter=2)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:23:08.257449Z","iopub.execute_input":"2023-03-26T10:23:08.258199Z","iopub.status.idle":"2023-03-26T10:23:08.263854Z","shell.execute_reply.started":"2023-03-26T10:23:08.258170Z","shell.execute_reply":"2023-03-26T10:23:08.262452Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"SVM.fit(images_resized, labels)\nSVM.score(images_resized, labels)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:23:08.265586Z","iopub.execute_input":"2023-03-26T10:23:08.266138Z","iopub.status.idle":"2023-03-26T10:23:14.046298Z","shell.execute_reply.started":"2023-03-26T10:23:08.266077Z","shell.execute_reply":"2023-03-26T10:23:14.045538Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"SVM_predictions = SVM.predict(test_images_resized)\n\nscore = accuracy_score(SVM_predictions, test_labels)\nprint(score)","metadata":{"execution":{"iopub.status.busy":"2023-03-26T10:25:09.239668Z","iopub.execute_input":"2023-03-26T10:25:09.239995Z","iopub.status.idle":"2023-03-26T10:25:11.170016Z","shell.execute_reply.started":"2023-03-26T10:25:09.239967Z","shell.execute_reply":"2023-03-26T10:25:11.169041Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def load_images_from_dir(dir_location, filenames):\n    return [np.array(Image.open('{}/{}'.format(dir_location, filename)).resize((64, 64))) for filename in filenames]\n\nimages = np.array(load_images_from_dir(TRAIN_DIR, filenames))\nimages.shape\n\n# Dimesion Reduction\n# Pixel * Pixel * RGB\nprint(images[0].shape)\nh, w, d = images[0].shape\nimages_resized = np.array([np.reshape(img, (w*h*d)) for img in images])\n","metadata":{},"execution_count":null,"outputs":[]}]}