{"cells":[{"metadata":{},"cell_type":"markdown","source":"> For 695"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"!pip install lap\n# Read the dataset description\nimport gzip\n# Read or generate p2h, a dictionary of image name to image id (picture to hash)\nimport pickle\nimport platform\nimport random\n# Suppress annoying stderr output when importing keras.\nimport sys\nfrom lap import lapjv\nfrom math import sqrt\n# Determine the size of each image\nfrom os.path import isfile\n\nimport keras\nimport matplotlib.pyplot as plt\nfrom matplotlib.pyplot import figure\nimport seaborn as sns\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image as pil_image\nfrom imagehash import phash\nfrom keras import backend as K\nfrom keras import regularizers\nfrom keras.engine.topology import Input\nfrom keras.layers import Activation, Add, BatchNormalization, Concatenate, Conv2D, Dense, Flatten, GlobalMaxPooling2D, \\\n    Lambda, MaxPooling2D, Reshape\nfrom keras.models import Model\nfrom keras.optimizers import Adam\nfrom keras.preprocessing.image import img_to_array\nfrom keras.utils import Sequence\nfrom pandas import read_csv\nfrom scipy.ndimage import affine_transform\nfrom tqdm import tqdm_notebook as tqdm\nimport time\n\n%matplotlib inline","execution_count":30,"outputs":[{"output_type":"stream","text":"Requirement already satisfied: lap in /opt/conda/lib/python3.6/site-packages (0.4.0)\n\u001b[33mYou are using pip version 19.0.3, however version 19.1.1 is available.\nYou should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"## Data Analysis for the set"},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nfig = plt.figure(figsize=(8, 8), dpi=100,facecolor='w', edgecolor='k')\ntrain_imgs = os.listdir(\"../input/humpback-whale-identification/train\")\nfor idx, img in enumerate(np.random.choice(train_imgs, 12)):\n    ax = fig.add_subplot(4, 20//5, idx+1, xticks=[], yticks=[])\n    im = pil_image.open(\"../input/humpback-whale-identification/train/\" + img)\n    plt.imshow(im)","execution_count":34,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 800x800 with 12 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# load image data\n#image name\ndf = pd.read_csv('../input/humpback-whale-identification/train.csv')\ndf.head()","execution_count":36,"outputs":[{"output_type":"execute_result","execution_count":36,"data":{"text/plain":"           Image         Id\n0  0000e88ab.jpg  w_f48451c\n1  0001f9222.jpg  w_c3d896a\n2  00029d126.jpg  w_20df2c5\n3  00050a15a.jpg  new_whale\n4  0005c1ef8.jpg  new_whale","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Image</th>\n      <th>Id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0000e88ab.jpg</td>\n      <td>w_f48451c</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0001f9222.jpg</td>\n      <td>w_c3d896a</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>00029d126.jpg</td>\n      <td>w_20df2c5</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>00050a15a.jpg</td>\n      <td>new_whale</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0005c1ef8.jpg</td>\n      <td>new_whale</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(f'Training examples: {len(df)}')\nprint(\"Unique whales: \",df['Id'].nunique()) # it includes new_whale as a separate type.\ntraining_pts_per_class = df.groupby('Id').size()\nprint(\"Min example a class can have: \",training_pts_per_class.min())\nprint(\"0.99 quantile: \",training_pts_per_class.quantile(0.99))\nprint(\"Max example a class can have: \\n\",training_pts_per_class.nlargest(2)) ","execution_count":37,"outputs":[{"output_type":"stream","text":"Training examples: 25361\nUnique whales:  5005\nMin example a class can have:  1\n0.99 quantile:  22.0\nMax example a class can have: \n Id\nnew_whale    9664\nw_23a388d      73\ndtype: int64\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"data = training_pts_per_class.copy()\ndata.loc[data > data.quantile(0.99)] = '22+'\nplt.figure(figsize=(15,10))\nsns.countplot(data.astype('str'))\nplt.title(\"#classes with different number of images\",fontsize=15)\nplt.show()","execution_count":38,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x720 with 1 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{},"cell_type":"markdown","source":"## Based on SNN with limited computing resources\n\nThe basic idea to solve the problem besed on SNN structure is in order to deal with highly unbanlenced dataset -- class 0 has more than a half of the pics in the whole dataset.\n\n\nWe are just using the pretrained weights from  [@martinpiotte](https://kaggle.com/martinpiotte).\n\nWe keep the basic structure of the *Siamese (pretrained) 0.822* kernel, but we change the input as the RGB channels. And for the epochs , we narrow its number to 20 in this kernel for every model, but we use the pretrained weight to do the warm initialization.\n\nWe also get generated bounding boxes from this kernel [here](https://www.kaggle.com/suicaokhoailang/generating-whale-bounding-boxes) which saved as a **.csv** instead of **pickle** for readability. "},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"TRAIN_DF = '../input/humpback-whale-identification/train.csv'\nSUB_Df = '../input/humpback-whale-identification/sample_submission.csv'\nTRAIN = '../input/humpback-whale-identification/train/'\nTEST = '../input/humpback-whale-identification/test/'\nP2H = '../input/metadata/p2h.pickle'\nP2SIZE = '../input/metadata/p2size.pickle'\nBB_DF = \"../input/metadata/bounding_boxes.csv\"\ntagged = dict([(p, w) for _, p, w in read_csv(TRAIN_DF).to_records()])\nsubmit = [p for _, p, _ in read_csv(SUB_Df).to_records()]\njoin = list(tagged.keys()) + submit","execution_count":3,"outputs":[]},{"metadata":{"_uuid":"7ee3c6a569bfe93b81bcbb97a40e3e78363c79d2"},"cell_type":"markdown","source":"## Duplicate image identification\n\nThis part was from the original kernel, seems like in the playground competition dulicated images was a real issue. I don't know the case about this one but I took one for the team and generated the results anyway. I'm such a nice chap."},{"metadata":{"trusted":true,"_uuid":"aa24819e1cc9ef98db60d218cc01e56f8d4e5046"},"cell_type":"code","source":"def expand_path(p):\n    if isfile(TRAIN + p):\n        return TRAIN + p\n    if isfile(TEST + p):\n        return TEST + p\n    return p\n\nif isfile(P2SIZE):\n    print(\"P2SIZE exists.\")\n    with open(P2SIZE, 'rb') as f:\n        p2size = pickle.load(f)\nelse:\n    p2size = {}\n    for p in tqdm(join):\n        size = pil_image.open(expand_path(p)).size\n        p2size[p] = size","execution_count":5,"outputs":[{"output_type":"stream","text":"P2SIZE exists.\n","name":"stdout"}]},{"metadata":{"trusted":true,"_uuid":"cdc36543403de9841a8af37f40c0044e17f6aa69"},"cell_type":"code","source":"def match(h1, h2):\n    for p1 in h2ps[h1]:\n        for p2 in h2ps[h2]:\n            i1 = pil_image.open(expand_path(p1))\n            i2 = pil_image.open(expand_path(p2))\n            if i1.mode != i2.mode or i1.size != i2.size: return False\n            a1 = np.array(i1)\n            a1 = a1 - a1.mean()\n            a1 = a1 / sqrt((a1 ** 2).mean())\n            a2 = np.array(i2)\n            a2 = a2 - a2.mean()\n            a2 = a2 / sqrt((a2 ** 2).mean())\n            a = ((a1 - a2) ** 2).mean()\n            if a > 0.1: return False\n    return True\n\n\nif isfile(P2H):\n    print(\"P2H exists.\")\n    with open(P2H, 'rb') as f:\n        p2h = pickle.load(f)\nelse:\n    # Compute phash for each image in the training and test set.\n    p2h = {}\n    for p in tqdm(join):\n        img = pil_image.open(expand_path(p))\n        h = phash(img)\n        p2h[p] = h\n\n    # Find all images associated with a given phash value.\n    h2ps = {}\n    for p, h in p2h.items():\n        if h not in h2ps: h2ps[h] = []\n        if p not in h2ps[h]: h2ps[h].append(p)\n\n    # Find all distinct phash values\n    hs = list(h2ps.keys())\n\n    # If the images are close enough, associate the two phash values (this is the slow part: n^2 algorithm)\n    h2h = {}\n    for i, h1 in enumerate(tqdm(hs)):\n        for h2 in hs[:i]:\n            if h1 - h2 <= 6 and match(h1, h2):\n                s1 = str(h1)\n                s2 = str(h2)\n                if s1 < s2: s1, s2 = s2, s1\n                h2h[s1] = s2\n\n    # Group together images with equivalent phash, and replace by string format of phash (faster and more readable)\n    for p, h in p2h.items():\n        h = str(h)\n        if h in h2h: h = h2h[h]\n        p2h[p] = h\n#     with open(P2H, 'wb') as f:\n#         pickle.dump(p2h, f)\n# For each image id, determine the list of pictures\nh2ps = {}\nfor p, h in p2h.items():\n    if h not in h2ps: h2ps[h] = []\n    if p not in h2ps[h]: h2ps[h].append(p)","execution_count":6,"outputs":[{"output_type":"stream","text":"P2H exists.\n","name":"stdout"}]},{"metadata":{"trusted":true,"_uuid":"62cc064dede5463c4f553da833020bee789f0de5"},"cell_type":"code","source":"def show_whale(imgs, per_row=2):\n    n = len(imgs)\n    rows = (n + per_row - 1) // per_row\n    cols = min(per_row, n)\n    fig, axes = plt.subplots(rows, cols, figsize=(24 // per_row * cols, 24 // per_row * rows))\n    for ax in axes.flatten(): ax.axis('off')\n    for i, (img, ax) in enumerate(zip(imgs, axes.flatten())): ax.imshow(img.convert('RGB'))\n        \n\ndef read_raw_image(p):\n    img = pil_image.open(expand_path(p))\n    return img","execution_count":7,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"87e36806009c7252803a2f49d7a071dbacfafda9"},"cell_type":"code","source":"# For each images id, select the prefered image\ndef prefer(ps):\n    if len(ps) == 1: return ps[0]\n    best_p = ps[0]\n    best_s = p2size[best_p]\n    for i in range(1, len(ps)):\n        p = ps[i]\n        s = p2size[p]\n        if s[0] * s[1] > best_s[0] * best_s[1]:  # Select the image with highest resolution\n            best_p = p\n            best_s = s\n    return best_p\n\nh2p = {}\nfor h, ps in h2ps.items():\n    h2p[h] = prefer(ps)\nlen(h2p), list(h2p.items())[:5]","execution_count":8,"outputs":[{"output_type":"execute_result","execution_count":8,"data":{"text/plain":"(33317,\n [('d26698c3271c757c', '0000e88ab.jpg'),\n  ('ba8cc231ad489b77', '0001f9222.jpg'),\n  ('bbcad234a52d0f0b', '00029d126.jpg'),\n  ('c09ae7dc09f33a29', '00050a15a.jpg'),\n  ('d02f65ba9f74a08a', '0005c1ef8.jpg')])"},"metadata":{}}]},{"metadata":{"trusted":true,"_uuid":"208f5d98270a8081f7024c52f4dad14791e48182"},"cell_type":"code","source":"# Read the bounding box data from the bounding box kernel (see reference above)\np2bb = pd.read_csv(BB_DF).set_index(\"Image\")\n\nold_stderr = sys.stderr\nsys.stderr = open('/dev/null' if platform.system() != 'Windows' else 'nul', 'w')\n\nsys.stderr = old_stderr\n\nimg_shape = (384, 384, 1)  # The image shape used by the model\nanisotropy = 2.15  # The horizontal compression ratio\ncrop_margin = 0.05  # The margin added around the bounding box to compensate for bounding box inaccuracy","execution_count":9,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"0b0629a511b86810a0106f23c5e25710242edf11"},"cell_type":"code","source":"def build_transform(rotation, shear, height_zoom, width_zoom, height_shift, width_shift):\n    \"\"\"\n    Build a transformation matrix with the specified characteristics.\n    \"\"\"\n    rotation = np.deg2rad(rotation)\n    shear = np.deg2rad(shear)\n    rotation_matrix = np.array(\n        [[np.cos(rotation), np.sin(rotation), 0], [-np.sin(rotation), np.cos(rotation), 0], [0, 0, 1]])\n    shift_matrix = np.array([[1, 0, height_shift], [0, 1, width_shift], [0, 0, 1]])\n    shear_matrix = np.array([[1, np.sin(shear), 0], [0, np.cos(shear), 0], [0, 0, 1]])\n    zoom_matrix = np.array([[1.0 / height_zoom, 0, 0], [0, 1.0 / width_zoom, 0], [0, 0, 1]])\n    shift_matrix = np.array([[1, 0, -height_shift], [0, 1, -width_shift], [0, 0, 1]])\n    return np.dot(np.dot(rotation_matrix, shear_matrix), np.dot(zoom_matrix, shift_matrix))","execution_count":10,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"a9bf0641d287366059c95fcbe0f5e2812f4bf236"},"cell_type":"code","source":"def read_cropped_image(p, augment):\n    \"\"\"\n    @param p : the name of the picture to read\n    @param augment: True/False if data augmentation should be performed\n    @return a numpy array with the transformed image\n    \"\"\"\n    # If an image id was given, convert to filename\n    if p in h2p:\n        p = h2p[p]\n    size_x, size_y = p2size[p]\n\n    # Determine the region of the original image we want to capture based on the bounding box.\n    row = p2bb.loc[p]\n    x0, y0, x1, y1 = row['x0'], row['y0'], row['x1'], row['y1']\n    dx = x1 - x0\n    dy = y1 - y0\n    x0 -= dx * crop_margin\n    x1 += dx * crop_margin + 1\n    y0 -= dy * crop_margin\n    y1 += dy * crop_margin + 1\n    if x0 < 0:\n        x0 = 0\n    if x1 > size_x:\n        x1 = size_x\n    if y0 < 0:\n        y0 = 0\n    if y1 > size_y:\n        y1 = size_y\n    dx = x1 - x0\n    dy = y1 - y0\n    if dx > dy * anisotropy:\n        dy = 0.5 * (dx / anisotropy - dy)\n        y0 -= dy\n        y1 += dy\n    else:\n        dx = 0.5 * (dy * anisotropy - dx)\n        x0 -= dx\n        x1 += dx\n\n    # Generate the transformation matrix\n    trans = np.array([[1, 0, -0.5 * img_shape[0]], [0, 1, -0.5 * img_shape[1]], [0, 0, 1]])\n    trans = np.dot(np.array([[(y1 - y0) / img_shape[0], 0, 0], [0, (x1 - x0) / img_shape[1], 0], [0, 0, 1]]), trans)\n    if augment:\n        trans = np.dot(build_transform(\n            random.uniform(-5, 5),\n            random.uniform(-5, 5),\n            random.uniform(0.8, 1.0),\n            random.uniform(0.8, 1.0),\n            random.uniform(-0.05 * (y1 - y0), 0.05 * (y1 - y0)),\n            random.uniform(-0.05 * (x1 - x0), 0.05 * (x1 - x0))\n        ), trans)\n    trans = np.dot(np.array([[1, 0, 0.5 * (y1 + y0)], [0, 1, 0.5 * (x1 + x0)], [0, 0, 1]]), trans)\n\n    # Read the image, transform to black and white and comvert to numpy array\n    img = read_raw_image(p).convert('L')\n    img = img_to_array(img)\n\n    # Apply affine transformation\n    matrix = trans[:2, :2]\n    offset = trans[:2, 2]\n    img = img.reshape(img.shape[:-1])\n    img = affine_transform(img, matrix, offset, output_shape=img_shape[:-1], order=1, mode='constant',\n                           cval=np.average(img))\n    img = img.reshape(img_shape)\n\n    # Normalize to zero mean and unit variance\n    img -= np.mean(img, keepdims=True)\n    img /= np.std(img, keepdims=True) + K.epsilon()\n    return img\n\ndef read_for_training(p):\n    \"\"\"\n    Read and preprocess an image with data augmentation (random transform).\n    \"\"\"\n    return read_cropped_image(p, True)\n\n\ndef read_for_validation(p):\n    \"\"\"\n    Read and preprocess an image without data augmentation (use for testing).\n    \"\"\"\n    return read_cropped_image(p, False)\n\n\np = list(tagged.keys())[312]","execution_count":11,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(p)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Model Part"},{"metadata":{"trusted":true},"cell_type":"code","source":"# # Dependent for SNN Model structure\n# from keras import backend as K\n# from keras import regularizers\n# from keras.applications.xception import Xception\n# from keras.applications.densenet import DenseNet121, DenseNet169\n# from keras.applications.inception_v3 import InceptionV3\n# from keras.applications.mobilenet import MobileNet\n# from keras.applications.resnet50 import ResNet50\n# from keras.applications.nasnet import NASNetMobile\n# from keras.engine.topology import Input\n# from keras.layers import Activation, Add, BatchNormalization, Concatenate, Conv2D, Dense, Flatten, GlobalMaxPooling2D, \\\n#     Lambda, MaxPooling2D, Reshape, GlobalAveragePooling2D\n# from keras.models import Model\n# from keras.optimizers import Adam","execution_count":12,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"725e7e521b6bf776e8a165614dba50cb597d3a1c"},"cell_type":"code","source":"# Here we only should the self-designed cnn layers, the Pretrained layers like dense121 are well packaged.\ndef subblock(x, filter, **kwargs):\n    x = BatchNormalization()(x)\n    y = x\n    y = Conv2D(filter, (1, 1), activation='relu', **kwargs)(y)  # Reduce the number of features to 'filter'\n    y = BatchNormalization()(y)\n    y = Conv2D(filter, (3, 3), activation='relu', **kwargs)(y)  # Extend the feature field\n    y = BatchNormalization()(y)\n    y = Conv2D(K.int_shape(x)[-1], (1, 1), **kwargs)(y)  # no activation # Restore the number of original features\n    y = Add()([x, y])  # Add the bypass connection\n    y = Activation('relu')(y)\n    return y\n\n\ndef build_model(lr, l2, activation='sigmoid'):\n    ##############\n    # BRANCH MODEL\n    ##############\n    regul = regularizers.l2(l2)\n    optim = Adam(lr=lr)\n    kwargs = {'padding': 'same', 'kernel_regularizer': regul}\n\n    inp = Input(shape=img_shape)  # 384x384x1\n    x = Conv2D(64, (9, 9), strides=2, activation='relu', **kwargs)(inp)\n\n    x = MaxPooling2D((2, 2), strides=(2, 2))(x)  # 96x96x64\n    for _ in range(2):\n        x = BatchNormalization()(x)\n        x = Conv2D(64, (3, 3), activation='relu', **kwargs)(x)\n\n    x = MaxPooling2D((2, 2), strides=(2, 2))(x)  # 48x48x64\n    x = BatchNormalization()(x)\n    x = Conv2D(128, (1, 1), activation='relu', **kwargs)(x)  # 48x48x128\n    for _ in range(4):\n        x = subblock(x, 64, **kwargs)\n\n    x = MaxPooling2D((2, 2), strides=(2, 2))(x)  # 24x24x128\n    x = BatchNormalization()(x)\n    x = Conv2D(256, (1, 1), activation='relu', **kwargs)(x)  # 24x24x256\n    for _ in range(4):\n        x = subblock(x, 64, **kwargs)\n\n    x = MaxPooling2D((2, 2), strides=(2, 2))(x)  # 12x12x256\n    x = BatchNormalization()(x)\n    x = Conv2D(384, (1, 1), activation='relu', **kwargs)(x)  # 12x12x384\n    for _ in range(4):\n        x = subblock(x, 96, **kwargs)\n\n    x = MaxPooling2D((2, 2), strides=(2, 2))(x)  # 6x6x384\n    x = BatchNormalization()(x)\n    x = Conv2D(512, (1, 1), activation='relu', **kwargs)(x)  # 6x6x512\n    for _ in range(4):\n        x = subblock(x, 128, **kwargs)\n\n    x = GlobalMaxPooling2D()(x)  # 512\n    branch_model = Model(inp, x)\n\n    ############\n    # HEAD MODEL\n    ############\n    mid = 32\n    xa_inp = Input(shape=branch_model.output_shape[1:])\n    xb_inp = Input(shape=branch_model.output_shape[1:])\n    x1 = Lambda(lambda x: x[0] * x[1])([xa_inp, xb_inp])\n    x2 = Lambda(lambda x: x[0] + x[1])([xa_inp, xb_inp])\n    x3 = Lambda(lambda x: K.abs(x[0] - x[1]))([xa_inp, xb_inp])\n    x4 = Lambda(lambda x: K.square(x))(x3)\n    x = Concatenate()([x1, x2, x3, x4])\n    x = Reshape((4, branch_model.output_shape[1], 1), name='reshape1')(x)\n\n    # Per feature NN with shared weight is implemented using CONV2D with appropriate stride.\n    x = Conv2D(mid, (4, 1), activation='relu', padding='valid')(x)\n    x = Reshape((branch_model.output_shape[1], mid, 1))(x)\n    x = Conv2D(1, (1, mid), activation='linear', padding='valid')(x)\n    x = Flatten(name='flatten')(x)\n\n    # Weighted sum implemented as a Dense layer.\n    x = Dense(1, use_bias=True, activation=activation, name='weighted-average')(x)\n    head_model = Model([xa_inp, xb_inp], x, name='head')\n\n    ########################\n    # SIAMESE NEURAL NETWORK\n    ########################\n    # Complete model is constructed by calling the branch model on each input image,\n    # and then the head model on the resulting 512-vectors.\n    img_a = Input(shape=img_shape)\n    img_b = Input(shape=img_shape)\n    xa = branch_model(img_a)\n    xb = branch_model(img_b)\n    x = head_model([xa, xb])\n    model = Model([img_a, img_b], x)\n    model.compile(optim, loss='binary_crossentropy', metrics=['binary_crossentropy', 'acc'])\n    return model, branch_model, head_model\n\n\nmodel, branch_model, head_model = build_model(64e-5, 0)","execution_count":13,"outputs":[{"output_type":"stream","text":"WARNING:tensorflow:From /opt/conda/lib/python3.6/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.\nInstructions for updating:\nColocations handled automatically by placer.\n","name":"stdout"}]},{"metadata":{"trusted":true,"_uuid":"d8266e1cc94c9c56ff75352aef4194aa37574972"},"cell_type":"code","source":"h2ws = {}\nnew_whale = 'new_whale'\nfor p, w in tagged.items():\n    if w != new_whale:  # Use only identified whales\n        h = p2h[p]\n        if h not in h2ws: h2ws[h] = []\n        if w not in h2ws[h]: h2ws[h].append(w)\nfor h, ws in h2ws.items():\n    if len(ws) > 1:\n        h2ws[h] = sorted(ws)\n\n# For each whale, find the unambiguous images ids.\nw2hs = {}\nfor h, ws in h2ws.items():\n    if len(ws) == 1:  # Use only unambiguous pictures\n        w = ws[0]\n        if w not in w2hs: w2hs[w] = []\n        if h not in w2hs[w]: w2hs[w].append(h)\nfor w, hs in w2hs.items():\n    if len(hs) > 1:\n        w2hs[w] = sorted(hs)","execution_count":14,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"f122bcb1d87721a96a18c31aa2f46aaad4037039"},"cell_type":"code","source":"train = []  # A list of training image ids\nfor hs in w2hs.values():\n    if len(hs) > 1:\n        train += hs\nrandom.shuffle(train)\ntrain_set = set(train)\n\nw2ts = {}  # Associate the image ids from train to each whale id.\nfor w, hs in w2hs.items():\n    for h in hs:\n        if h in train_set:\n            if w not in w2ts:\n                w2ts[w] = []\n            if h not in w2ts[w]:\n                w2ts[w].append(h)\nfor w, ts in w2ts.items():\n    w2ts[w] = np.array(ts)\n\nt2i = {}  # The position in train of each training image id\nfor i, t in enumerate(train):\n    t2i[t] = i","execution_count":15,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"aa16cfd51fdbce44271883869486c1cad32f1091"},"cell_type":"code","source":"class TrainingData(Sequence):\n    def __init__(self, score, steps=1000, batch_size=32):\n        \"\"\"\n        @param score the cost matrix for the picture matching\n        @param steps the number of epoch we are planning with this score matrix\n        \"\"\"\n        super(TrainingData, self).__init__()\n        self.score = -score  # Maximizing the score is the same as minimuzing -score.\n        self.steps = steps\n        self.batch_size = batch_size\n        for ts in w2ts.values():\n            idxs = [t2i[t] for t in ts]\n            for i in idxs:\n                for j in idxs:\n                    self.score[\n                        i, j] = 10000.0  # Set a large value for matching whales -- eliminates this potential pairing\n        self.on_epoch_end()\n\n    def __getitem__(self, index):\n        start = self.batch_size * index\n        end = min(start + self.batch_size, len(self.match) + len(self.unmatch))\n        size = end - start\n        assert size > 0\n        a = np.zeros((size,) + img_shape, dtype=K.floatx())\n        b = np.zeros((size,) + img_shape, dtype=K.floatx())\n        c = np.zeros((size, 1), dtype=K.floatx())\n        j = start // 2\n        for i in range(0, size, 2):\n            a[i, :, :, :] = read_for_training(self.match[j][0])\n            b[i, :, :, :] = read_for_training(self.match[j][1])\n            c[i, 0] = 1  # This is a match\n            a[i + 1, :, :, :] = read_for_training(self.unmatch[j][0])\n            b[i + 1, :, :, :] = read_for_training(self.unmatch[j][1])\n            c[i + 1, 0] = 0  # Different whales\n            j += 1\n        return [a, b], c\n\n    def on_epoch_end(self):\n        if self.steps <= 0: return  # Skip this on the last epoch.\n        self.steps -= 1\n        self.match = []\n        self.unmatch = []\n        _, _, x = lapjv(self.score)  # Solve the linear assignment problem\n        y = np.arange(len(x), dtype=np.int32)\n\n        # Compute a derangement for matching whales\n        for ts in w2ts.values():\n            d = ts.copy()\n            while True:\n                random.shuffle(d)\n                if not np.any(ts == d): break\n            for ab in zip(ts, d): self.match.append(ab)\n\n        # Construct unmatched whale pairs from the LAP solution.\n        for i, j in zip(x, y):\n            if i == j:\n                print(self.score)\n                print(x)\n                print(y)\n                print(i, j)\n            assert i != j\n            self.unmatch.append((train[i], train[j]))\n\n        # Force a different choice for an eventual next epoch.\n        self.score[x, y] = 10000.0\n        self.score[y, x] = 10000.0\n        random.shuffle(self.match)\n        random.shuffle(self.unmatch)\n        # print(len(self.match), len(train), len(self.unmatch), len(train))\n        assert len(self.match) == len(train) and len(self.unmatch) == len(train)\n\n    def __len__(self):\n        return (len(self.match) + len(self.unmatch) + self.batch_size - 1) // self.batch_size\n\n\n# Test on a batch of 32 with random costs.\nscore = np.random.random_sample(size=(len(train), len(train)))\ndata = TrainingData(score)\n(a, b), c = data[0]","execution_count":16,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"005d041475be5ec97ac8e1d937bea6e7253226af"},"cell_type":"code","source":"# A Keras generator to evaluate only the BRANCH MODEL\nclass FeatureGen(Sequence):\n    def __init__(self, data, batch_size=64, verbose=1):\n        super(FeatureGen, self).__init__()\n        self.data = data\n        self.batch_size = batch_size\n        self.verbose = verbose\n        if self.verbose > 0: self.progress = tqdm(total=len(self), desc='Features')\n\n    def __getitem__(self, index):\n        start = self.batch_size * index\n        size = min(len(self.data) - start, self.batch_size)\n        a = np.zeros((size,) + img_shape, dtype=K.floatx())\n        for i in range(size): a[i, :, :, :] = read_for_validation(self.data[start + i])\n        if self.verbose > 0:\n            self.progress.update()\n            if self.progress.n >= len(self): self.progress.close()\n        return a\n\n    def __len__(self):\n        return (len(self.data) + self.batch_size - 1) // self.batch_size\n\n\nclass ScoreGen(Sequence):\n    def __init__(self, x, y=None, batch_size=2048, verbose=1):\n        super(ScoreGen, self).__init__()\n        self.x = x\n        self.y = y\n        self.batch_size = batch_size\n        self.verbose = verbose\n        if y is None:\n            self.y = self.x\n            self.ix, self.iy = np.triu_indices(x.shape[0], 1)\n        else:\n            self.iy, self.ix = np.indices((y.shape[0], x.shape[0]))\n            self.ix = self.ix.reshape((self.ix.size,))\n            self.iy = self.iy.reshape((self.iy.size,))\n        self.subbatch = (len(self.x) + self.batch_size - 1) // self.batch_size\n        if self.verbose > 0:\n            self.progress = tqdm(total=len(self), desc='Scores')\n\n    def __getitem__(self, index):\n        start = index * self.batch_size\n        end = min(start + self.batch_size, len(self.ix))\n        a = self.y[self.iy[start:end], :]\n        b = self.x[self.ix[start:end], :]\n        if self.verbose > 0:\n            self.progress.update()\n            if self.progress.n >= len(self): self.progress.close()\n        return [a, b]\n\n    def __len__(self):\n        return (len(self.ix) + self.batch_size - 1) // self.batch_size\n","execution_count":17,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"7ac5f82779a71cca2bc2cd1bac8bac385cb48a23"},"cell_type":"code","source":"def set_lr(model, lr):\n    K.set_value(model.optimizer.lr, float(lr))\n\n\ndef get_lr(model):\n    return K.get_value(model.optimizer.lr)\n\n\ndef score_reshape(score, x, y=None):\n    \"\"\"\n    Tranformed the packed matrix 'score' into a square matrix.\n    @param score the packed matrix\n    @param x the first image feature tensor\n    @param y the second image feature tensor if different from x\n    @result the square matrix\n    \"\"\"\n    if y is None:\n        # When y is None, score is a packed upper triangular matrix.\n        # Unpack, and transpose to form the symmetrical lower triangular matrix.\n        m = np.zeros((x.shape[0], x.shape[0]), dtype=K.floatx())\n        m[np.triu_indices(x.shape[0], 1)] = score.squeeze()\n        m += m.transpose()\n    else:\n        m = np.zeros((y.shape[0], x.shape[0]), dtype=K.floatx())\n        iy, ix = np.indices((y.shape[0], x.shape[0]))\n        ix = ix.reshape((ix.size,))\n        iy = iy.reshape((iy.size,))\n        m[iy, ix] = score.squeeze()\n    return m\n\n\ndef compute_score(verbose=1):\n    \"\"\"\n    Compute the score matrix by scoring every pictures from the training set against every other picture O(n^2).\n    \"\"\"\n    features = branch_model.predict_generator(FeatureGen(train, verbose=verbose), max_queue_size=12, workers=6,\n                                              verbose=0)\n    score = head_model.predict_generator(ScoreGen(features, verbose=verbose), max_queue_size=12, workers=6, verbose=0)\n    score = score_reshape(score, features)\n    return features, score\n\n\ndef make_steps(step, ampl):\n    \"\"\"\n    Perform training epochs\n    @param step Number of epochs to perform\n    @param ampl the K, the randomized component of the score matrix.\n    \"\"\"\n    global w2ts, t2i, steps, features, score, histories\n\n    # shuffle the training pictures\n    random.shuffle(train)\n\n    # Map whale id to the list of associated training picture hash value\n    w2ts = {}\n    for w, hs in w2hs.items():\n        for h in hs:\n            if h in train_set:\n                if w not in w2ts: w2ts[w] = []\n                if h not in w2ts[w]: w2ts[w].append(h)\n    for w, ts in w2ts.items(): w2ts[w] = np.array(ts)\n\n    # Map training picture hash value to index in 'train' array    \n    t2i = {}\n    for i, t in enumerate(train): t2i[t] = i\n\n    # Compute the match score for each picture pair\n    features, score = compute_score()\n\n    # Train the model for 'step' epochs\n    history = model.fit_generator(\n        TrainingData(score + ampl * np.random.random_sample(size=score.shape), steps=step, batch_size=32),\n        initial_epoch=steps, epochs=steps + step, max_queue_size=12, workers=6, verbose=1).history\n    steps += step\n\n    # Collect history data\n    history['epochs'] = steps\n    history['ms'] = np.mean(score)\n    history['lr'] = get_lr(model)\n    print(history['epochs'], history['lr'], history['ms'])\n    histories.append(history)","execution_count":18,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"87091f9dcd5a0d11dc255d427abd42cb6ba7506e"},"cell_type":"code","source":"histories = []\nsteps = 0\n\nif isfile('../input/humpback-whale-identification-model-files/mpiotte-standard.model'):\n    print('pretrained exist.')\n    tmp = keras.models.load_model('../input/humpback-whale-identification-model-files/mpiotte-standard.model')\n    model.set_weights(tmp.get_weights())\nelse:\n    # epoch -> 10\n    make_steps(10, 1000)\n    ampl = 100.0\n    for _ in range(2):\n        print('noise ampl.  = ', ampl)\n        make_steps(5, ampl)\n        ampl = max(1.0, 100 ** -0.1 * ampl)\n#     # epoch -> 150\n#     for _ in range(18): make_steps(5, 1.0)\n#     # epoch -> 200\n#     set_lr(model, 16e-5)\n#     for _ in range(10): make_steps(5, 0.5)\n#     # epoch -> 240\n#     set_lr(model, 4e-5)\n#     for _ in range(8): make_steps(5, 0.25)\n#     # epoch -> 250\n#     set_lr(model, 1e-5)\n#     for _ in range(2): make_steps(5, 0.25)\n#     # epoch -> 300\n#     weights = model.get_weights()\n#     model, branch_model, head_model = build_model(64e-5, 0.0002)\n#     model.set_weights(weights)\n#     for _ in range(10): make_steps(5, 1.0)\n#     # epoch -> 350\n#     set_lr(model, 16e-5)\n#     for _ in range(10): make_steps(5, 0.5)\n#     # epoch -> 390\n#     set_lr(model, 4e-5)\n#     for _ in range(8): make_steps(5, 0.25)\n#     # epoch -> 400\n#     set_lr(model, 1e-5)\n#     for _ in range(2): make_steps(5, 0.25)\n#     model.save('standard.model')","execution_count":19,"outputs":[{"output_type":"stream","text":"pretrained exist.\n","name":"stdout"}]},{"metadata":{"trusted":true,"_uuid":"fdeb2d88e3ea69c5452694fa7c764231c48c590a"},"cell_type":"code","source":"model.summary()","execution_count":20,"outputs":[{"output_type":"stream","text":"__________________________________________________________________________________________________\nLayer (type)                    Output Shape         Param #     Connected to                     \n==================================================================================================\ninput_4 (InputLayer)            (None, 384, 384, 1)  0                                            \n__________________________________________________________________________________________________\ninput_5 (InputLayer)            (None, 384, 384, 1)  0                                            \n__________________________________________________________________________________________________\nmodel_1 (Model)                 (None, 512)          2692096     input_4[0][0]                    \n                                                                 input_5[0][0]                    \n__________________________________________________________________________________________________\nhead (Model)                    (None, 1)            706         model_1[1][0]                    \n                                                                 model_1[2][0]                    \n==================================================================================================\nTotal params: 2,692,802\nTrainable params: 2,675,010\nNon-trainable params: 17,792\n__________________________________________________________________________________________________\n","name":"stdout"}]},{"metadata":{"trusted":true,"_uuid":"f194458bbb728a7cc35b75b40752e98021b6493b"},"cell_type":"code","source":"def prepare_submission(threshold, filename):\n    \"\"\"\n    Generate a Kaggle submission file.\n    @param threshold the score given to 'new_whale'\n    @param filename the submission file name\n    \"\"\"\n    vtop = 0\n    vhigh = 0\n    pos = [0, 0, 0, 0, 0, 0]\n    with open(filename, 'wt', newline='\\n') as f:\n        f.write('Image,Id\\n')\n        for i, p in enumerate(tqdm(submit)):\n            t = []\n            s = set()\n            a = score[i, :]\n            for j in list(reversed(np.argsort(a))):\n                h = known[j]\n                if a[j] < threshold and new_whale not in s:\n                    pos[len(t)] += 1\n                    s.add(new_whale)\n                    t.append(new_whale)\n                    if len(t) == 5: break;\n                for w in h2ws[h]:\n                    assert w != new_whale\n                    if w not in s:\n                        if a[j] > 1.0:\n                            vtop += 1\n                        elif a[j] >= threshold:\n                            vhigh += 1\n                        s.add(w)\n                        t.append(w)\n                        if len(t) == 5: break;\n                if len(t) == 5: break;\n            if new_whale not in s: pos[5] += 1\n            assert len(t) == 5 and len(s) == 5\n            f.write(p + ',' + ' '.join(t[:5]) + '\\n')\n    return vtop, vhigh, pos","execution_count":21,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"624143d234c6cc5f7374a2451aab84b955cecb09"},"cell_type":"code","source":"# Find elements from training sets not 'new_whale'\ntic = time.time()\nh2ws = {}\nfor p, w in tagged.items():\n    if w != new_whale:  # Use only identified whales\n        h = p2h[p]\n        if h not in h2ws: h2ws[h] = []\n        if w not in h2ws[h]: h2ws[h].append(w)\nknown = sorted(list(h2ws.keys()))\n\n# Dictionary of picture indices\nh2i = {}\nfor i, h in enumerate(known): h2i[h] = i\n\n# Evaluate the model.\nfknown = branch_model.predict_generator(FeatureGen(known), max_queue_size=20, workers=10, verbose=0)\nfsubmit = branch_model.predict_generator(FeatureGen(submit), max_queue_size=20, workers=10, verbose=0)\nscore = head_model.predict_generator(ScoreGen(fknown, fsubmit), max_queue_size=20, workers=10, verbose=0)\nscore = score_reshape(score, fknown, fsubmit)\n\n# Generate the subsmission file.\nprepare_submission(0.99, 'submission_for_em.csv')\ntoc = time.time()\nprint(\"Submission time: \", (toc - tic) / 60.)\n\n# Here the submission_for_em.csv, we use other way to get upload it get the leaderboard score.","execution_count":22,"outputs":[{"output_type":"display_data","data":{"text/plain":"HBox(children=(IntProgress(value=0, description='Features', max=246, style=ProgressStyle(description_width='in…","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7b08f717709541c5975339d2acea97f2"}},"metadata":{}},{"output_type":"stream","text":"\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"HBox(children=(IntProgress(value=0, description='Features', max=125, style=ProgressStyle(description_width='in…","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"98c33aa98da34383a1ae93cd95e7b81c"}},"metadata":{}},{"output_type":"stream","text":"\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"HBox(children=(IntProgress(value=0, description='Scores', max=61006, style=ProgressStyle(description_width='in…","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"d0ddad3141ae427791c67c9cb515e0af"}},"metadata":{}},{"output_type":"stream","text":"\n","name":"stdout"},{"output_type":"display_data","data":{"text/plain":"HBox(children=(IntProgress(value=0, max=7960), HTML(value='')))","application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"fbd0a55e27de4e2187568818ba4d0d49"}},"metadata":{}},{"output_type":"stream","text":"\nSubmission time:  16.67746210892995\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"By training differrnt rounds of the model, the more we train, the better result we have, but the performance will be worse. For each round, we need nearly 5 hours to finish but the total session of the kernel is 9 hours, so we desided to store each round's submission result and combine them in the last round by emsembling."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Emsembling we only choose the 4 most different results from 4 different model structure to compute the final result \nimport csv\n\nsub_files = ['../input/em-whale/submission_0.csv',\n             '../input/em-whale/submission_7.csv',\n            '../input/em-whale/submission_8.csv',\n            '../input/em-whale/submission_3.csv']\nsub_weight = [0.9001**2,\n              0.7719**2,\n             0.8229**2,\n             0.8903**2]\nHlabel = 'Image' \nHtarget = 'Id'\nnpt = 6\nplace_weights = {}\nfor i in range(npt):\n    place_weights[i] = ( 1 / (i + 1) )\n    \nprint(place_weights)\n\nlg = len(sub_files)\nsub = [None]*lg\nfor i, file in enumerate( sub_files ):\n   \n    print(\"Reading {}: w={} - {}\". format(i, sub_weight[i], file))\n    reader = csv.DictReader(open(file,\"r\"))\n    sub[i] = sorted(reader, key=lambda d: str(d[Hlabel]))\n\nout = open(\"submission.csv\", \"w\", newline='')\nwriter = csv.writer(out)\nwriter.writerow([Hlabel,Htarget])\n\nfor p, row in enumerate(sub[0]):\n    target_weight = {}\n    for s in range(lg):\n        row1 = sub[s][p]\n        for ind, trgt in enumerate(row1[Htarget].split(' ')):\n            target_weight[trgt] = target_weight.get(trgt,0) + (place_weights[ind]*sub_weight[s])\n    tops_trgt = sorted(target_weight, key=target_weight.get, reverse=True)[:npt]\n    writer.writerow([row1[Hlabel], \" \".join(tops_trgt)])\nout.close()","execution_count":29,"outputs":[{"output_type":"stream","text":"{0: 1.0, 1: 0.5, 2: 0.3333333333333333, 3: 0.25, 4: 0.2, 5: 0.16666666666666666}\nReading 0: w=0.84658401 - ../input/em-whale/submission_0.csv\nReading 1: w=0.59582961 - ../input/em-whale/submission_7.csv\nReading 2: w=0.6771644099999999 - ../input/em-whale/submission_8.csv\nReading 3: w=0.81 - ../input/em-whale/submission_3.csv\n","name":"stdout"}]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}