{
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.0"
  },
  "orig_nbformat": 4,
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.9.0 64-bit ('.venv')"
  },
  "interpreter": {
   "hash": "d78da394afdad4210aa22efe35c08b5867548b059557eec2b19bd77cf05351f8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2,
 "cells": [
  {
   "source": [
    "# 0 - Intro\n",
    "This is a notebook sample to download dataset, arrange folders, train a simple model and export it to model's folder"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "## Caltech-256 dataset \n",
    "\n",
    "Could be downloaded from [oficial website](http://www.vision.caltech.edu/Image_Datasets/Caltech256/)\n",
    "\n",
    "or\n",
    "\n",
    "It can be downloaded from a public S3 from AWS with some dataset [samples](https://sagemaker-examples.readthedocs.io/en/latest/introduction_to_amazon_algorithms/imageclassification_caltech/Image-classification-transfer-learning-highlevel.html)"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "## 1 - Download and arrange Data"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "import boto3\n",
    "import tarfile\n",
    "import os\n",
    "import shutil\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "session = boto3.Session(profile_name='test')\n",
    "s3 = session.client('s3')\n",
    "\n",
    "data_bucket = \"sagemaker-sample-files\"\n",
    "data_prefix = \"datasets/image/caltech-256/256_ObjectCategories.tar\"\n",
    "root = \"./dataset/\"\n",
    "local_prefix = \"256_ObjectCategories.tar\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "# download\n",
    "s3.download_file(\n",
    "    data_bucket, data_prefix , root + local_prefix\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract file\n",
    "cwd = os.getcwd()\n",
    "tar = tarfile.open(os.path.join(root, local_prefix), \"r\")\n",
    "os.chdir(root)\n",
    "tar.extractall()\n",
    "tar.close()\n",
    "os.remove(local_prefix)\n",
    "os.chdir(cwd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "# clean objects that was not on list\n",
    "classes = ['010.beer-mug','041.coffee-mug','212.teapot','246.wine-bottle']\n",
    "new_dir = root + \"256_ObjectCategories\"\n",
    "for i in os.listdir(new_dir):\n",
    "    if not i in classes:\n",
    "        shutil.rmtree(os.path.join(new_dir, i))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create destination folders\n",
    "new_destination = root + \"Caltech-256\" \n",
    "if not os.path.isdir(new_destination): os.mkdir(new_destination)\n",
    "if not os.path.isdir(new_destination + \"/train\"): os.mkdir(new_destination + \"/train\")\n",
    "if not os.path.isdir(new_destination + \"/test\"): os.mkdir(new_destination + \"/test\")\n",
    "for i in classes:\n",
    "    if not os.path.isdir(new_destination + \"/train/\" + i): os.mkdir(new_destination + \"/train/\" + i)\n",
    "    if not os.path.isdir(new_destination + \"/test/\" + i): os.mkdir(new_destination + \"/test/\" + i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# arrange into new folder structure\n",
    "for i in os.listdir(new_dir):\n",
    "    for j in os.listdir(os.path.join(new_dir, i)):\n",
    "        #print(os.path.join(new_dir, i, j))\n",
    "        if np.random.rand(1) < 0.2:\n",
    "            os.rename(os.path.join(new_dir, i, j),\n",
    "                os.path.join(new_destination,'test',i,j))\n",
    "            #print(\"test\",os.path.join(new_dir,'test',i,j))\n",
    "        else:\n",
    "            os.rename(os.path.join(new_dir, i, j),\n",
    "                os.path.join(new_destination,'train',i,j))\n",
    "            #print(\"train\",os.path.join(new_dir,'train',i,j))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Delete Old folder\n",
    "if os.path.isdir(new_dir): shutil.rmtree(new_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Rename dirs (one time only)\n",
    "os.rename(os.path.join(new_destination,'train','010.beer-mug'),\n",
    "    os.path.join(new_destination,'train','01.beer-mug'))\n",
    "os.rename(os.path.join(new_destination,'test','010.beer-mug'),\n",
    "    os.path.join(new_destination,'test','01.beer-mug'))\n",
    "os.rename(os.path.join(new_destination,'train','041.coffee-mug'),\n",
    "    os.path.join(new_destination,'train','02.coffee-mug'))\n",
    "os.rename(os.path.join(new_destination,'test','041.coffee-mug'),\n",
    "    os.path.join(new_destination,'test','02.coffee-mug'))\n",
    "os.rename(os.path.join(new_destination,'train','212.teapot'),\n",
    "    os.path.join(new_destination,'train','03.teapot'))\n",
    "os.rename(os.path.join(new_destination,'test','212.teapot'),\n",
    "    os.path.join(new_destination,'test','03.teapot'))\n",
    "os.rename(os.path.join(new_destination,'train','246.wine-bottle'),\n",
    "    os.path.join(new_destination,'train','04.wine-bottle'))\n",
    "os.rename(os.path.join(new_destination,'test','246.wine-bottle'),\n",
    "    os.path.join(new_destination,'test','04.wine-bottle'))"
   ]
  },
  {
   "source": [
    "## 2 - Training"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "from torch.optim import lr_scheduler\n",
    "from torchvision import datasets, models, transforms\n",
    "import matplotlib.pyplot as plt\n",
    "import time\n",
    "import copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load images into tensors\n",
    "data_transforms = {\n",
    "    'train': transforms.Compose([\n",
    "        transforms.RandomResizedCrop(size=256, scale=(0.8, 1.0)),\n",
    "        transforms.RandomRotation(degrees=15),\n",
    "        transforms.RandomHorizontalFlip(),\n",
    "        transforms.CenterCrop(size=224),\n",
    "        transforms.ToTensor(),\n",
    "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "    ]),\n",
    "    'test': transforms.Compose([\n",
    "        transforms.Resize(256),\n",
    "        transforms.CenterCrop(224),\n",
    "        transforms.ToTensor(),\n",
    "        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "    ]),\n",
    "}\n",
    "\n",
    "data_dir = 'dataset/Caltech-256'\n",
    "image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x),\n",
    "                                          data_transforms[x])\n",
    "                  for x in ['train', 'test']}\n",
    "dataloaders = {x: torch.utils.data.DataLoader(image_datasets[x], batch_size=4,\n",
    "                                             shuffle=True, num_workers=4)\n",
    "              for x in ['train', 'test']}\n",
    "dataset_sizes = {x: len(image_datasets[x]) for x in ['train', 'test']}\n",
    "class_names = image_datasets['train'].classes\n",
    "\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "['01.beer-mug', '02.coffee-mug', '03.teapot', '04.wine-bottle']\n"
     ]
    }
   ],
   "source": [
    "# Optional, only to see few samples\n",
    "def imshow(inp, title=None):\n",
    "    \"\"\"Imshow for Tensor.\"\"\"\n",
    "    inp = inp.numpy().transpose((1, 2, 0))\n",
    "    mean = np.array([0.485, 0.456, 0.406])\n",
    "    std = np.array([0.229, 0.224, 0.225])\n",
    "    inp = std * inp + mean\n",
    "    inp = np.clip(inp, 0, 1)\n",
    "    plt.imshow(inp)\n",
    "    if title is not None:\n",
    "        plt.title(title)\n",
    "    plt.pause(0.001)  # pause a bit so that plots are updated\n",
    "\n",
    "\n",
    "# Get a batch of training data\n",
    "inputs, classes = next(iter(dataloaders['train']))\n",
    "\n",
    "# Make a grid from batch\n",
    "out = torchvision.utils.make_grid(inputs)\n",
    "\n",
    "imshow(out, title=[class_names[x] for x in classes])\n",
    "\n",
    "print(class_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_model(model, criterion, optimizer, scheduler, num_epochs=25):\n",
    "    since = time.time()\n",
    "\n",
    "    best_model_wts = copy.deepcopy(model.state_dict())\n",
    "    best_acc = 0.0\n",
    "\n",
    "    for epoch in range(num_epochs):\n",
    "        print('Epoch {}/{}'.format(epoch, num_epochs - 1))\n",
    "        print('-' * 10)\n",
    "\n",
    "        # Each epoch has a training and validation phase\n",
    "        for phase in ['train', 'test']:\n",
    "            if phase == 'train':\n",
    "                model.train()  # Set model to training mode\n",
    "            else:\n",
    "                model.eval()   # Set model to evaluate mode\n",
    "\n",
    "            running_loss = 0.0\n",
    "            running_corrects = 0\n",
    "\n",
    "            # Iterate over data.\n",
    "            for inputs, labels in dataloaders[phase]:\n",
    "                inputs = inputs.to(device)\n",
    "                labels = labels.to(device)\n",
    "\n",
    "                # zero the parameter gradients\n",
    "                optimizer.zero_grad()\n",
    "\n",
    "                # forward\n",
    "                # track history if only in train\n",
    "                with torch.set_grad_enabled(phase == 'train'):\n",
    "                    outputs = model(inputs)\n",
    "                    _, preds = torch.max(outputs, 1)\n",
    "                    loss = criterion(outputs, labels)\n",
    "\n",
    "                    # backward + optimize only if in training phase\n",
    "                    if phase == 'train':\n",
    "                        loss.backward()\n",
    "                        optimizer.step()\n",
    "\n",
    "                # statistics\n",
    "                running_loss += loss.item() * inputs.size(0)\n",
    "                running_corrects += torch.sum(preds == labels.data)\n",
    "            if phase == 'train':\n",
    "                scheduler.step()\n",
    "\n",
    "            epoch_loss = running_loss / dataset_sizes[phase]\n",
    "            epoch_acc = running_corrects.double() / dataset_sizes[phase]\n",
    "\n",
    "            print('{} Loss: {:.4f} Acc: {:.4f}'.format(\n",
    "                phase, epoch_loss, epoch_acc))\n",
    "\n",
    "            # deep copy the model\n",
    "            if phase == 'test' and epoch_acc > best_acc:\n",
    "                best_acc = epoch_acc\n",
    "                best_model_wts = copy.deepcopy(model.state_dict())\n",
    "\n",
    "        print()\n",
    "\n",
    "    time_elapsed = time.time() - since\n",
    "    print('Training complete in {:.0f}m {:.0f}s'.format(\n",
    "        time_elapsed // 60, time_elapsed % 60))\n",
    "    print('Best val Acc: {:4f}'.format(best_acc))\n",
    "\n",
    "    # load best model weights\n",
    "    model.load_state_dict(best_model_wts)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "def visualize_model(model, num_images=6):\n",
    "    was_training = model.training\n",
    "    model.eval()\n",
    "    images_so_far = 0\n",
    "    fig = plt.figure()\n",
    "\n",
    "    with torch.no_grad():\n",
    "        for i, (inputs, labels) in enumerate(dataloaders['test']):\n",
    "            inputs = inputs.to(device)\n",
    "            labels = labels.to(device)\n",
    "\n",
    "            outputs = model(inputs)\n",
    "            _, preds = torch.max(outputs, 1)\n",
    "\n",
    "            for j in range(inputs.size()[0]):\n",
    "                images_so_far += 1\n",
    "                ax = plt.subplot(num_images//2, 2, images_so_far)\n",
    "                ax.axis('off')\n",
    "                ax.set_title('predicted: {}'.format(class_names[preds[j]]))\n",
    "                imshow(inputs.cpu().data[j])\n",
    "\n",
    "                if images_so_far == num_images:\n",
    "                    model.train(mode=was_training)\n",
    "                    return\n",
    "        model.train(mode=was_training)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "Downloading: \"https://download.pytorch.org/models/resnet18-f37072fd.pth\" to /Users/egfranco/.cache/torch/hub/checkpoints/resnet18-f37072fd.pth\n",
      "100.0%\n"
     ]
    }
   ],
   "source": [
    "model_ft = models.resnet18(pretrained=True)\n",
    "num_ftrs = model_ft.fc.in_features\n",
    "\n",
    "model_ft.fc = nn.Sequential(\n",
    "    nn.Linear(num_ftrs, 256),\n",
    "    nn.ReLU(),\n",
    "    nn.Dropout(0.4),\n",
    "    nn.Linear(256, 4), \n",
    "    nn.LogSoftmax(dim=1) # For using NLLLoss()\n",
    ")\n",
    "\n",
    "model_ft = model_ft.to(device)\n",
    "\n",
    "criterion = nn.NLLLoss()\n",
    "\n",
    "# Observe that all parameters are being optimized\n",
    "optimizer_ft = optim.SGD(model_ft.parameters(), lr=0.001, momentum=0.9)\n",
    "\n",
    "# Decay LR by a factor of 0.1 every 7 epochs\n",
    "exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=7, gamma=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Epoch 0/11\n",
      "----------\n",
      "train Loss: 1.1855 Acc: 0.4370\n",
      "test Loss: 0.6345 Acc: 0.8701\n",
      "\n",
      "Epoch 1/11\n",
      "----------\n",
      "train Loss: 0.7126 Acc: 0.7742\n",
      "test Loss: 0.3037 Acc: 0.9221\n",
      "\n",
      "Epoch 2/11\n",
      "----------\n",
      "train Loss: 0.5259 Acc: 0.8182\n",
      "test Loss: 0.2504 Acc: 0.8831\n",
      "\n",
      "Epoch 3/11\n",
      "----------\n",
      "train Loss: 0.4555 Acc: 0.8446\n",
      "test Loss: 0.1787 Acc: 0.9351\n",
      "\n",
      "Epoch 4/11\n",
      "----------\n",
      "train Loss: 0.4937 Acc: 0.8358\n",
      "test Loss: 0.2237 Acc: 0.9740\n",
      "\n",
      "Epoch 5/11\n",
      "----------\n",
      "train Loss: 0.4140 Acc: 0.8475\n",
      "test Loss: 0.1751 Acc: 0.9481\n",
      "\n",
      "Epoch 6/11\n",
      "----------\n",
      "train Loss: 0.3172 Acc: 0.8886\n",
      "test Loss: 0.1864 Acc: 0.9091\n",
      "\n",
      "Epoch 7/11\n",
      "----------\n",
      "train Loss: 0.2870 Acc: 0.9120\n",
      "test Loss: 0.2114 Acc: 0.9091\n",
      "\n",
      "Epoch 8/11\n",
      "----------\n",
      "train Loss: 0.3029 Acc: 0.9120\n",
      "test Loss: 0.2046 Acc: 0.9221\n",
      "\n",
      "Epoch 9/11\n",
      "----------\n",
      "train Loss: 0.2704 Acc: 0.9091\n",
      "test Loss: 0.2000 Acc: 0.9091\n",
      "\n",
      "Epoch 10/11\n",
      "----------\n",
      "train Loss: 0.3203 Acc: 0.8827\n",
      "test Loss: 0.1762 Acc: 0.9091\n",
      "\n",
      "Epoch 11/11\n",
      "----------\n",
      "train Loss: 0.3068 Acc: 0.8886\n",
      "test Loss: 0.2632 Acc: 0.8831\n",
      "\n",
      "Training complete in 23m 38s\n",
      "Best val Acc: 0.974026\n"
     ]
    }
   ],
   "source": [
    "model_ft = train_model(model_ft, criterion, optimizer_ft, exp_lr_scheduler,\n",
    "                       num_epochs=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<svg height=\"93.471066pt\" version=\"1.1\" viewBox=\"0 0 165.81375 93.471066\" width=\"165.81375pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <metadata>\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n   <cc:Work>\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n    <dc:date>2021-06-22T13:22:05.924409</dc:date>\n    <dc:format>image/svg+xml</dc:format>\n    <dc:creator>\n     <cc:Agent>\n      <dc:title>Matplotlib v3.4.2, https://matplotlib.org/</dc:title>\n     </cc:Agent>\n    </dc:creator>\n   </cc:Work>\n  </rdf:RDF>\n </metadata>\n <defs>\n  <style 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\n"
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "visualize_model(model_ft)"
   ]
  },
  {
   "source": [
    "## 3 - Export Model"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [],
   "source": [
    "def save_model(model, model_dir):\n",
    "    path = os.path.join(model_dir, 'model.pth')\n",
    "    print(path)\n",
    "    torch.save(model.state_dict(), path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "./model/model.pth\n"
     ]
    }
   ],
   "source": [
    "save_model(model_ft, './model')"
   ]
  }
 ]
}