From dfc0ec5ee8a4a34a72279c8cf5a517f6e7eecd7a Mon Sep 17 00:00:00 2001 From: Shambhavi Mishra <42893001+ShambhaviCodes@users.noreply.github.com> Date: Sun, 9 Aug 2020 00:15:11 +0530 Subject: [PATCH 1/4] Add Image_Augmentation --- Ch14_Computer_Vision/Image_Augmentation.ipynb | 178 ++++++++++++++++++ 1 file changed, 178 insertions(+) create mode 100644 Ch14_Computer_Vision/Image_Augmentation.ipynb diff --git a/Ch14_Computer_Vision/Image_Augmentation.ipynb b/Ch14_Computer_Vision/Image_Augmentation.ipynb new file mode 100644 index 00000000..c970752c --- /dev/null +++ b/Ch14_Computer_Vision/Image_Augmentation.ipynb @@ -0,0 +1,178 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "Image_Augmentation.ipynb", + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "Snhu_azo7fsM", + "colab_type": "text" + }, + "source": [ + "# Image Augmentation" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rTLdv_H27bBa", + "colab_type": "text" + }, + "source": [ + "Image augmentation technology expands the scale of training datasets by making a series of random changes to the training images to produce similar, but different, training examples. Another way to explain image augmentation is that randomly changing training examples can reduce a model's dependence on certain properties, thereby improving its capability for generalization. For example, we can crop the images in different ways, so that the objects of interest appear in different positions, reducing the model's dependence on the position where objects appear. We can also adjust the brightness, color, and other factors to reduce model's sensitivity to color. It can be said that image augmentation technology contributed greatly to the success of AlexNet. In this section, we will discuss this technology, which is widely used in computer vision." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2Ic6XMusTkB5", + "colab_type": "text" + }, + "source": [ + "Let's start with importing necessary libraries." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "_U0WGY0p8xpY", + "colab_type": "code", + "colab": {} + }, + "source": [ + "import PIL\n", + "from PIL import Image\n", + "import numpy as np\n", + "import torch\n", + "import torchvision" + ], + "execution_count": 1, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Pjamf0FQUNc4", + "colab_type": "text" + }, + "source": [ + "We will apply the following transforms to an image using 'torchvision.transforms' :\n", + "\n", + "\n", + "* Resize the image to (224, 224)\n", + "* Hue and Saturation to (0.05)\n", + "* Horizontal Flip\n", + "* Rotation\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "KQj8i59__qyc", + "colab_type": "code", + "colab": {} + }, + "source": [ + "transforms = torchvision.transforms.Compose([\n", + " torchvision.transforms.Resize((224,224)),\n", + " torchvision.transforms.ColorJitter(hue=.05, saturation=.05),\n", + " torchvision.transforms.RandomHorizontalFlip(),\n", + " torchvision.transforms.RandomRotation(20, resample=PIL.Image.BILINEAR)\n", + "])" + ], + "execution_count": 2, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "I7yR8ruINMxn", + "colab_type": "code", + "colab": {} + }, + "source": [ + "img = Image.open(\"/content/drive/My Drive/Dataset/7.jpg\")" + ], + "execution_count": 3, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "K5UG9uy-OHo4", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 241 + }, + "outputId": "297305b0-9e79-477d-f183-71a3c15d9b12" + }, + "source": [ + "transforms(img)" + ], + "execution_count": 4, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 4 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "SoUkqlSAWBwJ", + "colab_type": "text" + }, + "source": [ + "We can see the augmentation in the image. These transforms are very basic, one may utilise libraries such as [imgaug](https://github.com/aleju/imgaug) for more interesting transformations." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "cqyi2TnEXhIJ", + "colab_type": "text" + }, + "source": [ + "## Summary \n", + "Image Augmentation is the process of generating new images for training our deep learning model. It helps in expanding the dataset and helps in a more robust training to perform more accurately." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "N57zPuNeX1NY", + "colab_type": "text" + }, + "source": [ + "## Exercise\n", + "\n", + "Perform Image Classification and compare the performance of Image Classification Model for dataset with augmentation." + ] + } + ] +} \ No newline at end of file From 46c1d660e7d96b1b57bb4d3cab1ce90746b4f73f Mon Sep 17 00:00:00 2001 From: Shambhavi Mishra <42893001+ShambhaviCodes@users.noreply.github.com> Date: Sun, 9 Aug 2020 00:20:03 +0530 Subject: [PATCH 2/4] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 3ce82bc0..55a3cb40 100644 --- a/README.md +++ b/README.md @@ -105,7 +105,7 @@ Note: Some ipynb notebooks may not be rendered perfectly in Github. We suggest ` * 12.9 Adadelta * 12.10 Adam * **Ch14 Computer Vision** - * 14.1 Image Augmentation + * 14.1 [Image Augmentation](https://github.com/ShambhaviCodes/d2l-pytorch/blob/master/Ch14_Computer_Vision/Image_Augmentation.ipynb) * 14.2 Fine Tuning * 14.3 [Object Detection and Bounding Boxes](https://github.com/dsgiitr/d2l-pytorch/blob/master/Ch14_Computer_Vision/Object_Detection_and_Bounding_Boxes.ipynb) * 14.4 [Anchor Boxes](https://github.com/dsgiitr/d2l-pytorch/blob/master/Ch14_Computer_Vision/Anchor_Boxes.ipynb) From e0d08c5b9d933261d84f7fe400dd7cf3c7a76a51 Mon Sep 17 00:00:00 2001 From: Shambhavi Mishra <42893001+ShambhaviCodes@users.noreply.github.com> Date: Sat, 15 Aug 2020 00:50:13 +0530 Subject: [PATCH 3/4] Delete Image_Augmentation.ipynb --- Ch14_Computer_Vision/Image_Augmentation.ipynb | 178 ------------------ 1 file changed, 178 deletions(-) delete mode 100644 Ch14_Computer_Vision/Image_Augmentation.ipynb diff --git a/Ch14_Computer_Vision/Image_Augmentation.ipynb b/Ch14_Computer_Vision/Image_Augmentation.ipynb deleted file mode 100644 index c970752c..00000000 --- a/Ch14_Computer_Vision/Image_Augmentation.ipynb +++ /dev/null @@ -1,178 +0,0 @@ -{ - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "name": "Image_Augmentation.ipynb", - "provenance": [] - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "accelerator": "GPU" - }, - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Snhu_azo7fsM", - "colab_type": "text" - }, - "source": [ - "# Image Augmentation" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "rTLdv_H27bBa", - "colab_type": "text" - }, - "source": [ - "Image augmentation technology expands the scale of training datasets by making a series of random changes to the training images to produce similar, but different, training examples. Another way to explain image augmentation is that randomly changing training examples can reduce a model's dependence on certain properties, thereby improving its capability for generalization. For example, we can crop the images in different ways, so that the objects of interest appear in different positions, reducing the model's dependence on the position where objects appear. We can also adjust the brightness, color, and other factors to reduce model's sensitivity to color. It can be said that image augmentation technology contributed greatly to the success of AlexNet. In this section, we will discuss this technology, which is widely used in computer vision." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2Ic6XMusTkB5", - "colab_type": "text" - }, - "source": [ - "Let's start with importing necessary libraries." - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "_U0WGY0p8xpY", - "colab_type": "code", - "colab": {} - }, - "source": [ - "import PIL\n", - "from PIL import Image\n", - "import numpy as np\n", - "import torch\n", - "import torchvision" - ], - "execution_count": 1, - "outputs": [] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Pjamf0FQUNc4", - "colab_type": "text" - }, - "source": [ - "We will apply the following transforms to an image using 'torchvision.transforms' :\n", - "\n", - "\n", - "* Resize the image to (224, 224)\n", - "* Hue and Saturation to (0.05)\n", - "* Horizontal Flip\n", - "* Rotation\n", - "\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "KQj8i59__qyc", - "colab_type": "code", - "colab": {} - }, - "source": [ - "transforms = torchvision.transforms.Compose([\n", - " torchvision.transforms.Resize((224,224)),\n", - " torchvision.transforms.ColorJitter(hue=.05, saturation=.05),\n", - " torchvision.transforms.RandomHorizontalFlip(),\n", - " torchvision.transforms.RandomRotation(20, resample=PIL.Image.BILINEAR)\n", - "])" - ], - "execution_count": 2, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "I7yR8ruINMxn", - "colab_type": "code", - "colab": {} - }, - "source": [ - "img = Image.open(\"/content/drive/My Drive/Dataset/7.jpg\")" - ], - "execution_count": 3, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "K5UG9uy-OHo4", - "colab_type": "code", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 241 - }, - "outputId": "297305b0-9e79-477d-f183-71a3c15d9b12" - }, - "source": [ - "transforms(img)" - ], - "execution_count": 4, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "image/png": 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\n", - "text/plain": [ - "" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 4 - } - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "SoUkqlSAWBwJ", - "colab_type": "text" - }, - "source": [ - "We can see the augmentation in the image. These transforms are very basic, one may utilise libraries such as [imgaug](https://github.com/aleju/imgaug) for more interesting transformations." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "cqyi2TnEXhIJ", - "colab_type": "text" - }, - "source": [ - "## Summary \n", - "Image Augmentation is the process of generating new images for training our deep learning model. It helps in expanding the dataset and helps in a more robust training to perform more accurately." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "N57zPuNeX1NY", - "colab_type": "text" - }, - "source": [ - "## Exercise\n", - "\n", - "Perform Image Classification and compare the performance of Image Classification Model for dataset with augmentation." - ] - } - ] -} \ No newline at end of file From 7f725a783661bc8e3cc60f19f429528118bdecaf Mon Sep 17 00:00:00 2001 From: Shambhavi Mishra <42893001+ShambhaviCodes@users.noreply.github.com> Date: Sat, 15 Aug 2020 00:52:01 +0530 Subject: [PATCH 4/4] Adding Image Augmetation --- Ch14_Computer_Vision/Image_Augmentation.ipynb | 445 ++++++++++++++++++ 1 file changed, 445 insertions(+) create mode 100644 Ch14_Computer_Vision/Image_Augmentation.ipynb diff --git a/Ch14_Computer_Vision/Image_Augmentation.ipynb b/Ch14_Computer_Vision/Image_Augmentation.ipynb new file mode 100644 index 00000000..2b77e5ae --- /dev/null +++ b/Ch14_Computer_Vision/Image_Augmentation.ipynb @@ -0,0 +1,445 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "Image_Augmentation.ipynb", + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "1QLSUl2cPmqk", + "colab_type": "text" + }, + "source": [ + "# Image Augmentation\n", + "Image augmentation technology expands the scale of training datasets\n", + "by making a series of random changes to the training images to produce similar,\n", + "but different, training examples. Another way to explain image augmentation is\n", + "that randomly changing training examples can reduce a model's dependence on\n", + "certain properties, thereby improving its capability for generalization. For\n", + "example, we can crop the images in different ways, so that the objects of\n", + "interest appear in different positions, reducing the model's dependence on the\n", + "position where objects appear. We can also adjust the brightness, color, and\n", + "other factors to reduce model's sensitivity to color. It can be said that image\n", + "augmentation technology contributed greatly to the success of AlexNet. In this\n", + "section, we will discuss this technology, which is widely used in computer\n", + "vision.\n", + "\n", + "First, import the packages or modules required for the experiment in this section." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "V833oFFA93jA", + "colab_type": "code", + "colab": {} + }, + "source": [ + "import torch \n", + "import torch.nn as nn\n", + "import torchvision\n", + "import torchvision.transforms as transforms\n", + "import PIL\n", + "from PIL import Image" + ], + "execution_count": 1, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UIDqgJsTQTAc", + "colab_type": "text" + }, + "source": [ + "# Common Image Augmentation Method\n", + "We will apply the following transforms to an image using 'torchvision.transforms' :\n", + "\n", + "\n", + "\n", + "* Resize the image to (224, 224)\n", + "* We can randomly change the hue and saturation of the image\n", + "* We can also create a RandomColorJitter instance and set how to randomly change the brightness, contrast, saturation, and hue of the image at the same time. \n", + "* Horizontal Flip\n", + "* Rotation\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "mj98T_1sQOfX", + "colab_type": "code", + "colab": {} + }, + "source": [ + "transforms = torchvision.transforms.Compose([\n", + " torchvision.transforms.Resize((224,224)),\n", + " torchvision.transforms.ColorJitter(hue=.10, saturation=.55),\n", + " torchvision.transforms.RandomHorizontalFlip(),\n", + " torchvision.transforms.RandomRotation(20, resample=PIL.Image.BILINEAR)\n", + "])" + ], + "execution_count": 2, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "9Kb5c_j-P1BE", + "colab_type": "code", + "colab": {} + }, + "source": [ + "img = Image.open(\"/content/apple.jpeg\")" + ], + "execution_count": 3, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "RZmWLaY7SOc4", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 241 + }, + "outputId": "1f38c8dc-9272-45b8-d9e4-3f07ca17e20f" + }, + "source": [ + "transforms(img)" + ], + "execution_count": 4, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 4 + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Bawyz8FHUHSR", + "colab_type": "text" + }, + "source": [ + "# Using an Image Augmentation Training Model\n", + "Next, we will look at how to apply image augmentation in actual training. Here, we use the MNIST dataset to observe the model performance on dataset of augmented images." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "WdEJ57Sy-AmF", + "colab_type": "code", + "colab": {} + }, + "source": [ + "transform_train = torchvision.transforms.Compose([\n", + " torchvision.transforms.ColorJitter(hue=.10, saturation=.55),\n", + " torchvision.transforms.RandomHorizontalFlip(),\n", + " torchvision.transforms.RandomRotation(40, resample=PIL.Image.BILINEAR),\n", + " torchvision.transforms.ToTensor()\n", + "])\n", + "\n", + "transform_test = torchvision.transforms.Compose([\n", + " torchvision.transforms.ToTensor()\n", + "])" + ], + "execution_count": 5, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-jVCSvGSUwc0", + "colab_type": "text" + }, + "source": [ + "In order to obtain definitive results during prediction, we usually only apply image augmentation to the training example, and do not use image augmentation with random operations during prediction. Here, we use resize, color jitter, rotation and random horizontal flipping method. In addition, we use a `ToTensor` instance to convert minibatch images into the format required by PyTorch." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "vxCj7lWwMXHG", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Device configuration\n", + "device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')" + ], + "execution_count": 6, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rZWPgTZ9V8T0", + "colab_type": "text" + }, + "source": [ + "We can set the hyper parameters for the model." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "c7NURcRJMXy6", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Hyper parameters\n", + "num_epochs = 5\n", + "num_classes = 10\n", + "batch_size = 100\n", + "learning_rate = 0.001" + ], + "execution_count": 7, + "outputs": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "otT3Ub7gWDwH", + "colab_type": "text" + }, + "source": [ + "We download the dataset and create DataLoaders for test set and train set." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "o9Uif2Z3JHrU", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# MNIST dataset\n", + "train_dataset = torchvision.datasets.MNIST(root='../../data/',\n", + " train=True, \n", + " transform=transform_train,\n", + " download=True)\n", + "\n", + "test_dataset = torchvision.datasets.MNIST(root='../../data/',\n", + " train=False, \n", + " transform=transform_test)\n", + "\n", + "# Data loader\n", + "train_loader = torch.utils.data.DataLoader(dataset=train_dataset,\n", + " batch_size=batch_size, \n", + " shuffle=True)\n", + "\n", + "test_loader = torch.utils.data.DataLoader(dataset=test_dataset,\n", + " batch_size=batch_size, \n", + " shuffle=False)" + ], + "execution_count": 8, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "Dyvf5Qh2M1mB", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Convolutional neural network (two convolutional layers)\n", + "class ConvNet(nn.Module):\n", + " def __init__(self, num_classes=10):\n", + " super(ConvNet, self).__init__()\n", + " self.layer1 = nn.Sequential(\n", + " nn.Conv2d(1, 16, kernel_size=5, stride=1, padding=2),\n", + " nn.BatchNorm2d(16),\n", + " nn.ReLU(),\n", + " nn.MaxPool2d(kernel_size=2, stride=2))\n", + " self.layer2 = nn.Sequential(\n", + " nn.Conv2d(16, 32, kernel_size=5, stride=1, padding=2),\n", + " nn.BatchNorm2d(32),\n", + " nn.ReLU(),\n", + " nn.MaxPool2d(kernel_size=2, stride=2))\n", + " self.fc = nn.Linear(7*7*32, num_classes)\n", + " \n", + " def forward(self, x):\n", + " out = self.layer1(x)\n", + " out = self.layer2(out)\n", + " out = out.reshape(out.size(0), -1)\n", + " out = self.fc(out)\n", + " return out\n", + "\n", + "model = ConvNet(num_classes).to(device)" + ], + "execution_count": 9, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "4Kz0ODLsEtiT", + "colab_type": "code", + "colab": {} + }, + "source": [ + "# Loss and optimizer\n", + "criterion = nn.CrossEntropyLoss()\n", + "optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)" + ], + "execution_count": 10, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "1IzDkL13M82i", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 521 + }, + "outputId": "791f04fd-7ccc-4ac0-8dce-7ed0b207a88d" + }, + "source": [ + "# Train the model\n", + "total_step = len(train_loader)\n", + "for epoch in range(num_epochs):\n", + " for i, (images, labels) in enumerate(train_loader):\n", + " images = images.to(device)\n", + " labels = labels.to(device)\n", + " \n", + " # Forward pass\n", + " outputs = model(images)\n", + " loss = criterion(outputs, labels)\n", + " \n", + " # Backward and optimize\n", + " optimizer.zero_grad()\n", + " loss.backward()\n", + " optimizer.step()\n", + " \n", + " if (i+1) % 100 == 0:\n", + " print ('Epoch [{}/{}], Step [{}/{}], Loss: {:.4f}' \n", + " .format(epoch+1, num_epochs, i+1, total_step, loss.item()))" + ], + "execution_count": 11, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Epoch [1/5], Step [100/600], Loss: 0.5863\n", + "Epoch [1/5], Step [200/600], Loss: 0.2191\n", + "Epoch [1/5], Step [300/600], Loss: 0.3434\n", + "Epoch [1/5], Step [400/600], Loss: 0.2428\n", + "Epoch [1/5], Step [500/600], Loss: 0.2102\n", + "Epoch [1/5], Step [600/600], Loss: 0.3019\n", + "Epoch [2/5], Step [100/600], Loss: 0.3036\n", + "Epoch [2/5], Step [200/600], Loss: 0.2419\n", + "Epoch [2/5], Step [300/600], Loss: 0.2189\n", + "Epoch [2/5], Step [400/600], Loss: 0.2131\n", + "Epoch [2/5], Step [500/600], Loss: 0.1447\n", + "Epoch [2/5], Step [600/600], Loss: 0.3064\n", + "Epoch [3/5], Step [100/600], Loss: 0.1166\n", + "Epoch [3/5], Step [200/600], Loss: 0.1930\n", + "Epoch [3/5], Step [300/600], Loss: 0.1506\n", + "Epoch [3/5], Step [400/600], Loss: 0.1399\n", + "Epoch [3/5], Step [500/600], Loss: 0.2541\n", + "Epoch [3/5], Step [600/600], Loss: 0.1431\n", + "Epoch [4/5], Step [100/600], Loss: 0.2039\n", + "Epoch [4/5], Step [200/600], Loss: 0.1451\n", + "Epoch [4/5], Step [300/600], Loss: 0.2032\n", + "Epoch [4/5], Step [400/600], Loss: 0.2130\n", + "Epoch [4/5], Step [500/600], Loss: 0.1343\n", + "Epoch [4/5], Step [600/600], Loss: 0.2140\n", + "Epoch [5/5], Step [100/600], Loss: 0.2033\n", + "Epoch [5/5], Step [200/600], Loss: 0.1511\n", + "Epoch [5/5], Step [300/600], Loss: 0.1760\n", + "Epoch [5/5], Step [400/600], Loss: 0.1979\n", + "Epoch [5/5], Step [500/600], Loss: 0.1957\n", + "Epoch [5/5], Step [600/600], Loss: 0.1357\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "sAuHgHQBNAr3", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "outputId": "a9ce4848-9dca-42b2-9582-72f2451e7e3c" + }, + "source": [ + "# Test the model\n", + "model.eval() # eval mode (batchnorm uses moving mean/variance instead of mini-batch mean/variance)\n", + "with torch.no_grad():\n", + " correct = 0\n", + " total = 0\n", + " for images, labels in test_loader:\n", + " images = images.to(device)\n", + " labels = labels.to(device)\n", + " outputs = model(images)\n", + " _, predicted = torch.max(outputs.data, 1)\n", + " total += labels.size(0)\n", + " correct += (predicted == labels).sum().item()\n", + "\n", + " print('Test Accuracy of the model on the 10000 test images: {} %'.format(100 * correct / total))" + ], + "execution_count": 12, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Test Accuracy of the model on the 10000 test images: 96.03 %\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TBNmZoIGXXcU", + "colab_type": "text" + }, + "source": [ + "## Summary\n", + "\n", + "* Image augmentation generates random images based on existing training data to cope with overfitting.\n", + "* In order to obtain definitive results during prediction, we usually only apply image augmentation to the training example, and do not use image augmentation with random operations during prediction.\n", + "* We can obtain classes related to image augmentation from PyTorch's `transforms` module." + ] + } + ] +} \ No newline at end of file