jan24_cds_mushrooms/notebooks/Data_Augmentation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator, img_to_array, load_img, array_to_img\n",
    "\n",
    "# Define the source and destination directories\n",
    "source_directory = 'path_to_your_images'\n",
    "augmented_directory = 'path_to_save_augmented_images'\n",
    "\n",
    "# Create the destination directory if it does not exist\n",
    "if not os.path.exists(augmented_directory):\n",
    "    os.makedirs(augmented_directory)\n",
    "\n",
    "# Initialize the ImageDataGenerator with augmentation parameters\n",
    "datagen = ImageDataGenerator(\n",
    "    rotation_range=40,\n",
    "    width_shift_range=0.2,\n",
    "    height_shift_range=0.2,\n",
    "    shear_range=0.2,\n",
    "    zoom_range=0.2,\n",
    "    horizontal_flip=True,\n",
    "    fill_mode='nearest'\n",
    ")\n",
    "\n",
    "# Function to augment and save images\n",
    "def augment_images(image_path, save_to_dir, prefix='aug', num_augmented_images=5):\n",
    "    img = load_img(image_path)  # Load image\n",
    "    x = img_to_array(img)  # Convert image to array\n",
    "    x = np.expand_dims(x, axis=0)  # Expand dimensions to match the input shape required by the generator\n",
    "\n",
    "    # Generate augmented images and save them\n",
    "    i = 0\n",
    "    for batch in datagen.flow(x, batch_size=1, save_to_dir=save_to_dir, save_prefix=prefix, save_format='jpeg'):\n",
    "        i += 1\n",
    "        if i >= num_augmented_images:\n",
    "            break\n",
    "\n",
    "# Loop over images in the source directory\n",
    "for filename in os.listdir(source_directory):\n",
    "    if filename.endswith(\".jpg\") or filename.endswith(\".png\"):\n",
    "        image_path = os.path.join(source_directory, filename)\n",
    "        augment_images(image_path, augmented_directory)\n",
    "\n",
    "print(\"Data augmentation completed!\")\n"
   ]
  }
 ],
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   "name": "python"
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