Upload 4 files

Final_classes.txt

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+all_purpose_flour
+almonds
+apple
+apricot
+asparagus
+avocado
+bacon
+banana
+barley
+basil
+basmati_rice
+beans
+beef
+beets
+bell_pepper
+berries
+biscuits
+blackberries
+black_pepper
+blueberries
+bread
+bread_crumbs
+bread_flour
+broccoli
+brownie_mix
+brown_rice
+butter
+cabbage
+cake
+cardamom
+carrot
+cashews
+cauliflower
+celery
+cereal
+cheese
+cherries
+chicken
+chickpeas
+chocolate
+chocolate_chips
+chocolate_syrup
+cilantro
+cinnamon
+clove
+cocoa_powder
+coconut
+cookies
+corn
+cucumber
+dates
+eggplant
+eggs
+fish
+garlic
+ginger
+grapes
+honey
+jalapeno
+kidney_beans
+lemon
+mango
+marshmallows
+milk
+mint
+muffins
+mushroom
+noodles
+nuts
+oats
+okra
+olive
+onion
+orange
+oreo_cookies
+pasta
+pear
+pepper
+pineapple
+pistachios
+pork
+potato
+pumpkin
+radishes
+raisins
+red_chilies
+rice
+rosemary
+salmon
+salt
+shrimp
+spinach
+strawberries
+sugar
+sweet_potato
+tomato
+vanilla_ice_cream
+walnuts
+watermelon
+yogurt

Initial_data_correction_n_augmentation.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Check for if class names in the txt file matches with the label dir "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Rename to bring the consistency"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Renamed 'all purpose flour' to 'all_purpose_flour'\n",
+      "Renamed 'basmati rice' to 'basmati_rice'\n",
+      "Renamed 'bell pepper' to 'bell_pepper'\n",
+      "Renamed 'black pepper' to 'black_pepper'\n",
+      "Renamed 'bread crumbs' to 'bread_crumbs'\n",
+      "Renamed 'bread flour' to 'bread_flour'\n",
+      "Renamed 'brown rice' to 'brown_rice'\n",
+      "Renamed 'brownie mix' to 'brownie_mix'\n",
+      "Renamed 'chocolate chips' to 'chocolate_chips'\n",
+      "Renamed 'chocolate syrup' to 'chocolate_syrup'\n",
+      "Renamed 'cocoa powder' to 'cocoa_powder'\n",
+      "Renamed 'kidney beans' to 'kidney_beans'\n",
+      "Renamed 'oreo cookies' to 'oreo_cookies'\n",
+      "Renamed 'red chilies' to 'red_chilies'\n",
+      "Renamed 'sweet potato' to 'sweet_potato'\n",
+      "Renamed 'vanilla ice cream' to 'vanilla_ice_cream'\n",
+      "Directory renaming completed.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "\n",
+    "def rename_directories(dataset_directory):\n",
+    "    for dirname in os.listdir(dataset_directory):\n",
+    "        current_dir_path = os.path.join(dataset_directory, dirname)\n",
+    "        if os.path.isdir(current_dir_path):\n",
+    "            new_dirname = dirname.replace(' ', '_')\n",
+    "            new_dir_path = os.path.join(dataset_directory, new_dirname)\n",
+    "            if current_dir_path != new_dir_path:  \n",
+    "                os.rename(current_dir_path, new_dir_path)\n",
+    "                print(f\"Renamed '{dirname}' to '{new_dirname}'\")\n",
+    "dataset_directory = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data'\n",
+    "rename_directories(dataset_directory)\n",
+    "\n",
+    "print(\"Directory renaming completed.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "All classes in 'Final_classes.txt' have corresponding directories in the dataset.\n",
+      "No extra directories in the dataset that are not listed in 'Final_classes.txt'.\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "# dataset directory and class names file\n",
+    "dataset_dir = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data'\n",
+    "class_names_file = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\Final_classes.txt'\n",
+    "\n",
+    "# Load class names from file\n",
+    "with open(class_names_file, 'r') as f:\n",
+    "    class_names = [line.strip().replace(' ', '_') for line in f]\n",
+    "\n",
+    "# Get a list of actual directory names in the dataset\n",
+    "actual_dirs = [d for d in os.listdir(dataset_dir) if os.path.isdir(os.path.join(dataset_dir, d))]\n",
+    "\n",
+    "# Check for discrepancies\n",
+    "missing_dirs = set(class_names) - set(actual_dirs)\n",
+    "extra_dirs = set(actual_dirs) - set(class_names)\n",
+    "\n",
+    "if missing_dirs:\n",
+    "    print(f\"Missing directories for classes in 'Final_classes.txt': {missing_dirs}\")\n",
+    "else:\n",
+    "    print(\"All classes in 'Final_classes.txt' have corresponding directories in the dataset.\")\n",
+    "\n",
+    "if extra_dirs:\n",
+    "    print(f\"Extra directories in the dataset that are not listed in 'Final_classes.txt': {extra_dirs}\")\n",
+    "else:\n",
+    "    print(\"No extra directories in the dataset that are not listed in 'Final_classes.txt'.\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Removing files other than jpg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "No non-JPG files found in the dataset.\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "def remove_non_jpg_images(dataset_dir):\n",
+    "    removed_files = []\n",
+    "    for root, dirs, files in os.walk(dataset_dir):\n",
+    "        for file in files:\n",
+    "            # Check if the file extension is not .jpg\n",
+    "            if not file.lower().endswith('.jpg'):\n",
+    "                file_path = os.path.join(root, file)\n",
+    "                os.remove(file_path)  # Remove the non-JPG file\n",
+    "                removed_files.append(file_path)\n",
+    "    return removed_files\n",
+    "\n",
+    "\n",
+    "dataset_dir = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data'\n",
+    "removed_files = remove_non_jpg_images(dataset_dir)\n",
+    "\n",
+    "if removed_files:\n",
+    "    print(f\"Removed {len(removed_files)} non-JPG files:\")\n",
+    "    for file in removed_files:\n",
+    "        print(file)\n",
+    "else:\n",
+    "    print(\"No non-JPG files found in the dataset.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "all_purpose_flour: 50 images\n",
+      "almonds: 50 images\n",
+      "apple: 50 images\n",
+      "apricot: 50 images\n",
+      "asparagus: 50 images\n",
+      "avocado: 50 images\n",
+      "bacon: 50 images\n",
+      "banana: 50 images\n",
+      "barley: 50 images\n",
+      "basil: 50 images\n",
+      "basmati_rice: 50 images\n",
+      "beans: 50 images\n",
+      "beef: 50 images\n",
+      "beets: 50 images\n",
+      "bell_pepper: 50 images\n",
+      "berries: 50 images\n",
+      "biscuits: 50 images\n",
+      "blackberries: 50 images\n",
+      "black_pepper: 50 images\n",
+      "blueberries: 50 images\n",
+      "bread: 50 images\n",
+      "bread_crumbs: 50 images\n",
+      "bread_flour: 50 images\n",
+      "broccoli: 50 images\n",
+      "brownie_mix: 50 images\n",
+      "brown_rice: 50 images\n",
+      "butter: 50 images\n",
+      "cabbage: 50 images\n",
+      "cake: 50 images\n",
+      "cardamom: 50 images\n",
+      "carrot: 50 images\n",
+      "cashews: 50 images\n",
+      "cauliflower: 50 images\n",
+      "celery: 50 images\n",
+      "cereal: 50 images\n",
+      "cheese: 50 images\n",
+      "cherries: 50 images\n",
+      "chicken: 50 images\n",
+      "chickpeas: 50 images\n",
+      "chocolate: 50 images\n",
+      "chocolate_chips: 50 images\n",
+      "chocolate_syrup: 50 images\n",
+      "cilantro: 50 images\n",
+      "cinnamon: 50 images\n",
+      "clove: 50 images\n",
+      "cocoa_powder: 50 images\n",
+      "coconut: 50 images\n",
+      "cookies: 50 images\n",
+      "corn: 50 images\n",
+      "cucumber: 50 images\n",
+      "dates: 50 images\n",
+      "eggplant: 50 images\n",
+      "eggs: 50 images\n",
+      "fish: 50 images\n",
+      "garlic: 50 images\n",
+      "ginger: 50 images\n",
+      "grapes: 50 images\n",
+      "honey: 50 images\n",
+      "jalapeno: 50 images\n",
+      "kidney_beans: 50 images\n",
+      "lemon: 50 images\n",
+      "mango: 50 images\n",
+      "marshmallows: 50 images\n",
+      "milk: 50 images\n",
+      "mint: 50 images\n",
+      "muffins: 50 images\n",
+      "mushroom: 50 images\n",
+      "noodles: 50 images\n",
+      "nuts: 50 images\n",
+      "oats: 50 images\n",
+      "okra: 50 images\n",
+      "olive: 50 images\n",
+      "onion: 50 images\n",
+      "orange: 50 images\n",
+      "oreo_cookies: 50 images\n",
+      "pasta: 50 images\n",
+      "pear: 50 images\n",
+      "pepper: 50 images\n",
+      "pineapple: 50 images\n",
+      "pistachios: 50 images\n",
+      "pork: 50 images\n",
+      "potato: 50 images\n",
+      "pumpkin: 50 images\n",
+      "radishes: 50 images\n",
+      "raisins: 50 images\n",
+      "red_chilies: 50 images\n",
+      "rice: 50 images\n",
+      "rosemary: 50 images\n",
+      "salmon: 50 images\n",
+      "salt: 50 images\n",
+      "shrimp: 50 images\n",
+      "spinach: 50 images\n",
+      "strawberries: 50 images\n",
+      "sugar: 50 images\n",
+      "sweet_potato: 50 images\n",
+      "tomato: 50 images\n",
+      "vanilla_ice_cream: 50 images\n",
+      "walnuts: 50 images\n",
+      "watermelon: 50 images\n",
+      "yogurt: 50 images\n",
+      "\n",
+      "Total images in dataset: 5000\n"
+     ]
+    }
+   ],
+   "source": [
+    "def count_images(dataset_dir):\n",
+    "    class_image_counts = {}\n",
+    "    for class_name in os.listdir(dataset_dir):\n",
+    "        class_dir = os.path.join(dataset_dir, class_name)\n",
+    "        if os.path.isdir(class_dir):\n",
+    "            image_count = sum(1 for file in os.listdir(class_dir) if file.lower().endswith('.jpg'))\n",
+    "            class_image_counts[class_name] = image_count\n",
+    "    return class_image_counts\n",
+    "\n",
+    "#\n",
+    "dataset_dir = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data'\n",
+    "image_counts = count_images(dataset_dir)\n",
+    "\n",
+    "# Print out the counts\n",
+    "for class_name, count in image_counts.items():\n",
+    "    print(f\"{class_name}: {count} images\")\n",
+    "\n",
+    "# Optional: total image count\n",
+    "total_images = sum(image_counts.values())\n",
+    "print(f\"\\nTotal images in dataset: {total_images}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- remove images that count is  more than 50 per class "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Class 'all_purpose_flour' meets the maximum image requirement.\n",
+      "Class 'almonds' meets the maximum image requirement.\n",
+      "Class 'apple' meets the maximum image requirement.\n",
+      "Class 'apricot' meets the maximum image requirement.\n",
+      "Class 'asparagus' meets the maximum image requirement.\n",
+      "Class 'avocado' meets the maximum image requirement.\n",
+      "Class 'bacon' meets the maximum image requirement.\n",
+      "Class 'banana' meets the maximum image requirement.\n",
+      "Class 'barley' meets the maximum image requirement.\n",
+      "Class 'basil' meets the maximum image requirement.\n",
+      "Class 'basmati_rice' meets the maximum image requirement.\n",
+      "Class 'beans' meets the maximum image requirement.\n",
+      "Class 'beef' meets the maximum image requirement.\n",
+      "Class 'beets' meets the maximum image requirement.\n",
+      "Class 'bell_pepper' meets the maximum image requirement.\n",
+      "Class 'berries' meets the maximum image requirement.\n",
+      "Class 'biscuits' meets the maximum image requirement.\n",
+      "Class 'blackberries' meets the maximum image requirement.\n",
+      "Class 'black_pepper' meets the maximum image requirement.\n",
+      "Class 'blueberries' meets the maximum image requirement.\n",
+      "Class 'bread' meets the maximum image requirement.\n",
+      "Class 'bread_crumbs' meets the maximum image requirement.\n",
+      "Class 'bread_flour' meets the maximum image requirement.\n",
+      "Class 'broccoli' meets the maximum image requirement.\n",
+      "Class 'brownie_mix' meets the maximum image requirement.\n",
+      "Class 'brown_rice' meets the maximum image requirement.\n",
+      "Class 'butter' meets the maximum image requirement.\n",
+      "Class 'cabbage' meets the maximum image requirement.\n",
+      "Class 'cake' meets the maximum image requirement.\n",
+      "Class 'cardamom' meets the maximum image requirement.\n",
+      "Class 'carrot' meets the maximum image requirement.\n",
+      "Class 'cashews' meets the maximum image requirement.\n",
+      "Class 'cauliflower' meets the maximum image requirement.\n",
+      "Class 'celery' meets the maximum image requirement.\n",
+      "Class 'cereal' meets the maximum image requirement.\n",
+      "Class 'cheese' meets the maximum image requirement.\n",
+      "Class 'cherries' meets the maximum image requirement.\n",
+      "Class 'chicken' meets the maximum image requirement.\n",
+      "Class 'chickpeas' meets the maximum image requirement.\n",
+      "Class 'chocolate' meets the maximum image requirement.\n",
+      "Class 'chocolate_chips' meets the maximum image requirement.\n",
+      "Class 'chocolate_syrup' meets the maximum image requirement.\n",
+      "Class 'cilantro' meets the maximum image requirement.\n",
+      "Class 'cinnamon' meets the maximum image requirement.\n",
+      "Class 'clove' meets the maximum image requirement.\n",
+      "Removed 15 images from 'cocoa_powder' to meet the maximum of 50 images.\n",
+      "Removed 57 images from 'coconut' to meet the maximum of 50 images.\n",
+      "Class 'cookies' meets the maximum image requirement.\n",
+      "Class 'corn' meets the maximum image requirement.\n",
+      "Class 'cucumber' meets the maximum image requirement.\n",
+      "Class 'dates' meets the maximum image requirement.\n",
+      "Class 'eggplant' meets the maximum image requirement.\n",
+      "Class 'eggs' meets the maximum image requirement.\n",
+      "Class 'fish' meets the maximum image requirement.\n",
+      "Class 'garlic' meets the maximum image requirement.\n",
+      "Class 'ginger' meets the maximum image requirement.\n",
+      "Class 'grapes' meets the maximum image requirement.\n",
+      "Class 'honey' meets the maximum image requirement.\n",
+      "Class 'jalapeno' meets the maximum image requirement.\n",
+      "Class 'kidney_beans' meets the maximum image requirement.\n",
+      "Class 'lemon' meets the maximum image requirement.\n",
+      "Class 'mango' meets the maximum image requirement.\n",
+      "Class 'marshmallows' meets the maximum image requirement.\n",
+      "Class 'milk' meets the maximum image requirement.\n",
+      "Class 'mint' meets the maximum image requirement.\n",
+      "Class 'muffins' meets the maximum image requirement.\n",
+      "Class 'mushroom' meets the maximum image requirement.\n",
+      "Class 'noodles' meets the maximum image requirement.\n",
+      "Class 'nuts' meets the maximum image requirement.\n",
+      "Class 'oats' meets the maximum image requirement.\n",
+      "Class 'okra' meets the maximum image requirement.\n",
+      "Class 'olive' meets the maximum image requirement.\n",
+      "Class 'onion' meets the maximum image requirement.\n",
+      "Class 'orange' meets the maximum image requirement.\n",
+      "Class 'oreo_cookies' meets the maximum image requirement.\n",
+      "Class 'pasta' meets the maximum image requirement.\n",
+      "Class 'pear' meets the maximum image requirement.\n",
+      "Class 'pepper' meets the maximum image requirement.\n",
+      "Class 'pineapple' meets the maximum image requirement.\n",
+      "Class 'pistachios' meets the maximum image requirement.\n",
+      "Class 'pork' meets the maximum image requirement.\n",
+      "Class 'potato' meets the maximum image requirement.\n",
+      "Class 'pumpkin' meets the maximum image requirement.\n",
+      "Class 'radishes' meets the maximum image requirement.\n",
+      "Class 'raisins' meets the maximum image requirement.\n",
+      "Class 'red_chilies' meets the maximum image requirement.\n",
+      "Class 'rice' meets the maximum image requirement.\n",
+      "Removed 8 images from 'rosemary' to meet the maximum of 50 images.\n",
+      "Removed 3 images from 'salmon' to meet the maximum of 50 images.\n",
+      "Removed 3 images from 'salt' to meet the maximum of 50 images.\n",
+      "Removed 9 images from 'shrimp' to meet the maximum of 50 images.\n",
+      "Removed 8 images from 'spinach' to meet the maximum of 50 images.\n",
+      "Removed 9 images from 'strawberries' to meet the maximum of 50 images.\n",
+      "Removed 8 images from 'sugar' to meet the maximum of 50 images.\n",
+      "Removed 9 images from 'sweet_potato' to meet the maximum of 50 images.\n",
+      "Removed 4 images from 'tomato' to meet the maximum of 50 images.\n",
+      "Removed 8 images from 'vanilla_ice_cream' to meet the maximum of 50 images.\n",
+      "Class 'walnuts' meets the maximum image requirement.\n",
+      "Class 'watermelon' meets the maximum image requirement.\n",
+      "Class 'yogurt' meets the maximum image requirement.\n",
+      "Image reduction completed.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import random\n",
+    "\n",
+    "def remove_images_if_more_than(dataset_dir, max_images=50):\n",
+    "    for class_name in os.listdir(dataset_dir):\n",
+    "        class_dir = os.path.join(dataset_dir, class_name)\n",
+    "        if os.path.isdir(class_dir):\n",
+    "            images = [file for file in os.listdir(class_dir) if file.lower().endswith('.jpg')]\n",
+    "            if len(images) > max_images:\n",
+    "                images_to_remove = random.sample(images, len(images) - max_images)\n",
+    "                for image in images_to_remove:\n",
+    "                    image_path = os.path.join(class_dir, image)\n",
+    "                    os.remove(image_path)\n",
+    "                print(f\"Removed {len(images_to_remove)} images from '{class_name}' to meet the maximum of {max_images} images.\")\n",
+    "            else:\n",
+    "                print(f\"Class '{class_name}' meets the maximum image requirement.\")\n",
+    "\n",
+    "# Specify the path to your dataset directory\n",
+    "dataset_dir = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data'\n",
+    "remove_images_if_more_than(dataset_dir, 50)\n",
+    "\n",
+    "print(\"Image reduction completed.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- augemnet to make every class contains count of 50"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting imgaug\n",
+      "  Downloading imgaug-0.4.0-py2.py3-none-any.whl.metadata (1.8 kB)\n",
+      "Requirement already satisfied: six in c:\\users\\kiyo\\appdata\\roaming\\python\\python312\\site-packages (from imgaug) (1.16.0)\n",
+      "Requirement already satisfied: numpy>=1.15 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from imgaug) (1.26.3)\n",
+      "Requirement already satisfied: scipy in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from imgaug) (1.12.0)\n",
+      "Requirement already satisfied: Pillow in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from imgaug) (10.2.0)\n",
+      "Requirement already satisfied: matplotlib in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from imgaug) (3.8.2)\n",
+      "Requirement already satisfied: scikit-image>=0.14.2 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from imgaug) (0.22.0)\n",
+      "Requirement already satisfied: opencv-python in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from imgaug) (4.9.0.80)\n",
+      "Requirement already satisfied: imageio in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from imgaug) (2.34.0)\n",
+      "Requirement already satisfied: Shapely in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from imgaug) (2.0.2)\n",
+      "Requirement already satisfied: networkx>=2.8 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from scikit-image>=0.14.2->imgaug) (3.2.1)\n",
+      "Requirement already satisfied: tifffile>=2022.8.12 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from scikit-image>=0.14.2->imgaug) (2024.2.12)\n",
+      "Requirement already satisfied: packaging>=21 in c:\\users\\kiyo\\appdata\\roaming\\python\\python312\\site-packages (from scikit-image>=0.14.2->imgaug) (23.2)\n",
+      "Requirement already satisfied: lazy_loader>=0.3 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from scikit-image>=0.14.2->imgaug) (0.3)\n",
+      "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib->imgaug) (1.2.0)\n",
+      "Requirement already satisfied: cycler>=0.10 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib->imgaug) (0.12.1)\n",
+      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib->imgaug) (4.47.2)\n",
+      "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib->imgaug) (1.4.5)\n",
+      "Requirement already satisfied: pyparsing>=2.3.1 in c:\\users\\kiyo\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib->imgaug) (3.1.1)\n",
+      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\kiyo\\appdata\\roaming\\python\\python312\\site-packages (from matplotlib->imgaug) (2.8.2)\n",
+      "Downloading imgaug-0.4.0-py2.py3-none-any.whl (948 kB)\n",
+      "   ---------------------------------------- 0.0/948.0 kB ? eta -:--:--\n",
+      "   ---------------------------------------- 10.2/948.0 kB ? eta -:--:--\n",
+      "   - ------------------------------------- 30.7/948.0 kB 660.6 kB/s eta 0:00:02\n",
+      "   ------ --------------------------------- 153.6/948.0 kB 1.5 MB/s eta 0:00:01\n",
+      "   ------------------------ --------------- 583.7/948.0 kB 4.6 MB/s eta 0:00:01\n",
+      "   ---------------------------------------- 948.0/948.0 kB 5.0 MB/s eta 0:00:00\n",
+      "Installing collected packages: imgaug\n",
+      "Successfully installed imgaug-0.4.0\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "DEPRECATION: celery 4.2.0 has a non-standard dependency specifier pytz>dev. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of celery or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install imgaug\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Completed augmentation for class 'all_purpose_flour'.\n",
+      "Completed augmentation for class 'almonds'.\n",
+      "Completed augmentation for class 'apple'.\n",
+      "Completed augmentation for class 'apricot'.\n",
+      "Completed augmentation for class 'asparagus'.\n",
+      "Completed augmentation for class 'avocado'.\n",
+      "Completed augmentation for class 'bacon'.\n",
+      "Completed augmentation for class 'banana'.\n",
+      "Completed augmentation for class 'barley'.\n",
+      "Completed augmentation for class 'basil'.\n",
+      "Completed augmentation for class 'basmati_rice'.\n",
+      "Completed augmentation for class 'beans'.\n",
+      "Completed augmentation for class 'beef'.\n",
+      "Completed augmentation for class 'beets'.\n",
+      "Completed augmentation for class 'bell_pepper'.\n",
+      "Completed augmentation for class 'berries'.\n",
+      "Completed augmentation for class 'biscuits'.\n",
+      "Completed augmentation for class 'blackberries'.\n",
+      "Completed augmentation for class 'black_pepper'.\n",
+      "Completed augmentation for class 'blueberries'.\n",
+      "Completed augmentation for class 'bread'.\n",
+      "Completed augmentation for class 'bread_crumbs'.\n",
+      "Completed augmentation for class 'bread_flour'.\n",
+      "Completed augmentation for class 'broccoli'.\n",
+      "Completed augmentation for class 'brownie_mix'.\n",
+      "Completed augmentation for class 'brown_rice'.\n",
+      "Completed augmentation for class 'butter'.\n",
+      "Completed augmentation for class 'cabbage'.\n",
+      "Completed augmentation for class 'cake'.\n",
+      "Completed augmentation for class 'cardamom'.\n",
+      "Completed augmentation for class 'carrot'.\n",
+      "Completed augmentation for class 'cashews'.\n",
+      "Completed augmentation for class 'cauliflower'.\n",
+      "Completed augmentation for class 'celery'.\n",
+      "Completed augmentation for class 'cereal'.\n",
+      "Completed augmentation for class 'cheese'.\n",
+      "Completed augmentation for class 'cherries'.\n",
+      "Completed augmentation for class 'chicken'.\n",
+      "Completed augmentation for class 'chickpeas'.\n",
+      "Completed augmentation for class 'chocolate'.\n",
+      "Completed augmentation for class 'chocolate_chips'.\n",
+      "Completed augmentation for class 'chocolate_syrup'.\n",
+      "Completed augmentation for class 'cilantro'.\n",
+      "Completed augmentation for class 'cinnamon'.\n",
+      "Completed augmentation for class 'clove'.\n",
+      "Completed augmentation for class 'cocoa_powder'.\n",
+      "Completed augmentation for class 'coconut'.\n",
+      "Completed augmentation for class 'cookies'.\n",
+      "Completed augmentation for class 'corn'.\n",
+      "Completed augmentation for class 'cucumber'.\n",
+      "Completed augmentation for class 'dates'.\n",
+      "Completed augmentation for class 'eggplant'.\n",
+      "Completed augmentation for class 'eggs'.\n",
+      "Completed augmentation for class 'fish'.\n",
+      "Completed augmentation for class 'garlic'.\n",
+      "Completed augmentation for class 'ginger'.\n",
+      "Completed augmentation for class 'grapes'.\n",
+      "Completed augmentation for class 'honey'.\n",
+      "Completed augmentation for class 'jalapeno'.\n",
+      "Completed augmentation for class 'kidney_beans'.\n",
+      "Completed augmentation for class 'lemon'.\n",
+      "Completed augmentation for class 'mango'.\n",
+      "Completed augmentation for class 'marshmallows'.\n",
+      "Completed augmentation for class 'milk'.\n",
+      "Completed augmentation for class 'mint'.\n",
+      "Completed augmentation for class 'muffins'.\n",
+      "Completed augmentation for class 'mushroom'.\n",
+      "Completed augmentation for class 'noodles'.\n",
+      "Completed augmentation for class 'nuts'.\n",
+      "Completed augmentation for class 'oats'.\n",
+      "Completed augmentation for class 'okra'.\n",
+      "Completed augmentation for class 'olive'.\n",
+      "Completed augmentation for class 'onion'.\n",
+      "Completed augmentation for class 'orange'.\n",
+      "Completed augmentation for class 'oreo_cookies'.\n",
+      "Completed augmentation for class 'pasta'.\n",
+      "Completed augmentation for class 'pear'.\n",
+      "Completed augmentation for class 'pepper'.\n",
+      "Completed augmentation for class 'pineapple'.\n",
+      "Completed augmentation for class 'pistachios'.\n",
+      "Completed augmentation for class 'pork'.\n",
+      "Completed augmentation for class 'potato'.\n",
+      "Completed augmentation for class 'pumpkin'.\n",
+      "Completed augmentation for class 'radishes'.\n",
+      "Completed augmentation for class 'raisins'.\n",
+      "Completed augmentation for class 'red_chilies'.\n",
+      "Completed augmentation for class 'rice'.\n",
+      "Completed augmentation for class 'rosemary'.\n",
+      "Completed augmentation for class 'salmon'.\n",
+      "Completed augmentation for class 'salt'.\n",
+      "Completed augmentation for class 'shrimp'.\n",
+      "Completed augmentation for class 'spinach'.\n",
+      "Completed augmentation for class 'strawberries'.\n",
+      "Completed augmentation for class 'sugar'.\n",
+      "Completed augmentation for class 'sweet_potato'.\n",
+      "Completed augmentation for class 'tomato'.\n",
+      "Completed augmentation for class 'vanilla_ice_cream'.\n",
+      "Completed augmentation for class 'walnuts'.\n",
+      "Completed augmentation for class 'watermelon'.\n",
+      "Completed augmentation for class 'yogurt'.\n",
+      "Dataset augmentation completed.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import random\n",
+    "from PIL import Image\n",
+    "import imgaug as ia\n",
+    "import imgaug.augmenters as iaa\n",
+    "import numpy as np\n",
+    "\n",
+    "ia.seed(1)\n",
+    "\n",
+    "def augment_image(image_path, save_dir, augmentation, img_count):\n",
+    "    image = Image.open(image_path)\n",
+    "    # Convert image to RGB if it's not already in that format\n",
+    "    if image.mode != 'RGB':\n",
+    "        image = image.convert('RGB')\n",
+    "    image_np = np.array(image)\n",
+    "    augmented_image_np = augmentation(image=image_np)\n",
+    "    augmented_image = Image.fromarray(augmented_image_np)\n",
+    "    base_name = os.path.basename(image_path)\n",
+    "    new_image_path = os.path.join(save_dir, f\"{os.path.splitext(base_name)[0]}_aug_{img_count}.jpg\")\n",
+    "    augmented_image.save(new_image_path)\n",
+    "\n",
+    "\n",
+    "def augment_class_images(class_dir, target_count=50):\n",
+    "    images = [file for file in os.listdir(class_dir) if file.lower().endswith('.jpg')]\n",
+    "    current_count = len(images)\n",
+    "    \n",
+    "    augmentation = iaa.Sequential([\n",
+    "        iaa.Fliplr(0.5),  # Horizontally flip 50% of the images\n",
+    "        iaa.Crop(percent=(0, 0.1)),  # Perform random crops\n",
+    "        \n",
+    "        # Apply affine transformations\n",
+    "        iaa.Affine(\n",
+    "            scale={\"x\": (0.8, 1.2), \"y\": (0.8, 1.2)},\n",
+    "            translate_percent={\"x\": (-0.2, 0.2), \"y\": (-0.2, 0.2)},\n",
+    "            rotate=(-25, 25),\n",
+    "            shear=(-8, 8)\n",
+    "        ),\n",
+    "        \n",
+    "        # Adjust brightness and contrast\n",
+    "        iaa.Multiply((0.8, 1.2)),  # Change brightness (80-120% of original value)\n",
+    "        iaa.LinearContrast((0.75, 1.5)),  # Strengthen or weaken the contrast in each image.\n",
+    "        \n",
+    "        # Apply color temperature changes\n",
+    "        iaa.Sequential([\n",
+    "            iaa.ChangeColorTemperature((1100, 10000)),  # Simulate different color temperatures\n",
+    "            iaa.WithChannels(0, iaa.Add((10, 100)))  # Optionally, add more red for warmth\n",
+    "        ], random_order=True)  # Apply these changes in a random order\n",
+    "    ])\n",
+    "    \n",
+    "    if current_count < target_count:\n",
+    "        while current_count < target_count:\n",
+    "            for img_file in random.sample(images, min(len(images), target_count - current_count)):\n",
+    "                augment_image(os.path.join(class_dir, img_file), class_dir, augmentation, current_count)\n",
+    "                current_count += 1\n",
+    "                if current_count >= target_count:\n",
+    "                    break\n",
+    "\n",
+    "def augment_dataset_if_needed(dataset_dir, target_count=50):\n",
+    "    for class_name in os.listdir(dataset_dir):\n",
+    "        class_dir = os.path.join(dataset_dir, class_name)\n",
+    "        if os.path.isdir(class_dir):\n",
+    "            augment_class_images(class_dir, target_count)\n",
+    "            print(f\"Completed augmentation for class '{class_name}'.\")\n",
+    "\n",
+    "# Specify the path to your dataset directory\n",
+    "dataset_dir = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data'\n",
+    "augment_dataset_if_needed(dataset_dir, 50)\n",
+    "\n",
+    "print(\"Dataset augmentation completed.\")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

correction_for_augmented data.ipynb

@@ -0,0 +1,567 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Check for the corrections in the augmented data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "import os\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Class 'all_purpose_flour_annotated': Perfect\n",
+      "Class 'almonds_annotated': Perfect\n",
+      "Class 'apple_annotated': Perfect\n",
+      "Class 'apricot_annotated': Perfect\n",
+      "Class 'asparagus_annotated': Perfect\n",
+      "Class 'avocado_annotated': Perfect\n",
+      "Class 'bacon_annotated': Perfect\n",
+      "Class 'banana_annotated': Perfect\n",
+      "Class 'barley_annotated': Perfect\n",
+      "Class 'basil_annotated': Perfect\n",
+      "Class 'basmati_rice_annotated': Perfect\n",
+      "Class 'beans_annotated': Perfect\n",
+      "Class 'beef_annotated': Perfect\n",
+      "Class 'beets_annotated': Perfect\n",
+      "Class 'bell_pepper_annotated': Perfect\n",
+      "Class 'berries_annotated': Perfect\n",
+      "Class 'biscuits_annotated': Perfect\n",
+      "Class 'blackberries_annotated': Perfect\n",
+      "Class 'black_pepper_annotated': Perfect\n",
+      "Class 'blueberries_annotated': Perfect\n",
+      "Class 'bread_annotated': Perfect\n",
+      "Class 'bread_crumbs_annotated': Perfect\n",
+      "Class 'bread_flour_annotated': Perfect\n",
+      "Class 'broccoli_annotated': Perfect\n",
+      "Class 'brownie_mix_annotated': Perfect\n",
+      "Class 'brown_rice_annotated': Perfect\n",
+      "Class 'butter_annotated': Perfect\n",
+      "Class 'cabbage_annotated': Perfect\n",
+      "Class 'cake_annotated': Perfect\n",
+      "Class 'cardamom_annotated': Perfect\n",
+      "Class 'carrot_annotated': Perfect\n",
+      "Class 'cashews_annotated': Perfect\n",
+      "Class 'cauliflower_annotated': Perfect\n",
+      "Class 'celery_annotated': Perfect\n",
+      "Class 'cereal_annotated': Perfect\n",
+      "Class 'cheese_annotated': Perfect\n",
+      "Class 'cherries_annotated': Perfect\n",
+      "Class 'chicken_annotated': Perfect\n",
+      "Class 'chickpeas_annotated': Perfect\n",
+      "Class 'chocolate_annotated': Perfect\n",
+      "Class 'chocolate_chips_annotated': Perfect\n",
+      "Class 'chocolate_syrup_annotated': Perfect\n",
+      "Class 'cilantro_annotated': Perfect\n",
+      "Class 'cinnamon_annotated': Perfect\n",
+      "Class 'clove_annotated': Perfect\n",
+      "Class 'cocoa_powder_annotated': Perfect\n",
+      "Class 'coconut_annotated': Perfect\n",
+      "Class 'cookies_annotated': Perfect\n",
+      "Class 'corn_annotated': Perfect\n",
+      "Class 'cucumber_annotated': Perfect\n",
+      "Class 'dates_annotated': Perfect\n",
+      "Class 'eggplant_annotated': Perfect\n",
+      "Class 'eggs_annotated': Perfect\n",
+      "Class 'fish_annotated': Perfect\n",
+      "Class 'garlic_annotated': Perfect\n",
+      "Class 'ginger_annotated': Perfect\n",
+      "Class 'grapes_annotated': Perfect\n",
+      "Class 'honey_annotated': Perfect\n",
+      "Class 'jalapeno_annotated': Perfect\n",
+      "Class 'kidney_beans_annotated': Perfect\n",
+      "Class 'lemon_annotated': Perfect\n",
+      "Class 'mango_annotated': Perfect\n",
+      "Class 'marshmallows_annotated': Perfect\n",
+      "Class 'milk_annotated': Perfect\n",
+      "Class 'mint_annotated': Perfect\n",
+      "Class 'muffins_annotated': Perfect\n",
+      "Class 'mushroom_annotated': Perfect\n",
+      "Class 'noodles_annotated': Perfect\n",
+      "Class 'nuts_annotated': Perfect\n",
+      "Class 'oats_annotated': Perfect\n",
+      "Class 'okra_annotated': Perfect\n",
+      "Class 'olive_annotated': Perfect\n",
+      "Class 'onion_annotated': Perfect\n",
+      "Class 'orange_annotated': Perfect\n",
+      "Class 'oreo_cookies_annotated': Perfect\n",
+      "Class 'pasta_annotated': Perfect\n",
+      "Class 'pear_annotated': Perfect\n",
+      "Class 'pepper_annotated': Perfect\n",
+      "Class 'pineapple_annotated': Perfect\n",
+      "Class 'pistachios_annotated': Perfect\n",
+      "Class 'pork_annotated': Perfect\n",
+      "Class 'potato_annotated': Perfect\n",
+      "Class 'pumpkin_annotated': Perfect\n",
+      "Class 'radishes_annotated': Perfect\n",
+      "Class 'raisins_annotated': Perfect\n",
+      "Class 'red_chilies_annotated': Discrepancies Found\n",
+      "  Missing JPG files for: Image_21\n",
+      "  Non-JPG/XML files: Image_21.JPG\n",
+      "Class 'rice_annotated': Discrepancies Found\n",
+      "  Missing JPG files for: Image_30\n",
+      "  Non-JPG/XML files: Image_30.JPG\n",
+      "Class 'rosemary_annotated': Discrepancies Found\n",
+      "  Missing JPG files for: Image_26\n",
+      "  Non-JPG/XML files: Image_26.JPG\n",
+      "Class 'salmon_annotated': Perfect\n",
+      "Class 'salt_annotated': Perfect\n",
+      "Class 'shrimp_annotated': Discrepancies Found\n",
+      "  Missing JPG files for: Image_16, Image_17\n",
+      "  Non-JPG/XML files: Image_16.JPG, Image_17.JPG\n",
+      "Class 'spinach_annotated': Discrepancies Found\n",
+      "  Missing JPG files for: Image_27\n",
+      "  Non-JPG/XML files: Image_27.JPG\n",
+      "Class 'strawberries_annotated': Discrepancies Found\n",
+      "  Missing JPG files for: Image_10, Image_20\n",
+      "  Non-JPG/XML files: Image_10.JPG, Image_20.JPG\n",
+      "Class 'sugar_annotated': Perfect\n",
+      "Class 'sweet_potato_annotated': Discrepancies Found\n",
+      "  Missing JPG files for: Image_15, Image_21\n",
+      "  Non-JPG/XML files: Image_15.JPG, Image_21.JPG\n",
+      "Class 'tomato_annotated': Perfect\n",
+      "Class 'vanilla_ice_cream_annotated': Discrepancies Found\n",
+      "  Missing JPG files for: Image_12, Image_15, Image_17, Image_20\n",
+      "  Non-JPG/XML files: Image_12.JPG, Image_15.JPG, Image_17.JPG, Image_20.JPG\n",
+      "Class 'walnuts_annotated': Perfect\n",
+      "Class 'watermelon_annotated': Perfect\n",
+      "Class 'yogurt_annotated': Perfect\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "\n",
+    "def check_dataset_integrity(dataset_directory):\n",
+    "    for class_name in os.listdir(dataset_directory):\n",
+    "        class_path = os.path.join(dataset_directory, class_name)\n",
+    "        if os.path.isdir(class_path):\n",
+    "            jpg_files = set()\n",
+    "            xml_files = set()\n",
+    "            other_files = set()\n",
+    "\n",
+    "            # Collect file names for each extension\n",
+    "            for file_name in os.listdir(class_path):\n",
+    "                if file_name.endswith('.jpg'):\n",
+    "                    jpg_files.add(os.path.splitext(file_name)[0])\n",
+    "                elif file_name.endswith('.xml'):\n",
+    "                    xml_files.add(os.path.splitext(file_name)[0])\n",
+    "                else:\n",
+    "                    other_files.add(file_name)\n",
+    "\n",
+    "            # Check for discrepancies\n",
+    "            missing_xmls = jpg_files - xml_files\n",
+    "            missing_jpgs = xml_files - jpg_files\n",
+    "            is_perfect = len(missing_xmls) == 0 and len(missing_jpgs) == 0 and len(other_files) == 0\n",
+    "\n",
+    "            # Report\n",
+    "            print(f\"Class '{class_name}':\", \"Perfect\" if is_perfect else \"Discrepancies Found\")\n",
+    "            if missing_xmls:\n",
+    "                print(f\"  Missing XML files for: {', '.join(sorted(missing_xmls))}\")\n",
+    "            if missing_jpgs:\n",
+    "                print(f\"  Missing JPG files for: {', '.join(sorted(missing_jpgs))}\")\n",
+    "            if other_files:\n",
+    "                print(f\"  Non-JPG/XML files: {', '.join(sorted(other_files))}\")\n",
+    "        else:\n",
+    "            print(f\"'{class_name}' is not a directory. Skipping.\")\n",
+    "\n",
+    "# Specify the path to the dataset directory\n",
+    "dataset_directory = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated'\n",
+    "check_dataset_integrity(dataset_directory)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "def count_files_in_classes(dataset_directory):\n",
+    "    # Iterate over all items in dataset_directory\n",
+    "    for item in os.listdir(dataset_directory):\n",
+    "        item_path = os.path.join(dataset_directory, item)\n",
+    "        # Check if the item is a directory\n",
+    "        if os.path.isdir(item_path):\n",
+    "            # List all files in the directory\n",
+    "            files = [f for f in os.listdir(item_path) if os.path.isfile(os.path.join(item_path, f))]\n",
+    "            # Print the count of files\n",
+    "            if len(files) < 100:\n",
+    "                print(f\"{item}: {len(files)} files\")\n",
+    "\n",
+    "dataset_directory = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated'\n",
+    "count_files_in_classes(dataset_directory)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\all_purpose_flour_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\all_purpose_flour'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\almonds_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\almonds'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\apple_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\apple'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\apricot_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\apricot'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\asparagus_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\asparagus'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\avocado_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\avocado'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bacon_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bacon'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\banana_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\banana'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\barley_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\barley'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\basil_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\basil'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\basmati_rice_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\basmati_rice'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\beans_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\beans'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\beef_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\beef'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\beets_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\beets'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bell_pepper_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bell_pepper'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\berries_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\berries'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\biscuits_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\biscuits'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\blackberries_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\blackberries'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\black_pepper_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\black_pepper'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\blueberries_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\blueberries'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bread_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bread'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bread_crumbs_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bread_crumbs'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bread_flour_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\bread_flour'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\broccoli_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\broccoli'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\brownie_mix_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\brownie_mix'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\brown_rice_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\brown_rice'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\butter_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\butter'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cabbage_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cabbage'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cake_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cake'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cardamom_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cardamom'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\carrot_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\carrot'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cashews_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cashews'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cauliflower_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cauliflower'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\celery_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\celery'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cereal_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cereal'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cheese_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cheese'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cherries_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cherries'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chicken_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chicken'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chickpeas_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chickpeas'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chocolate_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chocolate'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chocolate_chips_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chocolate_chips'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chocolate_syrup_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\chocolate_syrup'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cilantro_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cilantro'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cinnamon_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cinnamon'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\clove_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\clove'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cocoa_powder_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cocoa_powder'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\coconut_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\coconut'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cookies_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cookies'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\corn_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\corn'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cucumber_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\cucumber'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\dates_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\dates'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\eggplant_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\eggplant'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\eggs_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\eggs'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\fish_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\fish'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\garlic_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\garlic'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\ginger_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\ginger'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\grapes_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\grapes'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\honey_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\honey'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\jalapeno_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\jalapeno'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\kidney_beans_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\kidney_beans'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\lemon_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\lemon'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\mango_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\mango'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\marshmallows_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\marshmallows'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\milk_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\milk'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\mint_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\mint'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\muffins_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\muffins'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\mushroom_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\mushroom'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\noodles_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\noodles'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\nuts_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\nuts'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\oats_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\oats'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\okra_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\okra'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\olive_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\olive'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\onion_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\onion'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\orange_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\orange'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\oreo_cookies_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\oreo_cookies'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pasta_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pasta'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pear_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pear'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pepper_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pepper'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pineapple_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pineapple'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pistachios_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pistachios'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pork_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pork'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\potato_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\potato'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pumpkin_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\pumpkin'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\radishes_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\radishes'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\raisins_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\raisins'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\red_chilies_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\red_chilies'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\rice_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\rice'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\rosemary_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\rosemary'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\salmon_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\salmon'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\salt_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\salt'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\shrimp_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\shrimp'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\spinach_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\spinach'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\strawberries_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\strawberries'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\sugar_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\sugar'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\sweet_potato_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\sweet_potato'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\tomato_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\tomato'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\vanilla_ice_cream_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\vanilla_ice_cream'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\walnuts_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\walnuts'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\watermelon_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\watermelon'.\n",
+      "Renamed 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\yogurt_annotated' to 'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated\\yogurt'.\n",
+      "Directory renaming completed.\n"
+     ]
+    }
+   ],
+   "source": [
+    "def rename_directories(base_dir):\n",
+    "    for dirname in os.listdir(base_dir):\n",
+    "        if dirname.endswith('_annotated'):\n",
+    "            original_dir_path = os.path.join(base_dir, dirname)\n",
+    "            new_dirname = dirname.replace('_annotated', '')\n",
+    "            new_dir_path = os.path.join(base_dir, new_dirname)\n",
+    "            \n",
+    "            # Check if the target directory already exists\n",
+    "            if os.path.exists(new_dir_path):\n",
+    "                print(f\"Target directory '{new_dir_path}' already exists. Skipping '{dirname}'.\")\n",
+    "                continue\n",
+    "            \n",
+    "            os.rename(original_dir_path, new_dir_path)\n",
+    "            print(f\"Renamed '{original_dir_path}' to '{new_dir_path}'.\")\n",
+    "\n",
+    "# Specify the base directory containing the class directories to be renamed\n",
+    "base_dir = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated'\n",
+    "rename_directories(base_dir)\n",
+    "\n",
+    "print(\"Directory renaming completed.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Class 'all_purpose_flour': Perfect\n",
+      "Class 'almonds': Perfect\n",
+      "Class 'apple': Perfect\n",
+      "Class 'apricot': Perfect\n",
+      "Class 'asparagus': Perfect\n",
+      "Class 'avocado': Perfect\n",
+      "Class 'bacon': Perfect\n",
+      "Class 'banana': Perfect\n",
+      "Class 'barley': Perfect\n",
+      "Class 'basil': Perfect\n",
+      "Class 'basmati_rice': Perfect\n",
+      "Class 'beans': Perfect\n",
+      "Class 'beef': Perfect\n",
+      "Class 'beets': Perfect\n",
+      "Class 'bell_pepper': Perfect\n",
+      "Class 'berries': Perfect\n",
+      "Class 'biscuits': Perfect\n",
+      "Class 'blackberries': Perfect\n",
+      "Class 'black_pepper': Perfect\n",
+      "Class 'blueberries': Perfect\n",
+      "Class 'bread': Perfect\n",
+      "Class 'bread_crumbs': Perfect\n",
+      "Class 'bread_flour': Perfect\n",
+      "Class 'broccoli': Perfect\n",
+      "Class 'brownie_mix': Perfect\n",
+      "Class 'brown_rice': Perfect\n",
+      "Class 'butter': Perfect\n",
+      "Class 'cabbage': Perfect\n",
+      "Class 'cake': Perfect\n",
+      "Class 'cardamom': Perfect\n",
+      "Class 'carrot': Perfect\n",
+      "Class 'cashews': Perfect\n",
+      "Class 'cauliflower': Perfect\n",
+      "Class 'celery': Perfect\n",
+      "Class 'cereal': Perfect\n",
+      "Class 'cheese': Perfect\n",
+      "Class 'cherries': Perfect\n",
+      "Class 'chicken': Perfect\n",
+      "Class 'chickpeas': Perfect\n",
+      "Class 'chocolate': Perfect\n",
+      "Class 'chocolate_chips': Perfect\n",
+      "Class 'chocolate_syrup': Perfect\n",
+      "Class 'cilantro': Perfect\n",
+      "Class 'cinnamon': Perfect\n",
+      "Class 'clove': Perfect\n",
+      "Class 'cocoa_powder': Perfect\n",
+      "Class 'coconut': Perfect\n",
+      "Class 'cookies': Perfect\n",
+      "Class 'corn': Perfect\n",
+      "Class 'cucumber': Perfect\n",
+      "Class 'dates': Perfect\n",
+      "Class 'eggplant': Perfect\n",
+      "Class 'eggs': Perfect\n",
+      "Class 'fish': Perfect\n",
+      "Class 'garlic': Perfect\n",
+      "Class 'ginger': Perfect\n",
+      "Class 'grapes': Perfect\n",
+      "Class 'honey': Perfect\n",
+      "Class 'jalapeno': Perfect\n",
+      "Class 'kidney_beans': Perfect\n",
+      "Class 'lemon': Perfect\n",
+      "Class 'mango': Perfect\n",
+      "Class 'marshmallows': Perfect\n",
+      "Class 'milk': Perfect\n",
+      "Class 'mint': Perfect\n",
+      "Class 'muffins': Perfect\n",
+      "Class 'mushroom': Perfect\n",
+      "Class 'noodles': Perfect\n",
+      "Class 'nuts': Perfect\n",
+      "Class 'oats': Perfect\n",
+      "Class 'okra': Perfect\n",
+      "Class 'olive': Perfect\n",
+      "Class 'onion': Perfect\n",
+      "Class 'orange': Perfect\n",
+      "Class 'oreo_cookies': Perfect\n",
+      "Class 'pasta': Perfect\n",
+      "Class 'pear': Perfect\n",
+      "Class 'pepper': Perfect\n",
+      "Class 'pineapple': Perfect\n",
+      "Class 'pistachios': Perfect\n",
+      "Class 'pork': Perfect\n",
+      "Class 'potato': Perfect\n",
+      "Class 'pumpkin': Perfect\n",
+      "Class 'radishes': Perfect\n",
+      "Class 'raisins': Perfect\n",
+      "Class 'red_chilies': Perfect\n",
+      "Class 'rice': Perfect\n",
+      "Class 'rosemary': Perfect\n",
+      "Class 'salmon': Perfect\n",
+      "Class 'salt': Perfect\n",
+      "Class 'shrimp': Perfect\n",
+      "Class 'spinach': Perfect\n",
+      "Class 'strawberries': Perfect\n",
+      "Class 'sugar': Perfect\n",
+      "Class 'sweet_potato': Perfect\n",
+      "Class 'tomato': Perfect\n",
+      "Class 'vanilla_ice_cream': Perfect\n",
+      "Class 'walnuts': Perfect\n",
+      "Class 'watermelon': Perfect\n",
+      "Class 'yogurt': Perfect\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "\n",
+    "def check_dataset_integrity(dataset_directory):\n",
+    "    for class_name in os.listdir(dataset_directory):\n",
+    "        class_path = os.path.join(dataset_directory, class_name)\n",
+    "        if os.path.isdir(class_path):\n",
+    "            jpg_files = set()\n",
+    "            xml_files = set()\n",
+    "            other_files = set()\n",
+    "\n",
+    "            # Collect file names for each extension\n",
+    "            for file_name in os.listdir(class_path):\n",
+    "                if file_name.endswith('.jpg'):\n",
+    "                    jpg_files.add(os.path.splitext(file_name)[0])\n",
+    "                elif file_name.endswith('.xml'):\n",
+    "                    xml_files.add(os.path.splitext(file_name)[0])\n",
+    "                else:\n",
+    "                    other_files.add(file_name)\n",
+    "\n",
+    "            # Check for discrepancies\n",
+    "            missing_xmls = jpg_files - xml_files\n",
+    "            missing_jpgs = xml_files - jpg_files\n",
+    "            is_perfect = len(missing_xmls) == 0 and len(missing_jpgs) == 0 and len(other_files) == 0\n",
+    "\n",
+    "            # Report\n",
+    "            print(f\"Class '{class_name}':\", \"Perfect\" if is_perfect else \"Discrepancies Found\")\n",
+    "            if missing_xmls:\n",
+    "                print(f\"  Missing XML files for: {', '.join(sorted(missing_xmls))}\")\n",
+    "            if missing_jpgs:\n",
+    "                print(f\"  Missing JPG files for: {', '.join(sorted(missing_jpgs))}\")\n",
+    "            if other_files:\n",
+    "                print(f\"  Non-JPG/XML files: {', '.join(sorted(other_files))}\")\n",
+    "        else:\n",
+    "            print(f\"'{class_name}' is not a directory. Skipping.\")\n",
+    "\n",
+    "# Specify the path to the dataset directory\n",
+    "dataset_directory = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated'\n",
+    "check_dataset_integrity(dataset_directory)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "All class names from 'Final_classes.txt' match the dataset directories perfectly.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "\n",
+    "# Path to the directory containing the class directories\n",
+    "dataset_dir = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\initial_data_annotated'\n",
+    "\n",
+    "# Path to the file containing the final class names\n",
+    "classes_file = r'C:\\Users\\Kiyo\\Desktop\\DL\\Project\\image_data\\Final_classes.txt'\n",
+    "\n",
+    "# Load class names from file\n",
+    "with open(classes_file, 'r') as f:\n",
+    "    class_names = {line.strip() for line in f}\n",
+    "\n",
+    "# List directory names in the dataset\n",
+    "dataset_dirs = {d for d in os.listdir(dataset_dir) if os.path.isdir(os.path.join(dataset_dir, d))}\n",
+    "\n",
+    "# Find discrepancies\n",
+    "missing_dirs = class_names - dataset_dirs\n",
+    "extra_dirs = dataset_dirs - class_names\n",
+    "\n",
+    "# Report results\n",
+    "if not missing_dirs and not extra_dirs:\n",
+    "    print(\"All class names from 'Final_classes.txt' match the dataset directories perfectly.\")\n",
+    "else:\n",
+    "    if missing_dirs:\n",
+    "        print(f\"Missing directories for these classes: {', '.join(sorted(missing_dirs))}\")\n",
+    "    if extra_dirs:\n",
+    "        print(f\"Extra directories in the dataset not listed in 'Final_classes.txt': {', '.join(sorted(extra_dirs))}\")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}