camera_model1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import cv2\n",
    "from tensorflow.keras.preprocessing import image\n",
    "from tensorflow.keras.models import load_model\n",
    "from tensorflow.keras.utils import image_dataset_from_directory\n",
    "import tkinter as tk\n",
    "from tkinter import filedialog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dir = 'train'\n",
    "train_dataset = image_dataset_from_directory(\n",
    "    train_dir,\n",
    ")\n",
    "classes = train_dataset.class_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = \"from_camera.jpg\"\n",
    "modelname = \"first_model.keras\"\n",
    "\n",
    "def capture_image():\n",
    "    cam = cv2.VideoCapture(0)\n",
    "    cv2.namedWindow(\"Dog Breed Prediction\")\n",
    "\n",
    "    while True:\n",
    "        ret, frame = cam.read()\n",
    "        if not ret:\n",
    "            print(\"Failed to grab frame\")\n",
    "            break\n",
    "\n",
    "        cv2.imshow(\"Dog Breed Prediction\", frame)\n",
    "\n",
    "        if cv2.waitKey(1) & 0xFF == 13:\n",
    "            cv2.imwrite(filename, frame)\n",
    "            print(\"Image captured!\")\n",
    "            break\n",
    "\n",
    "    cam.release()\n",
    "    cv2.destroyAllWindows()\n",
    "\n",
    "def preprocess_image(img_path, img_size):\n",
    "    img = image.load_img(img_path, target_size=img_size)\n",
    "    img_array = image.img_to_array(img)\n",
    "    img_array = np.expand_dims(img_array, axis=0)\n",
    "    img_array /= 255.0\n",
    "    return img_array\n",
    "\n",
    "def predict_breed(model, img_array):\n",
    "    predictions = model.predict(img_array)\n",
    "    predicted_breed = np.argmax(predictions, axis=1)\n",
    "    return predicted_breed\n",
    "\n",
    "def use_existing_image():\n",
    "    global filename\n",
    "    filename = filedialog.askopenfilename(title=\"Select an Image\", filetypes=[(\"Image Files\", \"*.jpg;*.png\")])\n",
    "    if not filename:\n",
    "        print(\"No file selected\")\n",
    "        return False\n",
    "    return True\n",
    "\n",
    "def center_window(window, width, height):\n",
    "    screen_width = window.winfo_screenwidth()\n",
    "    screen_height = window.winfo_screenheight()\n",
    "\n",
    "    x = (screen_width // 2) - (width // 2)\n",
    "    y = (screen_height // 2) - (height // 2)\n",
    "\n",
    "    window.geometry(f'{width}x{height}+{x}+{y}')\n",
    "\n",
    "def main():\n",
    "    def on_button_click(choice):\n",
    "        if choice == \"capture\":\n",
    "            capture_image()\n",
    "        elif choice == \"existing\" and use_existing_image():\n",
    "            pass\n",
    "        else:\n",
    "            return\n",
    "        \n",
    "        window.destroy()\n",
    "        \n",
    "        img_size = (224, 224)\n",
    "        img_array = preprocess_image(filename, img_size)\n",
    "        \n",
    "        plt.imshow(img_array[0])\n",
    "        plt.axis(\"off\")\n",
    "        plt.show()\n",
    "\n",
    "        model = load_model(modelname)\n",
    "        \n",
    "        predicted_breed = predict_breed(model, img_array)\n",
    "        print(f\"Predicted Breed: {classes[predicted_breed[0]]}\")\n",
    "\n",
    "    window = tk.Tk()\n",
    "    window.title(\"Dog Breed Prediction\")\n",
    "    window.config(bg=\"lightblue\")\n",
    "    \n",
    "    center_window(window, 400, 200)\n",
    "\n",
    "    label = tk.Label(window, text=\"Choose an option:\", background=\"lightblue\", font=(\"Consolas\", 18))\n",
    "    label.pack(pady=10)\n",
    "\n",
    "    capture_button = tk.Button(window, background=\"#ffa343\", text=\"Capture Image\", font=(\"Consolas\", 14), width=20, command=lambda: on_button_click(\"capture\"))\n",
    "    capture_button.pack(pady=10)\n",
    "\n",
    "    existing_button = tk.Button(window, background=\"#50c878\", text=\"Use Existing Image\", font=(\"Consolas\", 14), width=20, command=lambda: on_button_click(\"existing\"))\n",
    "    existing_button.pack(pady=10)\n",
    "\n",
    "    window.mainloop()\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    main()"
   ]
  }
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