Audio_Image_Search_Demo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ad1609e4-0b49-4dfb-bc27-a9825a77962c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import random\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "import cv2\n",
    "import glob\n",
    "import copy\n",
    "from skimage.feature import hog\n",
    "from pathlib import Path\n",
    "import random\n",
    "from sklearn.linear_model import SGDClassifier\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.pipeline import make_pipeline\n",
    "import pickle\n",
    "import librosa\n",
    "\n",
    "import gradio as gr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "460fa7c6-5d81-4099-925a-33013debc3b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_model(path):\n",
    "    with open(path, 'rb') as f:\n",
    "        clf = pickle.load(f)\n",
    "        return clf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "50a81ff1-3250-44c5-a9b8-0bf0c587f5c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_hog(img_array = None):\n",
    "  gray_img = cv2.cvtColor(((img_array)*255),cv2.COLOR_RGB2GRAY)\n",
    "  hog_features, hog_image = hog(gray_img, orientations=8, pixels_per_cell=(4, 4),cells_per_block=(1, 1), visualize=True)\n",
    "  return hog_features, hog_image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c512db6c-31bb-49fd-896f-bf12fd7ab216",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_sift(img_array = None, num_features = 10):\n",
    "  sift_final_des = np.zeros((num_features,128), dtype = np.float64)\n",
    "  gray_img = cv2.cvtColor(((img_array)*255),cv2.COLOR_RGB2GRAY)\n",
    "  sift = cv2.SIFT_create()\n",
    "  sift_kp, sift_des = sift.detectAndCompute(gray_img.astype('uint8'),None)\n",
    "  if sift_des is None:\n",
    "    sift_des = np.zeros((num_features,128), dtype = np.float64)\n",
    "  sift_des = np.nan_to_num(sift_des, nan=0, posinf=0, neginf=0)\n",
    "  max_des = np.max(sift_des)\n",
    "  max_des = 1\n",
    "  if max_des is None or max_des == 0:\n",
    "    max_des = 1\n",
    "  sift_des_norm = sift_des/max_des\n",
    "  sift_final_des[0:min(sift_des_norm.shape[0], num_features) , :] = sift_des_norm[0:min(sift_des_norm.shape[0], num_features) , :]\n",
    "  return sift_final_des"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f45b003b-0802-4106-8fda-235e6bad637d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_all_features(img, aud):\n",
    "    img_file = cv2.imread(img)\n",
    "    hog_features, hog_image = get_hog(img_array = img_file)\n",
    "    #print(len(hog_features))\n",
    "    sift_features = get_sift(img_array = img_file, num_features = 10)\n",
    "    is0,is1 = sift_features.shape\n",
    "    sift_features = sift_features.reshape(is0*is1)\n",
    "    #print(sift_features.shape)\n",
    "    \n",
    "    y, sr = librosa.load(aud)\n",
    "    mfccs = librosa.feature.mfcc(y=y, sr=sr)\n",
    "    as0,as1 = mfccs.shape\n",
    "    mfccs = mfccs.reshape(as0*as1)\n",
    "    #print(mfccs.shape)\n",
    "\n",
    "    if len(hog_features) > 40000:\n",
    "        hog_features = hog_features[0:40000]\n",
    "    else:\n",
    "        pad_length = 40000 - len(hog_features)\n",
    "        hog_features = np.pad(hog_features, (0, pad_length), 'constant')\n",
    "\n",
    "    if len(mfccs) > 300:\n",
    "        mfccs = mfccs[0:300]\n",
    "    else:\n",
    "        pad_length = 300 - len(mfccs)\n",
    "        mfccs = np.pad(mfccs, (0, pad_length), 'constant')\n",
    "    \n",
    "    features = np.concatenate((hog_features, sift_features,mfccs), axis=None).reshape(1,-1)\n",
    "    return features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c6dda596-792c-4aee-bf91-79274fc8e1ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "aud_probe = '/home/ubuntu/food-101-small/Probe/hamburger/hamburger.wav'\n",
    "y, sr = librosa.load(aud_probe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bffb070d-b550-4138-a2a1-5210c8be2b06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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\" type=\"audio/x-wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Audio\n",
    "\n",
    "Audio(aud_probe, rate=sr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "147adefd-55e7-49cd-a353-e03da773828c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def search(Audio, Gallery):\n",
    "    clf = load_model('/home/ubuntu/model.pkl')\n",
    "    default_img = '/home/ubuntu/food-101-small/Other/No_Image_Available.jpg'\n",
    "    print(\"Model Loaded Successfully and Searching....\", flush=True)\n",
    "    gallery_all_list = glob.glob(Gallery + '/*')\n",
    "    #print(Audio)\n",
    "    for gitem in gallery_all_list:\n",
    "        for img in glob.glob(gitem + '/*.jpg'):\n",
    "            X = get_all_features(img, Audio)\n",
    "            y_pred = clf.predict(X)\n",
    "            #print(y_pred)\n",
    "            if y_pred[0] == 1:\n",
    "                print(\"Search Completed - Matching Image Found\")\n",
    "                return img, Audio\n",
    "            break\n",
    "    print(\"Search Completed - No Matching Image Found\")\n",
    "    return default_img, Audio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f76d2ba1-1651-4c82-a957-a82dfdcab450",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Loaded Successfully and Searching....\n",
      "Search Completed - Matching Image Found\n"
     ]
    }
   ],
   "source": [
    "img, audio = search('/home/ubuntu/food-101-small/Probe/churros/churros.wav', '/home/ubuntu/food-101-small/Gallery')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ba811d9-cc42-4291-b558-c4172721c660",
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Case1 : Match Found\n",
    "\n",
    "Audio : /home/ubuntu/food-101-small/Probe/churros/churros.wav\n",
    "Gallery : /home/ubuntu/food-101-small/Gallery\n",
    "\n",
    "Case2 : No Match Found\n",
    "\n",
    "Audio : /home/ubuntu/food-101-small/Probe/hamburger/hamburger.wav\n",
    "Gallery : /home/ubuntu/food-101-small/Gallery\n",
    "\n",
    "Case 3 : Incorrect Match Found\n",
    "\n",
    "Audio : /home/ubuntu/food-101-small/Probe/chicken_curry/chicken_curry.wav\n",
    "Gallery : /home/ubuntu/food-101-small/Gallery\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7ab39eb2-7b3a-4bd0-bf73-94fbe198c5b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7860\n",
      "Running on public URL: https://cdaca6f1e552e36e6c.gradio.live\n",
      "\n",
      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"https://cdaca6f1e552e36e6c.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model Loaded Successfully and Searching....\n",
      "Search Completed - Matching Image Found\n",
      "Model Loaded Successfully and Searching....\n",
      "Search Completed - Matching Image Found\n",
      "Model Loaded Successfully and Searching....\n",
      "Search Completed - No Matching Image Found\n",
      "Model Loaded Successfully and Searching....\n",
      "Search Completed - Matching Image Found\n",
      "Model Loaded Successfully and Searching....\n",
      "Search Completed - No Matching Image Found\n",
      "Model Loaded Successfully and Searching....\n",
      "Search Completed - Matching Image Found\n",
      "Model Loaded Successfully and Searching....\n",
      "Search Completed - Matching Image Found\n"
     ]
    }
   ],
   "source": [
    "import gradio as gr\n",
    "\n",
    "demo = gr.Interface(\n",
    "    title=\"See with Sound: Image Retrieval Redefined!\",\n",
    "    fn=search,\n",
    "    inputs=[\"text\", \"text\"],\n",
    "    outputs=[\"image\", \"audio\"],\n",
    ")\n",
    "demo.launch(share=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c4ddf9b-fd82-4d2a-8e86-b62efdbf840f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}