Upload Gradio Examples.ipynb

Gradio Examples.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "09eb5ef2",
+   "metadata": {},
+   "source": [
+    "#### Gradio Comparing Transfer Learning Models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "f3f83569",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2.12.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "import tensorflow as tf\n",
+    "print(tf.__version__)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "c1ca8b20",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting gradio==1.6.0\n",
+      "  Downloading gradio-1.6.0-py3-none-any.whl (1.1 MB)\n",
+      "                                              0.0/1.1 MB ? eta -:--:--\n",
+      "     ----                                     0.1/1.1 MB 3.2 MB/s eta 0:00:01\n",
+      "     ------------                             0.3/1.1 MB 4.2 MB/s eta 0:00:01\n",
+      "     ----------------------                   0.6/1.1 MB 5.6 MB/s eta 0:00:01\n",
+      "     -------------------------------          0.9/1.1 MB 5.6 MB/s eta 0:00:01\n",
+      "     -------------------------------------    1.0/1.1 MB 5.1 MB/s eta 0:00:01\n",
+      "     -------------------------------------    1.0/1.1 MB 5.1 MB/s eta 0:00:01\n",
+      "     ---------------------------------------- 1.1/1.1 MB 3.8 MB/s eta 0:00:00\n",
+      "Requirement already satisfied: numpy in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (1.24.3)\n",
+      "Requirement already satisfied: requests in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (2.28.1)\n",
+      "Requirement already satisfied: Flask>=1.1.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (2.1.2)\n",
+      "Requirement already satisfied: Flask-Cors>=3.0.8 in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (3.0.10)\n",
+      "Collecting flask-cachebuster (from gradio==1.6.0)\n",
+      "  Downloading Flask-CacheBuster-1.0.0.tar.gz (3.1 kB)\n",
+      "  Preparing metadata (setup.py): started\n",
+      "  Preparing metadata (setup.py): finished with status 'done'\n",
+      "Requirement already satisfied: Flask-BasicAuth in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (0.2.0)\n",
+      "Requirement already satisfied: paramiko in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (2.8.1)\n",
+      "Requirement already satisfied: scipy in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (1.10.0)\n",
+      "Requirement already satisfied: IPython in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (8.10.0)\n",
+      "Requirement already satisfied: scikit-image in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (0.19.3)\n",
+      "Collecting analytics-python (from gradio==1.6.0)\n",
+      "  Downloading analytics_python-1.4.post1-py2.py3-none-any.whl (23 kB)\n",
+      "Requirement already satisfied: pandas in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (1.5.3)\n",
+      "Requirement already satisfied: ffmpy in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (0.3.0)\n",
+      "Collecting markdown2 (from gradio==1.6.0)\n",
+      "  Downloading markdown2-2.4.8-py2.py3-none-any.whl (38 kB)\n",
+      "Requirement already satisfied: Werkzeug>=2.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from Flask>=1.1.1->gradio==1.6.0) (2.3.4)\n",
+      "Requirement already satisfied: Jinja2>=3.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from Flask>=1.1.1->gradio==1.6.0) (3.1.2)\n",
+      "Requirement already satisfied: itsdangerous>=2.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from Flask>=1.1.1->gradio==1.6.0) (2.1.2)\n",
+      "Requirement already satisfied: click>=8.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from Flask>=1.1.1->gradio==1.6.0) (8.1.3)\n",
+      "Requirement already satisfied: Six in c:\\users\\user\\anaconda3\\lib\\site-packages (from Flask-Cors>=3.0.8->gradio==1.6.0) (1.16.0)\n",
+      "Collecting monotonic>=1.5 (from analytics-python->gradio==1.6.0)\n",
+      "  Downloading monotonic-1.6-py2.py3-none-any.whl (8.2 kB)\n",
+      "Collecting backoff==1.10.0 (from analytics-python->gradio==1.6.0)\n",
+      "  Downloading backoff-1.10.0-py2.py3-none-any.whl (31 kB)\n",
+      "Requirement already satisfied: python-dateutil>2.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from analytics-python->gradio==1.6.0) (2.8.2)\n",
+      "Requirement already satisfied: charset-normalizer<3,>=2 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->gradio==1.6.0) (2.0.4)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->gradio==1.6.0) (3.4)\n",
+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->gradio==1.6.0) (1.26.14)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->gradio==1.6.0) (2022.12.7)\n",
+      "Requirement already satisfied: backcall in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (0.2.0)\n",
+      "Requirement already satisfied: decorator in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (5.1.1)\n",
+      "Requirement already satisfied: jedi>=0.16 in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (0.18.1)\n",
+      "Requirement already satisfied: matplotlib-inline in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (0.1.6)\n",
+      "Requirement already satisfied: pickleshare in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (0.7.5)\n",
+      "Requirement already satisfied: prompt-toolkit<3.1.0,>=3.0.30 in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (3.0.36)\n",
+      "Requirement already satisfied: pygments>=2.4.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (2.15.1)\n",
+      "Requirement already satisfied: stack-data in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (0.2.0)\n",
+      "Requirement already satisfied: traitlets>=5 in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (5.7.1)\n",
+      "Requirement already satisfied: colorama in c:\\users\\user\\anaconda3\\lib\\site-packages (from IPython->gradio==1.6.0) (0.4.6)\n",
+      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from pandas->gradio==1.6.0) (2022.7)\n",
+      "Requirement already satisfied: bcrypt>=3.1.3 in c:\\users\\user\\anaconda3\\lib\\site-packages (from paramiko->gradio==1.6.0) (3.2.0)\n",
+      "Requirement already satisfied: cryptography>=2.5 in c:\\users\\user\\anaconda3\\lib\\site-packages (from paramiko->gradio==1.6.0) (39.0.1)\n",
+      "Requirement already satisfied: pynacl>=1.0.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from paramiko->gradio==1.6.0) (1.5.0)\n",
+      "Requirement already satisfied: networkx>=2.2 in c:\\users\\user\\anaconda3\\lib\\site-packages (from scikit-image->gradio==1.6.0) (2.8.4)\n",
+      "Requirement already satisfied: pillow!=7.1.0,!=7.1.1,!=8.3.0,>=6.1.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from scikit-image->gradio==1.6.0) (9.4.0)\n",
+      "Requirement already satisfied: imageio>=2.4.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from scikit-image->gradio==1.6.0) (2.26.0)\n",
+      "Requirement already satisfied: tifffile>=2019.7.26 in c:\\users\\user\\anaconda3\\lib\\site-packages (from scikit-image->gradio==1.6.0) (2021.7.2)\n",
+      "Requirement already satisfied: PyWavelets>=1.1.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from scikit-image->gradio==1.6.0) (1.4.1)\n",
+      "Requirement already satisfied: packaging>=20.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from scikit-image->gradio==1.6.0) (22.0)\n",
+      "Requirement already satisfied: cffi>=1.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from bcrypt>=3.1.3->paramiko->gradio==1.6.0) (1.15.1)\n",
+      "Requirement already satisfied: parso<0.9.0,>=0.8.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from jedi>=0.16->IPython->gradio==1.6.0) (0.8.3)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from Jinja2>=3.0->Flask>=1.1.1->gradio==1.6.0) (2.1.1)\n",
+      "Requirement already satisfied: wcwidth in c:\\users\\user\\anaconda3\\lib\\site-packages (from prompt-toolkit<3.1.0,>=3.0.30->IPython->gradio==1.6.0) (0.2.5)\n",
+      "Requirement already satisfied: executing in c:\\users\\user\\anaconda3\\lib\\site-packages (from stack-data->IPython->gradio==1.6.0) (0.8.3)\n",
+      "Requirement already satisfied: asttokens in c:\\users\\user\\anaconda3\\lib\\site-packages (from stack-data->IPython->gradio==1.6.0) (2.0.5)\n",
+      "Requirement already satisfied: pure-eval in c:\\users\\user\\anaconda3\\lib\\site-packages (from stack-data->IPython->gradio==1.6.0) (0.2.2)\n",
+      "Requirement already satisfied: pycparser in c:\\users\\user\\anaconda3\\lib\\site-packages (from cffi>=1.1->bcrypt>=3.1.3->paramiko->gradio==1.6.0) (2.21)\n",
+      "Building wheels for collected packages: flask-cachebuster\n",
+      "  Building wheel for flask-cachebuster (setup.py): started\n",
+      "  Building wheel for flask-cachebuster (setup.py): finished with status 'done'\n",
+      "  Created wheel for flask-cachebuster: filename=Flask_CacheBuster-1.0.0-py3-none-any.whl size=3372 sha256=c1b85a8b017ca7784ce61eec4714ca9dd7e500dc251835ef6f9820731268b2c5\n",
+      "  Stored in directory: c:\\users\\user\\appdata\\local\\pip\\cache\\wheels\\22\\35\\5e\\088242cb16f309a4ff4e94ce97f1ef8a469983fdde92b45f50\n",
+      "Successfully built flask-cachebuster\n",
+      "Installing collected packages: monotonic, markdown2, backoff, analytics-python, flask-cachebuster, gradio\n",
+      "  Attempting uninstall: gradio\n",
+      "    Found existing installation: gradio 3.33.1\n",
+      "    Uninstalling gradio-3.33.1:\n",
+      "      Successfully uninstalled gradio-3.33.1\n",
+      "Successfully installed analytics-python-1.4.post1 backoff-1.10.0 flask-cachebuster-1.0.0 gradio-1.6.0 markdown2-2.4.8 monotonic-1.6\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install gradio==1.6.0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "70ec40a3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting MarkupSafe==2.1.1\n",
+      "  Downloading MarkupSafe-2.1.1-cp310-cp310-win_amd64.whl (17 kB)\n",
+      "Installing collected packages: MarkupSafe\n",
+      "  Attempting uninstall: MarkupSafe\n",
+      "    Found existing installation: MarkupSafe 2.0.1\n",
+      "    Uninstalling MarkupSafe-2.0.1:\n",
+      "      Successfully uninstalled MarkupSafe-2.0.1\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "ERROR: Could not install packages due to an OSError: [WinError 5] Access is denied: 'C:\\\\Users\\\\User\\\\anaconda3\\\\Lib\\\\site-packages\\\\~arkupsafe\\\\_speedups.cp310-win_amd64.pyd'\n",
+      "Consider using the `--user` option or check the permissions.\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install MarkupSafe==2.1.1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "961a6510",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\User\\anaconda3\\lib\\site-packages\\paramiko\\transport.py:219: CryptographyDeprecationWarning: Blowfish has been deprecated\n",
+      "  \"class\": algorithms.Blowfish,\n"
+     ]
+    }
+   ],
+   "source": [
+    "import gradio as gr\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "from PIL import Image\n",
+    "import requests\n",
+    "\n",
+    "\n",
+    "# Download human-readable labels for ImageNet.\n",
+    "response = requests.get(\"https://git.io/JJkYN\")\n",
+    "labels = response.text.split(\"\\n\")\n",
+    "\n",
+    "mobile_net = tf.keras.applications.MobileNetV2()\n",
+    "inception_net = tf.keras.applications.InceptionV3()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "44d83e7d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def classify_image_with_mobile_net(im):\n",
+    "    im = Image.fromarray(im.astype('uint8'), 'RGB')\n",
+    "    im = im.resize((224, 224))\n",
+    "    arr = np.array(im).reshape((-1, 224, 224, 3))\n",
+    "    arr = tf.keras.applications.mobilenet.preprocess_input(arr)\n",
+    "    prediction = mobile_net.predict(arr).flatten()\n",
+    "    return {labels[i]: float(prediction[i]) for i in range(1000)}\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "5e77912e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def classify_image_with_inception_net(im):\n",
+    "    # Resize the image to\n",
+    "    im = Image.fromarray(im.astype('uint8'), 'RGB')\n",
+    "    im = im.resize((299, 299))\n",
+    "    arr = np.array(im).reshape((-1, 299, 299, 3))\n",
+    "    arr = tf.keras.applications.inception_v3.preprocess_input(arr)\n",
+    "    prediction = inception_net.predict(arr).flatten()\n",
+    "    return {labels[i]: float(prediction[i]) for i in range(1000)}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f6a9e5fe",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "imagein = gr.inputs.Image()\n",
+    "label = gr.outputs.Label(num_top_classes=3)\n",
+    "sample_images = [\n",
+    "                 [\"monkey.jpg\"],\n",
+    "                 [\"sailboat.jpg\"],\n",
+    "                 [\"bicycle.jpg\"],\n",
+    "                 [\"download.jpg\"],\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "61c325d0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "IMPORTANT: You are using gradio version 1.6.0, however version 3.14.0 is available, please upgrade.\n",
+      "--------\n",
+      "Running locally at: http://127.0.0.1:7861/\n",
+      "To create a public link, set `share=True` in `launch()`.\n",
+      "Interface loading below...\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"1000\"\n",
+       "            height=\"500\"\n",
+       "            src=\"http://127.0.0.1:7861/\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "            \n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x1f4f8fe2830>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[2023-06-05 22:40:39,347] ERROR in app: Exception on /file/monkey.jpg [GET]\n",
+      "Traceback (most recent call last):\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
+      "    response = self.full_dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
+      "    rv = self.handle_user_exception(e)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
+      "    return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
+      "    rv = self.dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
+      "    return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 269, in file\n",
+      "    return send_file(os.path.join(app.cwd, path))\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\helpers.py\", line 610, in send_file\n",
+      "    return werkzeug.utils.send_file(\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\werkzeug\\utils.py\", line 427, in send_file\n",
+      "    stat = os.stat(path)\n",
+      "FileNotFoundError: [WinError 2] The system cannot find the file specified: 'C:\\\\Users\\\\User\\\\Downloads\\\\monkey.jpg'\n",
+      "[2023-06-05 22:40:39,356] ERROR in app: Exception on /file/sailboat.jpg [GET]\n",
+      "Traceback (most recent call last):\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
+      "    response = self.full_dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
+      "    rv = self.handle_user_exception(e)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
+      "    return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
+      "    rv = self.dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
+      "    return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 269, in file\n",
+      "    return send_file(os.path.join(app.cwd, path))\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\helpers.py\", line 610, in send_file\n",
+      "    return werkzeug.utils.send_file(\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\werkzeug\\utils.py\", line 427, in send_file\n",
+      "    stat = os.stat(path)\n",
+      "FileNotFoundError: [WinError 2] The system cannot find the file specified: 'C:\\\\Users\\\\User\\\\Downloads\\\\sailboat.jpg'\n",
+      "[2023-06-05 22:40:39,357] ERROR in app: Exception on /file/bicycle.jpg [GET]\n",
+      "Traceback (most recent call last):\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
+      "    response = self.full_dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
+      "    rv = self.handle_user_exception(e)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
+      "    return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
+      "    rv = self.dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
+      "    return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 269, in file\n",
+      "    return send_file(os.path.join(app.cwd, path))\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\helpers.py\", line 610, in send_file\n",
+      "    return werkzeug.utils.send_file(\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\werkzeug\\utils.py\", line 427, in send_file\n",
+      "    stat = os.stat(path)\n",
+      "FileNotFoundError: [WinError 2] The system cannot find the file specified: 'C:\\\\Users\\\\User\\\\Downloads\\\\bicycle.jpg'\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(<Flask 'gradio.networking'>, 'http://127.0.0.1:7861/', None)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gr.Interface(\n",
+    "    [classify_image_with_mobile_net, classify_image_with_inception_net],\n",
+    "    imagein,\n",
+    "    label,\n",
+    "    title=\"MobileNet vs. InceptionNet\",\n",
+    "    description=\"\"\"Let's compare 2 state-of-the-art machine learning models that classify images into one of 1,000 categories: MobileNet (top),\n",
+    "          a lightweight model that has an accuracy of 0.704, vs. InceptionNet\n",
+    "          (bottom), a much heavier model that has an accuracy of 0.779.\"\"\",\n",
+    "    examples=sample_images).launch()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3dbc1cab",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: transformers in c:\\users\\user\\anaconda3\\lib\\site-packages (4.27.0)\n",
+      "Requirement already satisfied: filelock in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (3.12.0)\n",
+      "Requirement already satisfied: huggingface-hub<1.0,>=0.11.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (0.14.1)\n",
+      "Requirement already satisfied: numpy>=1.17 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (1.24.3)\n",
+      "Requirement already satisfied: packaging>=20.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (22.0)\n",
+      "Requirement already satisfied: pyyaml>=5.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (6.0)\n",
+      "Requirement already satisfied: regex!=2019.12.17 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (2022.7.9)\n",
+      "Requirement already satisfied: requests in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (2.28.1)\n",
+      "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (0.11.4)\n",
+      "Requirement already satisfied: tqdm>=4.27 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (4.64.1)\n",
+      "Requirement already satisfied: fsspec in c:\\users\\user\\anaconda3\\lib\\site-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (2022.11.0)\n",
+      "Requirement already satisfied: typing-extensions>=3.7.4.3 in c:\\users\\user\\anaconda3\\lib\\site-packages (from huggingface-hub<1.0,>=0.11.0->transformers) (4.4.0)\n",
+      "Requirement already satisfied: colorama in c:\\users\\user\\anaconda3\\lib\\site-packages (from tqdm>=4.27->transformers) (0.4.6)\n",
+      "Requirement already satisfied: charset-normalizer<3,>=2 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->transformers) (2.0.4)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->transformers) (3.4)\n",
+      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->transformers) (1.26.14)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->transformers) (2022.12.7)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
+      "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n"
+     ]
+    }
+   ],
+   "source": [
+    "pip install transformers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "7deaaac7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "IMPORTANT: You are using gradio version 1.6.0, however version 3.14.0 is available, please upgrade.\n",
+      "--------\n",
+      "Running locally at: http://127.0.0.1:7861/\n",
+      "To create a public link, set `share=True` in `launch()`.\n",
+      "Interface loading below...\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"1000\"\n",
+       "            height=\"500\"\n",
+       "            src=\"http://127.0.0.1:7861/\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "            \n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x22af27eb940>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(<Flask 'gradio.networking'>, 'http://127.0.0.1:7861/', None)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import gradio as gr\n",
+    "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n",
+    "\n",
+    "# Load the models and tokenizers\n",
+    "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n",
+    "\n",
+    "tokenizer1 = AutoTokenizer.from_pretrained(\"textattack/bert-base-uncased-imdb\")\n",
+    "tokenizer2 = AutoTokenizer.from_pretrained(\"nlptown/bert-base-multilingual-uncased-sentiment\")\n",
+    "model1 = AutoModelForSequenceClassification.from_pretrained(\"textattack/bert-base-uncased-imdb\")\n",
+    "model2 = AutoModelForSequenceClassification.from_pretrained(\"nlptown/bert-base-multilingual-uncased-sentiment\")\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
+    "# Define the sentiment prediction functions\n",
+    "def predict_sentiment(text):\n",
+    "    # Predict sentiment using model 1\n",
+    "    inputs1 = tokenizer1.encode_plus(text, padding=\"longest\", truncation=True, return_tensors=\"pt\")\n",
+    "    outputs1 = model1(**inputs1)\n",
+    "    predicted_label1 = outputs1.logits.argmax().item()\n",
+    "    sentiment1 = \"Positive\" if predicted_label1 == 1 else \"Negative\" if predicted_label1 == 0 else \"Neutral\"\n",
+    "\n",
+    "    # Predict sentiment using model 2\n",
+    "    inputs2 = tokenizer2.encode_plus(text, padding=\"longest\", truncation=True, return_tensors=\"pt\")\n",
+    "    outputs2 = model2(**inputs2)\n",
+    "    predicted_label2 = outputs2.logits.argmax().item()\n",
+    "    sentiment2 = \"Positive\" if predicted_label2 == 1 else \"Negative\" if predicted_label2 == 0 else \"Neutral\"\n",
+    "\n",
+    "    return sentiment1, sentiment2\n",
+    "\n",
+    "# Create the Gradio interface\n",
+    "iface = gr.Interface(\n",
+    "    fn=predict_sentiment,\n",
+    "    inputs=\"text\",\n",
+    "    outputs=[\"text\", \"text\"],\n",
+    "    title=\"Sentiment Analysis (Model 1 vs Model 2)\",\n",
+    "    description=\"Compare sentiment predictions from two models.\",\n",
+    ")\n",
+    "\n",
+    "# Launch the interface\n",
+    "iface.launch()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "bd93f2a5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertForSequenceClassification: ['cls.seq_relationship.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.seq_relationship.bias', 'cls.predictions.transform.dense.bias', 'cls.predictions.decoder.weight', 'cls.predictions.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.LayerNorm.weight']\n",
+      "- This IS expected if you are initializing BertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
+      "- This IS NOT expected if you are initializing BertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
+      "Some weights of BertForSequenceClassification were not initialized from the model checkpoint at bert-base-uncased and are newly initialized: ['classifier.bias', 'classifier.weight']\n",
+      "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
+      "Some weights of the model checkpoint at distilbert-base-uncased were not used when initializing DistilBertForSequenceClassification: ['vocab_projector.bias', 'vocab_layer_norm.weight', 'vocab_transform.weight', 'vocab_transform.bias', 'vocab_layer_norm.bias', 'vocab_projector.weight']\n",
+      "- This IS expected if you are initializing DistilBertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
+      "- This IS NOT expected if you are initializing DistilBertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
+      "Some weights of DistilBertForSequenceClassification were not initialized from the model checkpoint at distilbert-base-uncased and are newly initialized: ['classifier.bias', 'classifier.weight', 'pre_classifier.bias', 'pre_classifier.weight']\n",
+      "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "IMPORTANT: You are using gradio version 1.6.0, however version 3.14.0 is available, please upgrade.\n",
+      "--------\n",
+      "Running locally at: http://127.0.0.1:7871/\n",
+      "To create a public link, set `share=True` in `launch()`.\n",
+      "Interface loading below...\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"1000\"\n",
+       "            height=\"500\"\n",
+       "            src=\"http://127.0.0.1:7871/\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "            \n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x22a82329c30>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(<Flask 'gradio.networking'>, 'http://127.0.0.1:7871/', None)"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[2023-06-05 21:25:10,327] ERROR in app: Exception on /api/predict/ [POST]\n",
+      "Traceback (most recent call last):\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
+      "    response = self.full_dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
+      "    rv = self.handle_user_exception(e)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
+      "    return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
+      "    rv = self.dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
+      "    return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 133, in predict\n",
+      "    prediction, durations = app.interface.process(raw_input)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\interface.py\", line 272, in process\n",
+      "    predictions, durations = self.run_prediction(processed_input, return_duration=True)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\interface.py\", line 246, in run_prediction\n",
+      "    prediction = predict_fn(*processed_input)\n",
+      "  File \"C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_9376\\3704131587.py\", line 80, in classify_image\n",
+      "    prediction = predict(image_file=image_file, model_key=model_key)\n",
+      "  File \"C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_9376\\3704131587.py\", line 67, in predict\n",
+      "    image = preprocess(image_file)\n",
+      "  File \"C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_9376\\3704131587.py\", line 51, in preprocess\n",
+      "    image = Image.open(BytesIO(image_file.read())).convert(\"RGB\")\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\PIL\\Image.py\", line 3283, in open\n",
+      "    raise UnidentifiedImageError(msg)\n",
+      "PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x0000022ABA1C10D0>\n",
+      "[2023-06-05 21:39:36,773] ERROR in app: Exception on /api/predict/ [POST]\n",
+      "Traceback (most recent call last):\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
+      "    response = self.full_dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
+      "    rv = self.handle_user_exception(e)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
+      "    return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
+      "    rv = self.dispatch_request()\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
+      "    return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 133, in predict\n",
+      "    prediction, durations = app.interface.process(raw_input)\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\interface.py\", line 270, in process\n",
+      "    processed_input = [input_interface.preprocess(raw_input[i])\n",
+      "  File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\interface.py\", line 270, in <listcomp>\n",
+      "    processed_input = [input_interface.preprocess(raw_input[i])\n",
+      "IndexError: list index out of range\n"
+     ]
+    }
+   ],
+   "source": [
+    "import gradio as gr\n",
+    "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n",
+    "import torch\n",
+    "from torchvision import transforms\n",
+    "from io import BytesIO\n",
+    "from PIL import Image\n",
+    "\n",
+    "# Define the available models and datasets\n",
+    "models = {\n",
+    "    \"Model 1\": {\n",
+    "        \"model_name\": \"bert-base-uncased\",\n",
+    "        \"tokenizer\": None,\n",
+    "        \"model\": None\n",
+    "    },\n",
+    "    \"Model 2\": {\n",
+    "        \"model_name\": \"distilbert-base-uncased\",\n",
+    "        \"tokenizer\": None,\n",
+    "        \"model\": None\n",
+    "    },\n",
+    "    # Add more models as needed\n",
+    "}\n",
+    "\n",
+    "datasets = {\n",
+    "    \"Dataset 1\": {\n",
+    "        \"name\": \"imdb\",\n",
+    "        \"split\": \"test\",\n",
+    "        \"features\": [\"text\"],\n",
+    "    },\n",
+    "    \"Dataset 2\": {\n",
+    "        \"name\": \"ag_news\",\n",
+    "        \"split\": \"test\",\n",
+    "        \"features\": [\"text\"],\n",
+    "    },\n",
+    "    # Add more datasets as needed\n",
+    "}\n",
+    "\n",
+    "# Load models\n",
+    "for model_key, model_info in models.items():\n",
+    "    tokenizer = AutoTokenizer.from_pretrained(model_info[\"model_name\"])\n",
+    "    model = AutoModelForSequenceClassification.from_pretrained(model_info[\"model_name\"])\n",
+    "    model_info[\"tokenizer\"] = tokenizer\n",
+    "    model_info[\"model\"] = model\n",
+    "\n",
+    "# Set the device to GPU if available\n",
+    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
+    "for model_info in models.values():\n",
+    "    model_info[\"model\"].to(device)\n",
+    "\n",
+    "# Define the preprocessing function\n",
+    "def preprocess(image_file):\n",
+    "    image = Image.open(BytesIO(image_file.read())).convert(\"RGB\")\n",
+    "    preprocess_transform = transforms.Compose([\n",
+    "        transforms.Resize((224, 224)),\n",
+    "        transforms.ToTensor(),\n",
+    "        transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
+    "    ])\n",
+    "    image = preprocess_transform(image)\n",
+    "    image = image.unsqueeze(0)\n",
+    "    return image.to(device)\n",
+    "\n",
+    "# Define the prediction function\n",
+    "def predict(image_file, model_key):\n",
+    "    model_info = models[model_key]\n",
+    "    tokenizer = model_info[\"tokenizer\"]\n",
+    "    model = model_info[\"model\"]\n",
+    "\n",
+    "    image = preprocess(image_file)\n",
+    "\n",
+    "    with torch.no_grad():\n",
+    "        outputs = model(image)\n",
+    "\n",
+    "    predictions = outputs.logits.argmax(dim=1)\n",
+    "\n",
+    "    return predictions.item()\n",
+    "\n",
+    "def classify_image(image, model_key):\n",
+    "    image = Image.fromarray(image.astype('uint8'), 'RGB')\n",
+    "    image_file = BytesIO()\n",
+    "    image.save(image_file, format=\"JPEG\")\n",
+    "    prediction = predict(image_file=image_file, model_key=model_key)\n",
+    "    return prediction\n",
+    "\n",
+    "iface = gr.Interface(fn=classify_image,\n",
+    "                     inputs=[\"image\", gr.inputs.Dropdown(list(models.keys()), label=\"Model\")],\n",
+    "                     outputs=\"text\",\n",
+    "                     title=\"Image Classification\",\n",
+    "                     description=\"Classify images using Hugging Face models\")\n",
+    "\n",
+    "iface.launch()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c25d39b5",
+   "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": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}