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Delete Gradio Examples.ipynb

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- {
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- "cells": [
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- {
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- "cell_type": "markdown",
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- "id": "09eb5ef2",
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- "metadata": {},
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- "source": [
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- "#### Gradio Comparing Transfer Learning Models"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 1,
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- "id": "f3f83569",
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "2.12.0\n"
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- ]
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- }
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- ],
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- "source": [
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- "import tensorflow as tf\n",
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- "print(tf.__version__)"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 2,
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- "id": "c1ca8b20",
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "Collecting gradio==1.6.0\n",
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- " Downloading gradio-1.6.0-py3-none-any.whl (1.1 MB)\n",
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- "Requirement already satisfied: numpy in c:\\users\\user\\anaconda3\\lib\\site-packages (from gradio==1.6.0) (1.24.3)\n",
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- "Collecting flask-cachebuster (from gradio==1.6.0)\n",
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- " Downloading Flask-CacheBuster-1.0.0.tar.gz (3.1 kB)\n",
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- " Preparing metadata (setup.py): started\n",
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- "Collecting markdown2 (from gradio==1.6.0)\n",
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- "Building wheels for collected packages: flask-cachebuster\n",
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- " Building wheel for flask-cachebuster (setup.py): started\n",
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- " Building wheel for flask-cachebuster (setup.py): finished with status 'done'\n",
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- " Created wheel for flask-cachebuster: filename=Flask_CacheBuster-1.0.0-py3-none-any.whl size=3372 sha256=c1b85a8b017ca7784ce61eec4714ca9dd7e500dc251835ef6f9820731268b2c5\n",
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- " Stored in directory: c:\\users\\user\\appdata\\local\\pip\\cache\\wheels\\22\\35\\5e\\088242cb16f309a4ff4e94ce97f1ef8a469983fdde92b45f50\n",
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- "Successfully built flask-cachebuster\n",
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- "Installing collected packages: monotonic, markdown2, backoff, analytics-python, flask-cachebuster, gradio\n",
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- " Attempting uninstall: gradio\n",
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- " Found existing installation: gradio 3.33.1\n",
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- " Uninstalling gradio-3.33.1:\n",
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- " Successfully uninstalled gradio-3.33.1\n",
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- "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",
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- "Note: you may need to restart the kernel to use updated packages.\n"
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- ]
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- "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
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- "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
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- }
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- ],
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- "source": [
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- "pip install gradio==1.6.0"
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- "cell_type": "code",
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- "execution_count": 3,
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- "id": "70ec40a3",
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- "outputs": [
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- "Collecting MarkupSafe==2.1.1\n",
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- " Downloading MarkupSafe-2.1.1-cp310-cp310-win_amd64.whl (17 kB)\n",
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- "Installing collected packages: MarkupSafe\n",
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- " Attempting uninstall: MarkupSafe\n",
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- " Found existing installation: MarkupSafe 2.0.1\n",
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- " Uninstalling MarkupSafe-2.0.1:\n",
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- " Successfully uninstalled MarkupSafe-2.0.1\n",
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- "Note: you may need to restart the kernel to use updated packages.\n"
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- ]
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- "name": "stderr",
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- "output_type": "stream",
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- "text": [
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- "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
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- "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
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- "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
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- "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
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- "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",
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- "Consider using the `--user` option or check the permissions.\n",
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- "\n"
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- ]
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- }
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- ],
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- "source": [
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- "pip install MarkupSafe==2.1.1"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 1,
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- "id": "961a6510",
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stderr",
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- "output_type": "stream",
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- "text": [
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- "C:\\Users\\User\\anaconda3\\lib\\site-packages\\paramiko\\transport.py:219: CryptographyDeprecationWarning: Blowfish has been deprecated\n",
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- " \"class\": algorithms.Blowfish,\n"
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- ]
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- }
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- ],
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- "source": [
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- "import gradio as gr\n",
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- "import tensorflow as tf\n",
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- "import numpy as np\n",
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- "from PIL import Image\n",
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- "import requests\n",
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- "\n",
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- "\n",
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- "# Download human-readable labels for ImageNet.\n",
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- "response = requests.get(\"https://git.io/JJkYN\")\n",
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- "labels = response.text.split(\"\\n\")\n",
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- "\n",
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- "mobile_net = tf.keras.applications.MobileNetV2()\n",
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- "inception_net = tf.keras.applications.InceptionV3()\n"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 2,
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- "id": "44d83e7d",
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "def classify_image_with_mobile_net(im):\n",
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- " im = Image.fromarray(im.astype('uint8'), 'RGB')\n",
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- " im = im.resize((224, 224))\n",
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- " arr = np.array(im).reshape((-1, 224, 224, 3))\n",
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- " arr = tf.keras.applications.mobilenet.preprocess_input(arr)\n",
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- " prediction = mobile_net.predict(arr).flatten()\n",
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- " return {labels[i]: float(prediction[i]) for i in range(1000)}\n",
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- " "
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 3,
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- "id": "5e77912e",
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "def classify_image_with_inception_net(im):\n",
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- " # Resize the image to\n",
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- " im = Image.fromarray(im.astype('uint8'), 'RGB')\n",
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- " im = im.resize((299, 299))\n",
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- " arr = np.array(im).reshape((-1, 299, 299, 3))\n",
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- " arr = tf.keras.applications.inception_v3.preprocess_input(arr)\n",
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- " prediction = inception_net.predict(arr).flatten()\n",
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- " return {labels[i]: float(prediction[i]) for i in range(1000)}"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 4,
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- "id": "f6a9e5fe",
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "imagein = gr.inputs.Image()\n",
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- "label = gr.outputs.Label(num_top_classes=3)\n",
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- "sample_images = [\n",
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- " [\"monkey.jpg\"],\n",
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- " [\"sailboat.jpg\"],\n",
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- " [\"bicycle.jpg\"],\n",
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- " [\"download.jpg\"],\n",
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- "]"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 6,
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- "id": "61c325d0",
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "IMPORTANT: You are using gradio version 1.6.0, however version 3.14.0 is available, please upgrade.\n",
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- "--------\n",
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- "Running locally at: http://127.0.0.1:7861/\n",
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- "To create a public link, set `share=True` in `launch()`.\n",
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- "Interface loading below...\n"
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- ]
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- },
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- {
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- "data": {
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- "text/html": [
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- "\n",
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- " <iframe\n",
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- " width=\"1000\"\n",
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- " height=\"500\"\n",
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- " src=\"http://127.0.0.1:7861/\"\n",
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- " frameborder=\"0\"\n",
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- " allowfullscreen\n",
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- " \n",
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- " ></iframe>\n",
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- " "
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- ],
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- "text/plain": [
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- "<IPython.lib.display.IFrame at 0x1f4f8fe2830>"
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- "text": [
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- "[2023-06-05 22:40:39,347] ERROR in app: Exception on /file/monkey.jpg [GET]\n",
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- "Traceback (most recent call last):\n",
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- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
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- " response = self.full_dispatch_request()\n",
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- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
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- " rv = self.handle_user_exception(e)\n",
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- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
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- " return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
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- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
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- " rv = self.dispatch_request()\n",
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- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
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- " return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
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- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 269, in file\n",
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- " return send_file(os.path.join(app.cwd, path))\n",
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- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\helpers.py\", line 610, in send_file\n",
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- " return werkzeug.utils.send_file(\n",
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- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\werkzeug\\utils.py\", line 427, in send_file\n",
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- " stat = os.stat(path)\n",
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- "FileNotFoundError: [WinError 2] The system cannot find the file specified: 'C:\\\\Users\\\\User\\\\Downloads\\\\monkey.jpg'\n",
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- "[2023-06-05 22:40:39,356] ERROR in app: Exception on /file/sailboat.jpg [GET]\n",
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- "Traceback (most recent call last):\n",
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- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
325
- " response = self.full_dispatch_request()\n",
326
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
327
- " rv = self.handle_user_exception(e)\n",
328
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
329
- " return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
330
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
331
- " rv = self.dispatch_request()\n",
332
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
333
- " return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
334
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 269, in file\n",
335
- " return send_file(os.path.join(app.cwd, path))\n",
336
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\helpers.py\", line 610, in send_file\n",
337
- " return werkzeug.utils.send_file(\n",
338
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\werkzeug\\utils.py\", line 427, in send_file\n",
339
- " stat = os.stat(path)\n",
340
- "FileNotFoundError: [WinError 2] The system cannot find the file specified: 'C:\\\\Users\\\\User\\\\Downloads\\\\sailboat.jpg'\n",
341
- "[2023-06-05 22:40:39,357] ERROR in app: Exception on /file/bicycle.jpg [GET]\n",
342
- "Traceback (most recent call last):\n",
343
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
344
- " response = self.full_dispatch_request()\n",
345
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
346
- " rv = self.handle_user_exception(e)\n",
347
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
348
- " return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
349
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
350
- " rv = self.dispatch_request()\n",
351
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
352
- " return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
353
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 269, in file\n",
354
- " return send_file(os.path.join(app.cwd, path))\n",
355
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\helpers.py\", line 610, in send_file\n",
356
- " return werkzeug.utils.send_file(\n",
357
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\werkzeug\\utils.py\", line 427, in send_file\n",
358
- " stat = os.stat(path)\n",
359
- "FileNotFoundError: [WinError 2] The system cannot find the file specified: 'C:\\\\Users\\\\User\\\\Downloads\\\\bicycle.jpg'\n"
360
- ]
361
- },
362
- {
363
- "data": {
364
- "text/plain": [
365
- "(<Flask 'gradio.networking'>, 'http://127.0.0.1:7861/', None)"
366
- ]
367
- },
368
- "execution_count": 6,
369
- "metadata": {},
370
- "output_type": "execute_result"
371
- }
372
- ],
373
- "source": [
374
- "gr.Interface(\n",
375
- " [classify_image_with_mobile_net, classify_image_with_inception_net],\n",
376
- " imagein,\n",
377
- " label,\n",
378
- " title=\"MobileNet vs. InceptionNet\",\n",
379
- " description=\"\"\"Let's compare 2 state-of-the-art machine learning models that classify images into one of 1,000 categories: MobileNet (top),\n",
380
- " a lightweight model that has an accuracy of 0.704, vs. InceptionNet\n",
381
- " (bottom), a much heavier model that has an accuracy of 0.779.\"\"\",\n",
382
- " examples=sample_images).launch()"
383
- ]
384
- },
385
- {
386
- "cell_type": "code",
387
- "execution_count": 6,
388
- "id": "3dbc1cab",
389
- "metadata": {},
390
- "outputs": [
391
- {
392
- "name": "stdout",
393
- "output_type": "stream",
394
- "text": [
395
- "Requirement already satisfied: transformers in c:\\users\\user\\anaconda3\\lib\\site-packages (4.27.0)\n",
396
- "Requirement already satisfied: filelock in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (3.12.0)\n",
397
- "Requirement already satisfied: huggingface-hub<1.0,>=0.11.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (0.14.1)\n",
398
- "Requirement already satisfied: numpy>=1.17 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (1.24.3)\n",
399
- "Requirement already satisfied: packaging>=20.0 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (22.0)\n",
400
- "Requirement already satisfied: pyyaml>=5.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (6.0)\n",
401
- "Requirement already satisfied: regex!=2019.12.17 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (2022.7.9)\n",
402
- "Requirement already satisfied: requests in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (2.28.1)\n",
403
- "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",
404
- "Requirement already satisfied: tqdm>=4.27 in c:\\users\\user\\anaconda3\\lib\\site-packages (from transformers) (4.64.1)\n",
405
- "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",
406
- "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",
407
- "Requirement already satisfied: colorama in c:\\users\\user\\anaconda3\\lib\\site-packages (from tqdm>=4.27->transformers) (0.4.6)\n",
408
- "Requirement already satisfied: charset-normalizer<3,>=2 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->transformers) (2.0.4)\n",
409
- "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->transformers) (3.4)\n",
410
- "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->transformers) (1.26.14)\n",
411
- "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\user\\anaconda3\\lib\\site-packages (from requests->transformers) (2022.12.7)\n",
412
- "Note: you may need to restart the kernel to use updated packages.\n"
413
- ]
414
- },
415
- {
416
- "name": "stderr",
417
- "output_type": "stream",
418
- "text": [
419
- "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
420
- "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
421
- "WARNING: Ignoring invalid distribution -orch (c:\\users\\user\\anaconda3\\lib\\site-packages)\n",
422
- "WARNING: Ignoring invalid distribution -rotobuf (c:\\users\\user\\anaconda3\\lib\\site-packages)\n"
423
- ]
424
- }
425
- ],
426
- "source": [
427
- "pip install transformers"
428
- ]
429
- },
430
- {
431
- "cell_type": "code",
432
- "execution_count": 6,
433
- "id": "7deaaac7",
434
- "metadata": {},
435
- "outputs": [
436
- {
437
- "name": "stdout",
438
- "output_type": "stream",
439
- "text": [
440
- "IMPORTANT: You are using gradio version 1.6.0, however version 3.14.0 is available, please upgrade.\n",
441
- "--------\n",
442
- "Running locally at: http://127.0.0.1:7861/\n",
443
- "To create a public link, set `share=True` in `launch()`.\n",
444
- "Interface loading below...\n"
445
- ]
446
- },
447
- {
448
- "data": {
449
- "text/html": [
450
- "\n",
451
- " <iframe\n",
452
- " width=\"1000\"\n",
453
- " height=\"500\"\n",
454
- " src=\"http://127.0.0.1:7861/\"\n",
455
- " frameborder=\"0\"\n",
456
- " allowfullscreen\n",
457
- " \n",
458
- " ></iframe>\n",
459
- " "
460
- ],
461
- "text/plain": [
462
- "<IPython.lib.display.IFrame at 0x22af27eb940>"
463
- ]
464
- },
465
- "metadata": {},
466
- "output_type": "display_data"
467
- },
468
- {
469
- "data": {
470
- "text/plain": [
471
- "(<Flask 'gradio.networking'>, 'http://127.0.0.1:7861/', None)"
472
- ]
473
- },
474
- "execution_count": 6,
475
- "metadata": {},
476
- "output_type": "execute_result"
477
- }
478
- ],
479
- "source": [
480
- "import gradio as gr\n",
481
- "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n",
482
- "\n",
483
- "# Load the models and tokenizers\n",
484
- "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n",
485
- "\n",
486
- "tokenizer1 = AutoTokenizer.from_pretrained(\"textattack/bert-base-uncased-imdb\")\n",
487
- "tokenizer2 = AutoTokenizer.from_pretrained(\"nlptown/bert-base-multilingual-uncased-sentiment\")\n",
488
- "model1 = AutoModelForSequenceClassification.from_pretrained(\"textattack/bert-base-uncased-imdb\")\n",
489
- "model2 = AutoModelForSequenceClassification.from_pretrained(\"nlptown/bert-base-multilingual-uncased-sentiment\")\n",
490
- "\n",
491
- "\n",
492
- "\n",
493
- "\n",
494
- "# Define the sentiment prediction functions\n",
495
- "def predict_sentiment(text):\n",
496
- " # Predict sentiment using model 1\n",
497
- " inputs1 = tokenizer1.encode_plus(text, padding=\"longest\", truncation=True, return_tensors=\"pt\")\n",
498
- " outputs1 = model1(**inputs1)\n",
499
- " predicted_label1 = outputs1.logits.argmax().item()\n",
500
- " sentiment1 = \"Positive\" if predicted_label1 == 1 else \"Negative\" if predicted_label1 == 0 else \"Neutral\"\n",
501
- "\n",
502
- " # Predict sentiment using model 2\n",
503
- " inputs2 = tokenizer2.encode_plus(text, padding=\"longest\", truncation=True, return_tensors=\"pt\")\n",
504
- " outputs2 = model2(**inputs2)\n",
505
- " predicted_label2 = outputs2.logits.argmax().item()\n",
506
- " sentiment2 = \"Positive\" if predicted_label2 == 1 else \"Negative\" if predicted_label2 == 0 else \"Neutral\"\n",
507
- "\n",
508
- " return sentiment1, sentiment2\n",
509
- "\n",
510
- "# Create the Gradio interface\n",
511
- "iface = gr.Interface(\n",
512
- " fn=predict_sentiment,\n",
513
- " inputs=\"text\",\n",
514
- " outputs=[\"text\", \"text\"],\n",
515
- " title=\"Sentiment Analysis (Model 1 vs Model 2)\",\n",
516
- " description=\"Compare sentiment predictions from two models.\",\n",
517
- ")\n",
518
- "\n",
519
- "# Launch the interface\n",
520
- "iface.launch()\n"
521
- ]
522
- },
523
- {
524
- "cell_type": "code",
525
- "execution_count": 17,
526
- "id": "bd93f2a5",
527
- "metadata": {},
528
- "outputs": [
529
- {
530
- "name": "stderr",
531
- "output_type": "stream",
532
- "text": [
533
- "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",
534
- "- 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",
535
- "- 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",
536
- "Some weights of BertForSequenceClassification were not initialized from the model checkpoint at bert-base-uncased and are newly initialized: ['classifier.bias', 'classifier.weight']\n",
537
- "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
538
- "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",
539
- "- 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",
540
- "- 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",
541
- "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",
542
- "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
543
- ]
544
- },
545
- {
546
- "name": "stdout",
547
- "output_type": "stream",
548
- "text": [
549
- "IMPORTANT: You are using gradio version 1.6.0, however version 3.14.0 is available, please upgrade.\n",
550
- "--------\n",
551
- "Running locally at: http://127.0.0.1:7871/\n",
552
- "To create a public link, set `share=True` in `launch()`.\n",
553
- "Interface loading below...\n"
554
- ]
555
- },
556
- {
557
- "data": {
558
- "text/html": [
559
- "\n",
560
- " <iframe\n",
561
- " width=\"1000\"\n",
562
- " height=\"500\"\n",
563
- " src=\"http://127.0.0.1:7871/\"\n",
564
- " frameborder=\"0\"\n",
565
- " allowfullscreen\n",
566
- " \n",
567
- " ></iframe>\n",
568
- " "
569
- ],
570
- "text/plain": [
571
- "<IPython.lib.display.IFrame at 0x22a82329c30>"
572
- ]
573
- },
574
- "metadata": {},
575
- "output_type": "display_data"
576
- },
577
- {
578
- "data": {
579
- "text/plain": [
580
- "(<Flask 'gradio.networking'>, 'http://127.0.0.1:7871/', None)"
581
- ]
582
- },
583
- "execution_count": 17,
584
- "metadata": {},
585
- "output_type": "execute_result"
586
- },
587
- {
588
- "name": "stderr",
589
- "output_type": "stream",
590
- "text": [
591
- "[2023-06-05 21:25:10,327] ERROR in app: Exception on /api/predict/ [POST]\n",
592
- "Traceback (most recent call last):\n",
593
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
594
- " response = self.full_dispatch_request()\n",
595
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
596
- " rv = self.handle_user_exception(e)\n",
597
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
598
- " return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
599
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
600
- " rv = self.dispatch_request()\n",
601
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
602
- " return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
603
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 133, in predict\n",
604
- " prediction, durations = app.interface.process(raw_input)\n",
605
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\interface.py\", line 272, in process\n",
606
- " predictions, durations = self.run_prediction(processed_input, return_duration=True)\n",
607
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\interface.py\", line 246, in run_prediction\n",
608
- " prediction = predict_fn(*processed_input)\n",
609
- " File \"C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_9376\\3704131587.py\", line 80, in classify_image\n",
610
- " prediction = predict(image_file=image_file, model_key=model_key)\n",
611
- " File \"C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_9376\\3704131587.py\", line 67, in predict\n",
612
- " image = preprocess(image_file)\n",
613
- " File \"C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_9376\\3704131587.py\", line 51, in preprocess\n",
614
- " image = Image.open(BytesIO(image_file.read())).convert(\"RGB\")\n",
615
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\PIL\\Image.py\", line 3283, in open\n",
616
- " raise UnidentifiedImageError(msg)\n",
617
- "PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x0000022ABA1C10D0>\n",
618
- "[2023-06-05 21:39:36,773] ERROR in app: Exception on /api/predict/ [POST]\n",
619
- "Traceback (most recent call last):\n",
620
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 2077, in wsgi_app\n",
621
- " response = self.full_dispatch_request()\n",
622
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1525, in full_dispatch_request\n",
623
- " rv = self.handle_user_exception(e)\n",
624
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask_cors\\extension.py\", line 165, in wrapped_function\n",
625
- " return cors_after_request(app.make_response(f(*args, **kwargs)))\n",
626
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1523, in full_dispatch_request\n",
627
- " rv = self.dispatch_request()\n",
628
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\flask\\app.py\", line 1509, in dispatch_request\n",
629
- " return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)\n",
630
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\networking.py\", line 133, in predict\n",
631
- " prediction, durations = app.interface.process(raw_input)\n",
632
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\interface.py\", line 270, in process\n",
633
- " processed_input = [input_interface.preprocess(raw_input[i])\n",
634
- " File \"C:\\Users\\User\\anaconda3\\lib\\site-packages\\gradio\\interface.py\", line 270, in <listcomp>\n",
635
- " processed_input = [input_interface.preprocess(raw_input[i])\n",
636
- "IndexError: list index out of range\n"
637
- ]
638
- }
639
- ],
640
- "source": [
641
- "import gradio as gr\n",
642
- "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n",
643
- "import torch\n",
644
- "from torchvision import transforms\n",
645
- "from io import BytesIO\n",
646
- "from PIL import Image\n",
647
- "\n",
648
- "# Define the available models and datasets\n",
649
- "models = {\n",
650
- " \"Model 1\": {\n",
651
- " \"model_name\": \"bert-base-uncased\",\n",
652
- " \"tokenizer\": None,\n",
653
- " \"model\": None\n",
654
- " },\n",
655
- " \"Model 2\": {\n",
656
- " \"model_name\": \"distilbert-base-uncased\",\n",
657
- " \"tokenizer\": None,\n",
658
- " \"model\": None\n",
659
- " },\n",
660
- " # Add more models as needed\n",
661
- "}\n",
662
- "\n",
663
- "datasets = {\n",
664
- " \"Dataset 1\": {\n",
665
- " \"name\": \"imdb\",\n",
666
- " \"split\": \"test\",\n",
667
- " \"features\": [\"text\"],\n",
668
- " },\n",
669
- " \"Dataset 2\": {\n",
670
- " \"name\": \"ag_news\",\n",
671
- " \"split\": \"test\",\n",
672
- " \"features\": [\"text\"],\n",
673
- " },\n",
674
- " # Add more datasets as needed\n",
675
- "}\n",
676
- "\n",
677
- "# Load models\n",
678
- "for model_key, model_info in models.items():\n",
679
- " tokenizer = AutoTokenizer.from_pretrained(model_info[\"model_name\"])\n",
680
- " model = AutoModelForSequenceClassification.from_pretrained(model_info[\"model_name\"])\n",
681
- " model_info[\"tokenizer\"] = tokenizer\n",
682
- " model_info[\"model\"] = model\n",
683
- "\n",
684
- "# Set the device to GPU if available\n",
685
- "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
686
- "for model_info in models.values():\n",
687
- " model_info[\"model\"].to(device)\n",
688
- "\n",
689
- "# Define the preprocessing function\n",
690
- "def preprocess(image_file):\n",
691
- " image = Image.open(BytesIO(image_file.read())).convert(\"RGB\")\n",
692
- " preprocess_transform = transforms.Compose([\n",
693
- " transforms.Resize((224, 224)),\n",
694
- " transforms.ToTensor(),\n",
695
- " transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
696
- " ])\n",
697
- " image = preprocess_transform(image)\n",
698
- " image = image.unsqueeze(0)\n",
699
- " return image.to(device)\n",
700
- "\n",
701
- "# Define the prediction function\n",
702
- "def predict(image_file, model_key):\n",
703
- " model_info = models[model_key]\n",
704
- " tokenizer = model_info[\"tokenizer\"]\n",
705
- " model = model_info[\"model\"]\n",
706
- "\n",
707
- " image = preprocess(image_file)\n",
708
- "\n",
709
- " with torch.no_grad():\n",
710
- " outputs = model(image)\n",
711
- "\n",
712
- " predictions = outputs.logits.argmax(dim=1)\n",
713
- "\n",
714
- " return predictions.item()\n",
715
- "\n",
716
- "def classify_image(image, model_key):\n",
717
- " image = Image.fromarray(image.astype('uint8'), 'RGB')\n",
718
- " image_file = BytesIO()\n",
719
- " image.save(image_file, format=\"JPEG\")\n",
720
- " prediction = predict(image_file=image_file, model_key=model_key)\n",
721
- " return prediction\n",
722
- "\n",
723
- "iface = gr.Interface(fn=classify_image,\n",
724
- " inputs=[\"image\", gr.inputs.Dropdown(list(models.keys()), label=\"Model\")],\n",
725
- " outputs=\"text\",\n",
726
- " title=\"Image Classification\",\n",
727
- " description=\"Classify images using Hugging Face models\")\n",
728
- "\n",
729
- "iface.launch()\n"
730
- ]
731
- },
732
- {
733
- "cell_type": "code",
734
- "execution_count": null,
735
- "id": "c25d39b5",
736
- "metadata": {},
737
- "outputs": [],
738
- "source": []
739
- }
740
- ],
741
- "metadata": {
742
- "kernelspec": {
743
- "display_name": "Python 3 (ipykernel)",
744
- "language": "python",
745
- "name": "python3"
746
- },
747
- "language_info": {
748
- "codemirror_mode": {
749
- "name": "ipython",
750
- "version": 3
751
- },
752
- "file_extension": ".py",
753
- "mimetype": "text/x-python",
754
- "name": "python",
755
- "nbconvert_exporter": "python",
756
- "pygments_lexer": "ipython3",
757
- "version": "3.10.9"
758
- }
759
- },
760
- "nbformat": 4,
761
- "nbformat_minor": 5
762
- }