finalproject.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyNpJbw9o5YVy70WbDJWG0Gg",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Unknown0028/HOARDVIEW/blob/main/finalproject.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from keras.models import load_model\n",
        "from PIL import Image, ImageOps\n",
        "import numpy as np\n",
        "import gradio as gr\n",
        "\n",
        "# Disable scientific notation for clarity\n",
        "np.set_printoptions(suppress=True)\n",
        "\n",
        "# Load the model\n",
        "model = load_model(\"keras_model.h5\", compile=False)\n",
        "\n",
        "# Load the labels\n",
        "class_names = open(\"labels.txt\", \"r\").readlines()\n",
        "\n",
        "def classify_image(image):\n",
        "    # Resize the image to 224x224\n",
        "    image = ImageOps.fit(image, (224, 224), Image.Resampling.LANCZOS)\n",
        "\n",
        "    # Create the array of the right shape to feed into the keras model\n",
        "    data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)\n",
        "\n",
        "    # Turn the image into a numpy array\n",
        "    image_array = np.asarray(image)\n",
        "\n",
        "    # Normalize the image\n",
        "    normalized_image_array = (image_array.astype(np.float32) / 127.5) - 1\n",
        "\n",
        "    # Load the image into the array\n",
        "    data[0] = normalized_image_array\n",
        "\n",
        "    # Predict the model\n",
        "    prediction = model.predict(data)\n",
        "    index = np.argmax(prediction)\n",
        "    class_name = class_names[index]\n",
        "    confidence_score = prediction[0][index]\n",
        "\n",
        "    return f\"Class: {class_name[2:]}, Confidence Score: {confidence_score:.2f}\"\n",
        "\n",
        "# Create the Gradio interface\n",
        "iface = gr.Interface(\n",
        "    fn=classify_image,\n",
        "    inputs=gr.Image(type=\"pil\"),\n",
        "    outputs=\"text\",\n",
        "    title=\"Image Classification\",\n",
        "    description=\"Upload an image and I'll classify it for you!\",\n",
        ")\n",
        "\n",
        "# Launch the Gradio interface\n",
        "iface.launch()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 646
        },
        "id": "GZp__JcNPWbE",
        "outputId": "99021ece-93d1-445c-e4c4-0f7c3ceea795"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
            "\n",
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Running on public URL: https://b514d7f97ddc725e66.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"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div><iframe src=\"https://b514d7f97ddc725e66.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install gradio\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rkcgb40yT4Fb",
        "outputId": "9505a8de-8838-409f-cf86-a62df94af293"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio->httpx>=0.24.1->gradio) (1.2.1)\n",
            "Collecting httptools>=0.5.0 (from uvicorn>=0.14.0->gradio)\n",
            "  Downloading httptools-0.6.1-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (341 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m341.4/341.4 kB\u001b[0m \u001b[31m29.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting python-dotenv>=0.13 (from uvicorn>=0.14.0->gradio)\n",
            "  Downloading python_dotenv-1.0.1-py3-none-any.whl (19 kB)\n",
            "Collecting uvloop!=0.15.0,!=0.15.1,>=0.14.0 (from uvicorn>=0.14.0->gradio)\n",
            "  Downloading uvloop-0.19.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.4 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.4/3.4 MB\u001b[0m \u001b[31m79.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting watchfiles>=0.13 (from uvicorn>=0.14.0->gradio)\n",
            "  Downloading watchfiles-0.21.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m64.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.19.3->gradio) (3.3.2)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich>=10.11.0->typer<1.0,>=0.12->gradio) (0.1.2)\n",
            "Building wheels for collected packages: ffmpy\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.2-py3-none-any.whl size=5584 sha256=fc0b9f50c8be1a0449238dc98ac6f1d283b038efb74d9c37a4cfc52c2d36df5d\n",
            "  Stored in directory: /root/.cache/pip/wheels/bd/65/9a/671fc6dcde07d4418df0c592f8df512b26d7a0029c2a23dd81\n",
            "Successfully built ffmpy\n",
            "Installing collected packages: pydub, ffmpy, websockets, uvloop, ujson, tomlkit, shellingham, semantic-version, ruff, python-multipart, python-dotenv, orjson, httptools, h11, dnspython, aiofiles, watchfiles, uvicorn, starlette, httpcore, email_validator, typer, httpx, gradio-client, fastapi-cli, fastapi, gradio\n",
            "  Attempting uninstall: typer\n",
            "    Found existing installation: typer 0.9.4\n",
            "    Uninstalling typer-0.9.4:\n",
            "      Successfully uninstalled typer-0.9.4\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "spacy 3.7.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\n",
            "weasel 0.3.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed aiofiles-23.2.1 dnspython-2.6.1 email_validator-2.1.1 fastapi-0.111.0 fastapi-cli-0.0.3 ffmpy-0.3.2 gradio-4.31.4 gradio-client-0.16.4 h11-0.14.0 httpcore-1.0.5 httptools-0.6.1 httpx-0.27.0 orjson-3.10.3 pydub-0.25.1 python-dotenv-1.0.1 python-multipart-0.0.9 ruff-0.4.4 semantic-version-2.10.0 shellingham-1.5.4 starlette-0.37.2 tomlkit-0.12.0 typer-0.12.3 ujson-5.10.0 uvicorn-0.29.0 uvloop-0.19.0 watchfiles-0.21.0 websockets-11.0.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "R9LalY1aT9ZE"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}