CLIP.ipynb

{
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  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
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    "accelerator": "GPU"
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  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ETwtDgkSnq-Z",
        "outputId": "71dc4038-0ad0-41b9-b145-086174ec6a13"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "INFO: This is taking longer than usual. You might need to provide the dependency resolver with stricter constraints to reduce runtime. See https://pip.pypa.io/warnings/backtracking for guidance. If you want to abort this run, press Ctrl + C.\n",
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            "\u001b[31mERROR: Cannot install clip-by-openai==0.1.0, clip-by-openai==0.1.1, clip-by-openai==0.1.1.2, clip-by-openai==0.1.1.3, clip-by-openai==0.1.1.4, clip-by-openai==0.1.1.5, clip-by-openai==1.0.1, clip-by-openai==1.1, torch and torchvision==0.12.0 because these package versions have conflicting dependencies.\u001b[0m\u001b[31m\n",
            "\u001b[0m\n",
            "The conflict is caused by:\n",
            "    The user requested torch\n",
            "    torchvision 0.12.0 depends on torch==1.11.0\n",
            "    clip-by-openai 1.1 depends on torch<1.7.2 and >=1.7.1\n",
            "    The user requested torch\n",
            "    torchvision 0.12.0 depends on torch==1.11.0\n",
            "    clip-by-openai 1.0.1 depends on torch<1.7.2 and >=1.7.1\n",
            "    The user requested torch\n",
            "    torchvision 0.12.0 depends on torch==1.11.0\n",
            "    clip-by-openai 0.1.1.5 depends on torch==1.7.1\n",
            "    The user requested torch\n",
            "    torchvision 0.12.0 depends on torch==1.11.0\n",
            "    clip-by-openai 0.1.1.4 depends on torch==1.7.1\n",
            "    The user requested torch\n",
            "    torchvision 0.12.0 depends on torch==1.11.0\n",
            "    clip-by-openai 0.1.1.3 depends on torch==1.7.1\n",
            "    The user requested torch\n",
            "    torchvision 0.12.0 depends on torch==1.11.0\n",
            "    clip-by-openai 0.1.1.2 depends on torch==1.7.1\n",
            "    The user requested torch\n",
            "    torchvision 0.12.0 depends on torch==1.11.0\n",
            "    clip-by-openai 0.1.1 depends on torch==1.7.1\n",
            "    The user requested torch\n",
            "    torchvision 0.12.0 depends on torch==1.11.0\n",
            "    clip-by-openai 0.1.0 depends on torch==1.7.1\n",
            "\n",
            "To fix this you could try to:\n",
            "1. loosen the range of package versions you've specified\n",
            "2. remove package versions to allow pip to attempt to solve the dependency conflict\n",
            "\n",
            "\u001b[31mERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts\u001b[0m\u001b[31m\n",
            "\u001b[0mCollecting git+https://github.com/openai/CLIP.git\n",
            "  Cloning https://github.com/openai/CLIP.git to /tmp/pip-req-build-vbi02bzu\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/openai/CLIP.git /tmp/pip-req-build-vbi02bzu\n",
            "  Resolved https://github.com/openai/CLIP.git to commit dcba3cb2e2827b402d2701e7e1c7d9fed8a20ef1\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting ftfy (from clip==1.0)\n",
            "  Using cached ftfy-6.2.3-py3-none-any.whl.metadata (7.8 kB)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from clip==1.0) (24.1)\n",
            "Requirement already satisfied: regex in /usr/local/lib/python3.10/dist-packages (from clip==1.0) (2024.5.15)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from clip==1.0) (4.66.5)\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from clip==1.0) (2.4.0+cu121)\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (from clip==1.0) (0.19.0+cu121)\n",
            "Requirement already satisfied: wcwidth<0.3.0,>=0.2.12 in /usr/local/lib/python3.10/dist-packages (from ftfy->clip==1.0) (0.2.13)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch->clip==1.0) (3.16.0)\n",
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            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from torchvision->clip==1.0) (1.26.4)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision->clip==1.0) (9.4.0)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->clip==1.0) (2.1.5)\n",
            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch->clip==1.0) (1.3.0)\n",
            "Downloading ftfy-6.2.3-py3-none-any.whl (43 kB)\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.0/43.0 kB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hBuilding wheels for collected packages: clip\n",
            "  Building wheel for clip (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for clip: filename=clip-1.0-py3-none-any.whl size=1369490 sha256=26e63d03330da96c8c1b1a65794e41c46b429e390924412c0c1a7995e5a441c4\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-uezpb2vy/wheels/da/2b/4c/d6691fa9597aac8bb85d2ac13b112deb897d5b50f5ad9a37e4\n",
            "Successfully built clip\n",
            "Installing collected packages: ftfy, clip\n",
            "Successfully installed clip-1.0 ftfy-6.2.3\n"
          ]
        }
      ],
      "source": [
        "!pip install flask-ngrok openai torch torchvision pillow clip-by-openai\n",
        "!pip install git+https://github.com/openai/CLIP.git\n",
        "!pip install openai==0.28\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from flask import Flask, request, jsonify\n",
        "import openai\n",
        "import clip\n",
        "from PIL import Image\n",
        "import torch\n",
        "import requests\n",
        "from io import BytesIO\n",
        "\n",
        "# Initialize Flask app\n",
        "app = Flask(__name__)\n",
        "\n",
        "# OpenAI API key setup\n",
        "openai.api_key = \"sk-proj-XEFdLjY0XkmvYMHz5cYg8U-ZLHVf9mkXdms3L1omf4\"\n",
        "\n",
        "# CLIP model setup\n",
        "device = \"cpu\"\n",
        "model, preprocess = clip.load(\"ViT-B/32\", device=device)\n",
        "\n",
        "@app.route('/generate-augmented-image', methods=['POST'])\n",
        "def generate_augmented_image():\n",
        "    data = request.json\n",
        "    image_url = data.get(\"imageUrl\")\n",
        "\n",
        "    # Download the image from the provided URL with User-Agent header\n",
        "    headers = {\n",
        "        \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36\"\n",
        "    }\n",
        "    try:\n",
        "        response = requests.get(image_url, headers=headers)\n",
        "        response.raise_for_status()  # Check for HTTP errors\n",
        "    except requests.exceptions.RequestException as e:\n",
        "        return jsonify({\"error\": f\"Failed to download image: {str(e)}\"}), 400\n",
        "\n",
        "    # Check if the response is an image\n",
        "    if 'image' not in response.headers['Content-Type']:\n",
        "        return jsonify({\"error\": \"URL does not point to a valid image\"}), 400\n",
        "\n",
        "    try:\n",
        "        img = Image.open(BytesIO(response.content))\n",
        "    except Exception as e:\n",
        "        return jsonify({\"error\": f\"Failed to open image: {str(e)}\"}), 400\n",
        "\n",
        "    image_tensor = preprocess(img).unsqueeze(0).to(device)\n",
        "\n",
        "    # Universal prompt for generating greenified images\n",
        "    prompt = \"Add trees and greenery in empty spaces. Preserve the buildings and other important structures but make the area more walkable with green spaces.\"\n",
        "\n",
        "    # Tokenize the text prompt\n",
        "    text = clip.tokenize([prompt]).to(device)\n",
        "\n",
        "    # CLIP Processing\n",
        "    with torch.no_grad():\n",
        "        image_features = model.encode_image(image_tensor)\n",
        "        text_features = model.encode_text(text)\n",
        "        similarity = torch.cosine_similarity(image_features, text_features)\n",
        "\n",
        "    # Use OpenAI Image API (DALL-E) to generate the augmented image\n",
        "    response = openai.Image.create(\n",
        "        prompt=\"Add trees and greenery in empty spaces in the given photo. Preserve the buildings and other important structures but make the area more walkable and beautiful with green spaces:\" + image_url,\n",
        "        n=1,\n",
        "        size=\"512x512\"\n",
        "    )\n",
        "\n",
        "    return jsonify({\"generatedImageUrl\": response['data'][0]['url']})\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "r7ad08E62PR1"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from threading import Thread\n",
        "def run_app():\n",
        "    app.run(host='0.0.0.0', port=5005)\n",
        "\n",
        "# Start the Flask app in the background\n",
        "Thread(target=run_app).start()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wLzfE8xu4zEA",
        "outputId": "5228c824-d4e0-4adf-c259-d5b3d8015502"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " * Serving Flask app '__main__'\n",
            " * Debug mode: off\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:werkzeug:\u001b[31m\u001b[1mWARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.\u001b[0m\n",
            " * Running on all addresses (0.0.0.0)\n",
            " * Running on http://127.0.0.1:5005\n",
            " * Running on http://172.28.0.12:5005\n",
            "INFO:werkzeug:\u001b[33mPress CTRL+C to quit\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import requests\n",
        "\n",
        "# Use a valid image URL (direct link to an image file)\n",
        "image_url = \"https://news.harvard.edu/gazette/wp-content/uploads/2017/07/streetchange_77_seaport_blvd_boston_ma_6052.jpg\"\n",
        "\n",
        "# Make a request to the API\n",
        "response = requests.post(\"http://127.0.0.1:5005/generate-augmented-image\", json={\"imageUrl\": image_url})\n",
        "\n",
        "# Output the result\n",
        "if response.status_code == 200:\n",
        "    augmented_image_url = response.json().get(\"generatedImageUrl\")\n",
        "    print(\"Generated Image URL:\", augmented_image_url)\n",
        "else:\n",
        "    print(f\"Error: {response.json()['error']}\")\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2F4SyKec2PYg",
        "outputId": "12a03b15-ba2d-4077-ccdd-3e0d6e9c1b9b"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "INFO:werkzeug:127.0.0.1 - - [15/Sep/2024 00:02:16] \"POST /generate-augmented-image HTTP/1.1\" 200 -\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generated Image URL: https://oaidalleapiprodscus.blob.core.windows.net/private/org-RBQ2Q8CEZiw1McLBsr4laXXi/user-mCX9NdmXBpTNWiuKlgQ1fxOS/img-J7f3vnn5lT3TkfvvLgO2VcvB.png?st=2024-09-14T23%3A02%3A16Z&se=2024-09-15T01%3A02%3A16Z&sp=r&sv=2024-08-04&sr=b&rscd=inline&rsct=image/png&skoid=d505667d-d6c1-4a0a-bac7-5c84a87759f8&sktid=a48cca56-e6da-484e-a814-9c849652bcb3&skt=2024-09-15T00%3A02%3A16Z&ske=2024-09-16T00%3A02%3A16Z&sks=b&skv=2024-08-04&sig=Xvvdh9RS7ZE53EQNh4Hc3tFindtFFIahaS5yOj%2B0u58%3D\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "o6ZOpvXn2PnZ"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}