Image_Compression.ipynb

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  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "#Importing the Necessary Libraries"
      ],
      "metadata": {
        "id": "PjFTaL2uVpKx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install ipywidgets\n",
        "!pip install pillow"
      ],
      "metadata": {
        "id": "SHT-S1fV87ag"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from PIL import Image\n",
        "import os\n",
        "import ipywidgets as widgets\n",
        "from IPython.display import display"
      ],
      "metadata": {
        "id": "egeoYcS8LuN5"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Directory Setup for Image Compression"
      ],
      "metadata": {
        "id": "lJV6AMnaXYOQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "input_dir = \"/content/images\"\n",
        "output_dir = \"/content/compressed images5\"\n",
        "\n",
        "if not os.path.exists(output_dir):\n",
        "    os.mkdir(output_dir)"
      ],
      "metadata": {
        "id": "19sJcKnTMq5L"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Interactive Image Compression Configuration"
      ],
      "metadata": {
        "id": "9q4V14ynXnt_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "compression_quality = int(input(\"Enter compression quality (0-100): \"))\n",
        "\n",
        "\n",
        "use_original_dimensions = input(\"Use original dimensions? (yes or no): \").lower()\n",
        "\n",
        "if use_original_dimensions not in [\"yes\", \"no\"]:\n",
        "        print(\"Invalid dimensions selection. Using original dimensions as default.\")\n",
        "        use_original_dimensions = \"yes\"\n",
        "\n",
        "if use_original_dimensions == \"yes\":\n",
        "    target_width = None\n",
        "    target_height = None\n",
        "else:\n",
        "    target_width = int(input(\"Enter target width: \"))\n",
        "    target_height = int(input(\"Enter target height: \"))\n",
        "\n",
        "\n",
        "output_format = input(\"Enter output format (JPEG or PNG or JPG): \").lower()\n",
        "if output_format not in [\"jpeg\", \"jpg\", \"png\"]:\n",
        "        print(\"Invalid output format selection. Using jpg as default.\")\n",
        "        output_format = \"jpg\"\n",
        "\n",
        "if output_format == 'png':\n",
        "    png_quality = input(\"Select PNG quality (High or Low): \").lower()\n",
        "\n",
        "    if png_quality not in [\"high\", \"low\"]:\n",
        "        print(\"Invalid PNG quality selection. Using High Quality as default.\")\n",
        "        png_quality = \"high\"\n",
        "\n",
        "print(\" \")"
      ],
      "metadata": {
        "id": "oST2J6AFMwMK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cc3fff5d-2b14-4826-e9c2-c1007aab8aa8"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter compression quality (0-100): 50\n",
            "Use original dimensions? (yes or no): yes\n",
            "Enter output format (JPEG or PNG or JPG): png\n",
            "Select PNG quality (High or Low): low\n",
            " \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Image Processing: Compression and Format Conversion"
      ],
      "metadata": {
        "id": "DmlylTKRYAw3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def process_images(directory):\n",
        "    for root, _, files in os.walk(directory):\n",
        "        for file in files:\n",
        "            input_path = os.path.join(root, file)\n",
        "            output_path = os.path.join(output_dir, os.path.relpath(input_path, input_dir))\n",
        "\n",
        "            try:\n",
        "                image = Image.open(input_path)\n",
        "\n",
        "                if target_width is not None and target_height is not None:\n",
        "                    image = image.resize((target_width, target_height), Image.ANTIALIAS)\n",
        "\n",
        "                if output_format == 'png':\n",
        "\n",
        "                    image_format = 'PNG' if png_quality == 'high' else 'JPEG'\n",
        "                    output_path = os.path.splitext(output_path)[0] + \".png\"\n",
        "                    image.save(output_path, format=image_format, optimize=True, quality=compression_quality)\n",
        "                else:\n",
        "                    image.save(output_path, format='JPEG', optimize=True, quality=compression_quality)\n",
        "\n",
        "                print(f\"{os.path.relpath(input_path, input_dir)} processed and saved as {output_format}\")\n",
        "            except Exception as e:\n",
        "                print(f\"Skipping {os.path.relpath(input_path, input_dir)} - Error: {str(e)}\")\n",
        "\n",
        "\n",
        "process_images(input_dir)\n",
        "\n",
        "print(\"Image compression and format conversion completed.\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xX6XMcIq5GBS",
        "outputId": "9bb5a4e8-ebe7-43d0-bc7e-81a1895887e3"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "eagle.jpg processed and saved as png\n",
            "Skipping blur.png - Error: cannot write mode RGBA as JPEG\n",
            "kite.jpg processed and saved as png\n",
            "person.jpg processed and saved as png\n",
            "ped.jpg processed and saved as png\n",
            "horses.jpg processed and saved as png\n",
            "road.jpg processed and saved as png\n",
            "Image compression and format conversion completed.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#GUI Version"
      ],
      "metadata": {
        "id": "C1LMYsyXM1Xx"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Image Processing: Compression and Format Conversion Function"
      ],
      "metadata": {
        "id": "8sUUrmF_YPfo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def process_images(input_dir, output_dir, compression_quality, use_original_dimensions, target_width, target_height, output_format, png_quality):\n",
        "    if not os.path.exists(output_dir):\n",
        "        os.makedirs(output_dir)\n",
        "\n",
        "    for root, _, files in os.walk(input_dir):\n",
        "        for file in files:\n",
        "            input_path = os.path.join(root, file)\n",
        "            output_path = os.path.join(output_dir, os.path.relpath(input_path, input_dir))\n",
        "\n",
        "            try:\n",
        "                image = Image.open(input_path)\n",
        "\n",
        "                if not use_original_dimensions:\n",
        "                    if target_width is not None and target_height is not None:\n",
        "                        image = image.resize((target_width, target_height), Image.LANCZOS)\n",
        "\n",
        "                if output_format == 'png':\n",
        "\n",
        "                    image_format = 'PNG' if png_quality == 'high' else 'JPEG'\n",
        "                    output_path = os.path.splitext(output_path)[0] + \".png\"\n",
        "                    image.save(output_path, format=image_format, optimize=True, quality=compression_quality)\n",
        "                else:\n",
        "                    image.save(output_path, format='JPEG', optimize=True, quality=compression_quality)\n",
        "\n",
        "                print(f\"{os.path.relpath(input_path, input_dir)} processed and saved as {output_format}\")\n",
        "            except Exception as e:\n",
        "                print(f\"Skipping {os.path.relpath(input_path, input_dir)} - Error: {str(e)}\")\n",
        "\n",
        "    print(\"Image compression and format conversion completed.\")"
      ],
      "metadata": {
        "id": "IjWBJfBnM8ci"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Widget-Based Image Compression Configurator"
      ],
      "metadata": {
        "id": "j5CBa95kYkRz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "input_dir_text = widgets.Text(value=\"/content/images\", layout=widgets.Layout(width='40%'))\n",
        "output_dir_text = widgets.Text(value=\"/content/compressed images8\", layout=widgets.Layout(width='40%'))\n",
        "compression_quality_slider = widgets.IntSlider(value=85, min=0, max=100, layout=widgets.Layout(width='40%'))\n",
        "output_format_dropdown = widgets.Dropdown(options=['JPEG', 'PNG'], value='JPEG', layout=widgets.Layout(width='40%'))\n",
        "png_quality_dropdown = widgets.Dropdown(options=['High', 'Low'], value='High', layout=widgets.Layout(width='40%'))\n",
        "use_original_dimensions_dropdown = widgets.Dropdown(options=['Yes', 'No'], value='Yes', layout=widgets.Layout(width='40%'))\n",
        "width_input = widgets.IntText(value=800, layout=widgets.Layout(width='40%'))\n",
        "height_input = widgets.IntText(value=600, layout=widgets.Layout(width='40%'))\n",
        "process_button = widgets.Button(description=\"Process Images\", layout=widgets.Layout(width='20%', margin='25px 0 20px 130px'))"
      ],
      "metadata": {
        "id": "m2FTQMbXNELJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Widget Labels for Image Processing Parameters"
      ],
      "metadata": {
        "id": "nuLMFrGbYv5l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "input_dir_label = widgets.Label(\"Input Directory:\", layout=widgets.Layout(width='40%'))\n",
        "output_dir_label = widgets.Label(\"Output Directory:\", layout=widgets.Layout(width='40%'))\n",
        "compression_quality_label = widgets.Label(\"Compression Quality:\", layout=widgets.Layout(width='40%'))\n",
        "output_format_label = widgets.Label(\"Output Format:\", layout=widgets.Layout(width='40%'))\n",
        "png_quality_label = widgets.Label(\"PNG Quality:\", layout=widgets.Layout(width='40%'))\n",
        "use_original_dimensions_label = widgets.Label(\"Use Original Dimensions:\", layout=widgets.Layout(width='40%'))\n",
        "width_label = widgets.Label(\"Width:\", layout=widgets.Layout(width='40%'))\n",
        "height_label = widgets.Label(\"Height:\", layout=widgets.Layout(width='40%'))"
      ],
      "metadata": {
        "id": "T4YikO9mNH5g"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Dynamic Visibility Control for Dimension Inputs and PNG Quality in Image Processing UI"
      ],
      "metadata": {
        "id": "bFcmvBM3ZHgP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def update_dimension_input(change):\n",
        "    if use_original_dimensions_dropdown.value == 'Yes':\n",
        "        width_input.layout.display = 'none'\n",
        "        height_input.layout.display = 'none'\n",
        "        height_label.layout.display = 'none'\n",
        "        width_label.layout.display = 'none'\n",
        "    else:\n",
        "        width_input.layout.display = ''\n",
        "        height_input.layout.display = ''\n",
        "        height_label.layout.display = ''\n",
        "        width_label.layout.display = ''\n",
        "\n",
        "def update_png_quality_dropdown(change):\n",
        "    if output_format_dropdown.value == 'PNG':\n",
        "        png_quality_dropdown.layout.display = ''\n",
        "        png_quality_label.layout.display = ''\n",
        "    else:\n",
        "        png_quality_dropdown.layout.display = 'none'\n",
        "        png_quality_label.layout.display = 'none'\n",
        "\n",
        "width_input.layout.display = 'none'\n",
        "height_input.layout.display = 'none'\n",
        "height_label.layout.display = 'none'\n",
        "width_label.layout.display = 'none'\n",
        "\n",
        "png_quality_dropdown.layout.display = 'none'\n",
        "png_quality_label.layout.display = 'none'\n",
        "\n",
        "use_original_dimensions_dropdown.observe(update_dimension_input, names='value')\n",
        "output_format_dropdown.observe(update_png_quality_dropdown, names='value')"
      ],
      "metadata": {
        "id": "atOmKj9KNOGN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Image Processing Widget with Interactive Controls"
      ],
      "metadata": {
        "id": "HOPIIyqYZW6A"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def process_button_clicked(b):\n",
        "    input_dir = input_dir_text.value\n",
        "    output_dir = output_dir_text.value\n",
        "    compression_quality = compression_quality_slider.value\n",
        "    output_format = output_format_dropdown.value.lower()\n",
        "    use_original_dimensions = use_original_dimensions_dropdown.value == 'Yes'\n",
        "    target_width = width_input.value if not use_original_dimensions else None\n",
        "    target_height = height_input.value if not use_original_dimensions else None\n",
        "    png_quality = png_quality_dropdown.value.lower()\n",
        "    process_images(input_dir, output_dir, compression_quality, use_original_dimensions, target_width, target_height, output_format, png_quality)\n",
        "\n",
        "process_button.on_click(process_button_clicked)\n",
        "\n",
        "input_widgets = [input_dir_label, input_dir_text, output_dir_label, output_dir_text]\n",
        "compression_quality_widgets = [compression_quality_label, compression_quality_slider]\n",
        "format_widgets = [output_format_label, output_format_dropdown, png_quality_label, png_quality_dropdown]\n",
        "dimensions_widgets = [use_original_dimensions_label, use_original_dimensions_dropdown, width_label, width_input, height_label, height_input]\n",
        "\n",
        "all_widgets = input_widgets + compression_quality_widgets + format_widgets + dimensions_widgets + [process_button]\n",
        "input_box = widgets.VBox(all_widgets)\n",
        "\n",
        "display(input_box)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
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        },
        "id": "SnCMAQt2BQuY",
        "outputId": "9bc2a9d4-d40d-4c8e-9e11-069678d20d33"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(Label(value='Input Directory:', layout=Layout(width='40%')), Text(value='/content/images', layo…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "8cdedc243dbd4463ab1ba696f39b23b5"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "126904491_2498244430469162_7443927954225604047_n.jpg processed and saved as jpeg\n",
            "ChrisEvans2023.jpg processed and saved as jpeg\n",
            "126361166_2498245567135715_4668557600125677782_n.jpg processed and saved as jpeg\n",
            "126298120_2498244220469183_7494224872683462910_n.jpg processed and saved as jpeg\n",
            "chris-evans-gettyimages-1138769185.jpg processed and saved as jpeg\n",
            "125882839_2498244717135800_4369754312076246234_n.jpg processed and saved as jpeg\n",
            "Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg processed and saved as jpeg\n",
            "126266971_2498244107135861_8853712875041431827_n.jpg processed and saved as jpeg\n",
            "126826015_2498244953802443_6444229007349497177_n.jpg processed and saved as jpeg\n",
            "Image compression and format conversion completed.\n",
            "126904491_2498244430469162_7443927954225604047_n.jpg processed and saved as png\n",
            "ChrisEvans2023.jpg processed and saved as png\n",
            "126361166_2498245567135715_4668557600125677782_n.jpg processed and saved as png\n",
            "126298120_2498244220469183_7494224872683462910_n.jpg processed and saved as png\n",
            "chris-evans-gettyimages-1138769185.jpg processed and saved as png\n",
            "125882839_2498244717135800_4369754312076246234_n.jpg processed and saved as png\n",
            "Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg processed and saved as png\n",
            "126266971_2498244107135861_8853712875041431827_n.jpg processed and saved as png\n",
            "126826015_2498244953802443_6444229007349497177_n.jpg processed and saved as png\n",
            "Image compression and format conversion completed.\n",
            "126904491_2498244430469162_7443927954225604047_n.jpg processed and saved as png\n",
            "ChrisEvans2023.jpg processed and saved as png\n",
            "126361166_2498245567135715_4668557600125677782_n.jpg processed and saved as png\n",
            "126298120_2498244220469183_7494224872683462910_n.jpg processed and saved as png\n",
            "chris-evans-gettyimages-1138769185.jpg processed and saved as png\n",
            "125882839_2498244717135800_4369754312076246234_n.jpg processed and saved as png\n",
            "Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg processed and saved as png\n",
            "126266971_2498244107135861_8853712875041431827_n.jpg processed and saved as png\n",
            "126826015_2498244953802443_6444229007349497177_n.jpg processed and saved as png\n",
            "Image compression and format conversion completed.\n",
            "126904491_2498244430469162_7443927954225604047_n.jpg processed and saved as png\n",
            "ChrisEvans2023.jpg processed and saved as png\n",
            "126361166_2498245567135715_4668557600125677782_n.jpg processed and saved as png\n",
            "126298120_2498244220469183_7494224872683462910_n.jpg processed and saved as png\n",
            "chris-evans-gettyimages-1138769185.jpg processed and saved as png\n",
            "125882839_2498244717135800_4369754312076246234_n.jpg processed and saved as png\n",
            "Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg processed and saved as png\n",
            "126266971_2498244107135861_8853712875041431827_n.jpg processed and saved as png\n",
            "126826015_2498244953802443_6444229007349497177_n.jpg processed and saved as png\n",
            "Image compression and format conversion completed.\n"
          ]
        }
      ]
    }
  ]
}