PhotoMaker_Demo.ipynb

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        "<a href=\"https://colab.research.google.com/github/yvrjsharma/HugginFace_Gradio/blob/main/PhotoMaker_Demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "!git clone https://github.com/TencentARC/PhotoMaker.git\n",
        "%cd PhotoMaker\n",
        "# Install requirements\n",
        "!pip install -r requirements.txt\n",
        "# Install photomaker\n",
        "!pip install git+https://github.com/TencentARC/PhotoMaker.git\n",
        "\n",
        "from photomaker import PhotoMakerStableDiffusionXLPipeline\n",
        "from huggingface_hub import hf_hub_download\n",
        "import torch\n",
        "import os\n",
        "from diffusers.utils import load_image\n",
        "from diffusers import EulerDiscreteScheduler\n",
        "from photomaker import PhotoMakerStableDiffusionXLPipeline\n",
        "from PIL import Image\n",
        "import gradio as gr\n",
        "\n",
        "photomaker_path = hf_hub_download(repo_id=\"TencentARC/PhotoMaker\", filename=\"photomaker-v1.bin\", repo_type=\"model\")\n",
        "base_model_path = 'SG161222/RealVisXL_V3.0'\n",
        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
        "\n",
        "### Load base model\n",
        "pipe = PhotoMakerStableDiffusionXLPipeline.from_pretrained(\n",
        "    base_model_path,  # can change to any base model based on SDXL\n",
        "    torch_dtype=torch.bfloat16,\n",
        "    use_safetensors=True,\n",
        "    variant=\"fp16\"\n",
        ").to(device)\n",
        "\n",
        "### Load PhotoMaker checkpoint\n",
        "pipe.load_photomaker_adapter(\n",
        "    os.path.dirname(photomaker_path),\n",
        "    subfolder=\"\",\n",
        "    weight_name=os.path.basename(photomaker_path),\n",
        "    trigger_word=\"img\"  # define the trigger word\n",
        ")\n",
        "pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)"
      ],
      "metadata": {
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      "execution_count": null,
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      "cell_type": "code",
      "source": [
        "def generate_image(files, prompt, negative_prompt):\n",
        "  # load the input ID images\n",
        "  files_list = []\n",
        "  for f in files:\n",
        "    img = Image.open(f.name)\n",
        "    files_list.append(img)\n",
        "  # Note that the trigger word `img` must follow the class word for personalization\n",
        "  generator = torch.Generator(device=device).manual_seed(42)\n",
        "  images = pipe(\n",
        "      prompt=prompt,\n",
        "      input_id_images=files_list,\n",
        "      negative_prompt=negative_prompt,\n",
        "      num_images_per_prompt=1,\n",
        "      num_inference_steps=50,\n",
        "      start_merge_step=10,\n",
        "      generator=generator,).images[0]\n",
        "  return [images]"
      ],
      "metadata": {
        "id": "vaFMd4YDUfgu"
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      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "logo = r\"\"\"<center><img src='https://photo-maker.github.io/assets/logo.png' alt='PhotoMaker logo' style=\"width:80px; margin-bottom:10px\"></center>\"\"\"\n",
        "title = r\"\"\"<h1 align=\"center\">PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding</h1>\"\"\"\n",
        "with gr.Blocks() as demo:\n",
        "    with gr.Row():\n",
        "      gr.Markdown(title)\n",
        "      gr.Markdown(logo)\n",
        "    with gr.Row():\n",
        "        files = gr.Files(\n",
        "                    label=\"Drag (Select) 1 or more photos of your face\",\n",
        "                    file_types=[\"image\"])\n",
        "        gallery = gr.Gallery(label=\"Generated Images\")\n",
        "    with gr.Row():\n",
        "        prompt = gr.Textbox(label=\"Prompt\",\n",
        "                  info=\"Try something like 'a photo of a man/woman img', 'img' is the trigger word.\",\n",
        "                  placeholder=\"A photo of a [man/woman img]...\")\n",
        "        negative_prompt = gr.Textbox(\n",
        "                label=\"Negative Prompt\",\n",
        "                placeholder=\"low quality\",\n",
        "                value=\"nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry\",)\n",
        "        submit = gr.Button(\"Submit\")\n",
        "\n",
        "\n",
        "    submit.click(generate_image, [files, prompt, negative_prompt], [gallery])\n",
        "\n",
        "demo.launch()"
      ],
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      "execution_count": 21,
      "outputs": [
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          "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://1443074086d29b3276.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"
          ]
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              "<div><iframe src=\"https://1443074086d29b3276.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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