notebooks/flux.1-image-generation/flux.1-image-generation.ipynb

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   "source": [
    "# Image generation with Flux.1 and OpenVINO\n",
    "\n",
    "Flux is a AI image generation model developed by [Black Forest Labs](https://blackforestlabs.ai/our-team/). It represents a significant advancement in AI-generated art, utilizing a hybrid architecture of [multimodal](https://arxiv.org/abs/2403.03206) and [parallel](https://arxiv.org/abs/2302.05442) [diffusion transformer](https://arxiv.org/abs/2212.09748) blocks and scaled to 12B parameter. The model offers state-of-the-art performance image generation with top of the line prompt following, visual quality, image detail and output diversity. More details about model can be found in [blog post](https://blackforestlabs.ai/announcing-black-forest-labs/) and [original repo](https://github.com/black-forest-labs/flux).\n",
    "\n",
    "<img src=\"https://raw.githubusercontent.com/black-forest-labs/flux/main/assets/grid.jpg\" width=\"1024\" height=\"800\"> \n",
    "\n",
    "In this tutorial we consider how to convert and optimize Flux.1 model using OpenVINO.\n",
    "\n",
    ">**Note**: Some demonstrated models can require at least 32GB RAM for conversion and running.\n",
    "\n",
    "#### Table of contents:\n",
    "\n",
    "- [Prerequisites](#Prerequisites)\n",
    "- [Select model](#Select-model)\n",
    "- [Convert model with OpenVINO](#Convert-model-with-OpenVINO)\n",
    "  - [Convert model using Optimum Intel](#Convert-model-using-Optimum-Intel)\n",
    "  - [Compress model weights](#Compress-model-weights)\n",
    "  - [Use optimized models provided on HuggingFace Hub](#use-optimized-models-provided-on-huggingface-hub)\n",
    "- [Run OpenVINO model inference](#Run-OpenVINO-model-inference)\n",
    "- [Interactive demo](#Interactive-demo)\n",
    "\n",
    "\n",
    "\n",
    "<img referrerpolicy=\"no-referrer-when-downgrade\" src=\"https://static.scarf.sh/a.png?x-pxid=5b5a4db0-7875-4bfb-bdbd-01698b5b1a77&file=notebooks/flux.1-image-generation/flux.1-image-generation.ipynb\" />\n",
    "\n",
    "### Installation Instructions\n",
    "\n",
    "This is a self-contained example that relies solely on its own code.\n",
    "\n",
    "We recommend  running the notebook in a virtual environment. You only need a Jupyter server to start.\n",
    "For details, please refer to [Installation Guide](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/README.md#-installation-guide)."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "97ce9e70-fdce-4187-a0ea-c69e0001e25a",
   "metadata": {},
   "source": [
    "## Prerequisites\n",
    "[back to top ⬆️](#Table-of-contents:)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b05ef521",
   "metadata": {},
   "outputs": [],
   "source": [
    "import platform\n",
    "\n",
    "%pip install -q \"gradio>=4.19\" \"torch>=2.1\" \"transformers\" \"nncf>=2.15.0\" \"diffusers>=0.31.0\" \"opencv-python\" \"pillow\" \"peft>=0.7.0\" --extra-index-url https://download.pytorch.org/whl/cpu\n",
    "%pip install -q \"sentencepiece\" \"protobuf\"\n",
    "%pip install -q \"git+https://github.com/huggingface/optimum-intel.git\"\n",
    "%pip install -qU \"openvino>=2025.0\" \"openvino_genai>=2025.0\" \"openvino_tokenizers>=2025.0\"\n",
    "\n",
    "if platform.system() == \"Darwin\":\n",
    "    %pip install -q \"numpy<2.0.0\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "64fff924",
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "from pathlib import Path\n",
    "\n",
    "if not Path(\"cmd_helper.py\").exists():\n",
    "    r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/cmd_helper.py\")\n",
    "    open(\"cmd_helper.py\", \"w\").write(r.text)\n",
    "\n",
    "if not Path(\"gradio_helper.py\").exists():\n",
    "    r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/flux.1-image-generation/gradio_helper.py\")\n",
    "    open(\"gradio_helper.py\", \"w\").write(r.text)\n",
    "\n",
    "if not Path(\"notebook_utils.py\").exists():\n",
    "    r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py\")\n",
    "    open(\"notebook_utils.py\", \"w\").write(r.text)\n",
    "\n",
    "# Read more about telemetry collection at https://github.com/openvinotoolkit/openvino_notebooks?tab=readme-ov-file#-telemetry\n",
    "from notebook_utils import collect_telemetry\n",
    "\n",
    "collect_telemetry(\"flux.1-image-generation.ipynb\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "592f926e-e4e4-4232-9c20-a986ddfcc4a5",
   "metadata": {},
   "source": [
    "## Select model\n",
    "[back to top ⬆️](#Table-of-contents:)\n",
    "\n",
    "To strike a balance between accessibility and model capabilities, FLUX.1 comes in three variants: FLUX.1-pro, FLUX.1-dev and FLUX.1-schnell: \n",
    "* **FLUX.1-pro**: The best of FLUX.1, offering state-of-the-art performance image generation with top of the line prompt following, visual quality, image detail and output diversity, but not available for public usage.\n",
    "* **FLUX.1-dev**: FLUX.1-dev is an open-weight, guidance-distilled models. Directly distilled from FLUX.1-pro, FLUX.1-dev obtains similar quality and prompt adherence capabilities, while being more efficient than a standard model of the same size. FLUX.1-dev weights are available on [HuggingFace](https://huggingface.co/black-forest-labs/FLUX.1-dev).\n",
    "* **FLUX.1-schnell**: the fastest model from Flux family is tailored for local development and personal use. FLUX.1-schnell is openly available under an Apache2.0 license. Similar, FLUX.1-dev, weights are available on [HuggingFace](https://huggingface.co/black-forest-labs/FLUX.1-schnell).\n",
    "\n",
    "![family.png](https://github.com/user-attachments/assets/c7f9df6b-cff3-4d33-98d7-1bb400b2861c)\n",
    "\n",
    "Be default, we will use FLUX.1-schnell model, but you can switch to FLUX.1-dev version using widget bellow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fd654a72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ace2c626d65c4cfca37806eed8b89ce6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Dropdown(description='Model:', options=('black-forest-labs/FLUX.1-schnell', 'black-forest-labs/FLUX.1-dev'), v…"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import ipywidgets as widgets\n",
    "\n",
    "model_ids = [\"black-forest-labs/FLUX.1-schnell\", \"black-forest-labs/FLUX.1-dev\"]\n",
    "\n",
    "model_selector = widgets.Dropdown(\n",
    "    options=model_ids,\n",
    "    default=model_ids[0],\n",
    "    description=\"Model:\",\n",
    ")\n",
    "\n",
    "\n",
    "model_selector"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "2578fc91-dda4-4a0b-9353-5654d2763905",
   "metadata": {},
   "source": [
    ">**Note**: run Flux.1-dev model with notebook, you will need to accept license agreement. \n",
    ">You must be a registered user in 🤗 Hugging Face Hub. Please visit [HuggingFace model card](https://huggingface.co/black-forest-labs/FLUX.1-dev), carefully read terms of usage and click accept button.  You will need to use an access token for the code below to run. For more information on access tokens, refer to [this section of the documentation](https://huggingface.co/docs/hub/security-tokens).\n",
    ">You can login on Hugging Face Hub in notebook environment, using following code:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c2676359",
   "metadata": {},
   "outputs": [],
   "source": [
    "# uncomment these lines to login to huggingfacehub to get access to pretrained model\n",
    "\n",
    "# from huggingface_hub import notebook_login, whoami\n",
    "\n",
    "# try:\n",
    "#     whoami()\n",
    "#     print('Authorization token already provided')\n",
    "# except OSError:\n",
    "#     notebook_login()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "10fee712-3dbe-4c2e-9bb2-b8a760a4d1f3",
   "metadata": {},
   "source": [
    "## Convert model with OpenVINO\n",
    "[back to top ⬆️](#Table-of-contents:)\n",
    "\n",
    "Starting from 2023.0 release, OpenVINO supports PyTorch models directly via Model Conversion API. `ov.convert_model` function accepts instance of PyTorch model and example inputs for tracing and returns object of `ov.Model` class, ready to use or save on disk using `ov.save_model` function. \n",
    "\n",
    "\n",
    "The pipeline consists of four important parts:\n",
    "\n",
    "* Clip and T5 Text Encoders to create condition to generate an image from a text prompt.\n",
    "* Transformer for step-by-step denoising latent image representation.\n",
    "* Autoencoder (VAE) for decoding latent space to image.\n",
    "  \n",
    "### Convert model using Optimum Intel\n",
    "[back to top ⬆️](#Table-of-contents:)\n",
    "\n",
    "For convenience, we will use OpenVINO integration with HuggingFace Optimum. 🤗 [Optimum Intel](https://huggingface.co/docs/optimum/intel/index) is the interface between the 🤗 Transformers and Diffusers libraries and the different tools and libraries provided by Intel to accelerate end-to-end pipelines on Intel architectures.\n",
    "\n",
    "Among other use cases, Optimum Intel provides a simple interface to optimize your Transformers and Diffusers models, convert them to the OpenVINO Intermediate Representation (IR) format and run inference using OpenVINO Runtime. `optimum-cli` provides command line interface for model conversion and optimization. \n",
    "\n",
    "General command format:\n",
    "\n",
    "```bash\n",
    "optimum-cli export openvino --model <model_id_or_path> --task <task> <output_dir>\n",
    "```\n",
    "\n",
    "where task is task to export the model for, if not specified, the task will be auto-inferred based on the model. You can find a mapping between tasks and model classes in Optimum TaskManager [documentation](https://huggingface.co/docs/optimum/exporters/task_manager). Additionally, you can specify weights compression using `--weight-format` argument with one of following options: `fp32`, `fp16`, `int8` and `int4`. Fro int8 and int4 [nncf](https://github.com/openvinotoolkit/nncf) will be used for  weight compression. More details about model export provided in [Optimum Intel documentation](https://huggingface.co/docs/optimum/intel/openvino/export#export-your-model).\n",
    "\n",
    "### Compress model weights\n",
    "[back to top ⬆️](#Table-of-contents:)\n",
    "\n",
    "For reducing model memory consumption we will use weights compression. The [Weights Compression](https://docs.openvino.ai/2024/openvino-workflow/model-optimization-guide/weight-compression.html) algorithm is aimed at compressing the weights of the models and can be used to optimize the model footprint and performance of large models where the size of weights is relatively larger than the size of activations, for example, Large Language Models (LLM). Compared to INT8 compression, INT4 compression improves performance even more, but introduces a minor drop in prediction quality. We will use [NNCF](https://github.com/openvinotoolkit/nncf) integration to `optimum-cli` tool for weight compression.\n",
    "\n",
    "### Use optimized models provided on HuggingFace Hub\n",
    "[back to top ⬆️](#Table-of-contents:)\n",
    "\n",
    "For quick start, OpenVINO provides [collection](https://huggingface.co/collections/OpenVINO/image-generation-67697d9952fb1eee4a252aa8) of optimized models that are ready to use with OpenVINO GenAI. You can download them using following command:\n",
    "\n",
    "```bash\n",
    "huggingface-cli download <model_id> --local-dir <output_dir>\n",
    "```\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "add19dd3",
   "metadata": {
    "test_replace": {
     "use_preconverted = widgets.Checkbox(value=True": "use_preconverted = widgets.Checkbox(value=False"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b8e0bde4eb0e41f5b0cf3a9be3d50bd0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Checkbox(value=True, description='Weight compression')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "use_preconverted = widgets.Checkbox(value=True, description=\"Use preconverted model\", disable=False)\n",
    "\n",
    "to_compress = widgets.Checkbox(\n",
    "    value=True,\n",
    "    description=\"Weight compression\",\n",
    "    disabled=False,\n",
    ")\n",
    "\n",
    "visible_widgets = [to_compress]\n",
    "\n",
    "if \"schnell\" in model_selector.value:\n",
    "    visible_widgets.append(use_preconverted)\n",
    "\n",
    "options = widgets.VBox(visible_widgets)\n",
    "\n",
    "options"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8e46869c",
   "metadata": {
    "test_replace": {
     "64": "-1",
     "model_selector.value": "\"katuni4ka/tiny-random-flux\""
    }
   },
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "model_id = model_selector.value\n",
    "\n",
    "model_base_dir = Path(model_id.split(\"/\")[-1])\n",
    "additional_args = {}\n",
    "\n",
    "if to_compress.value:\n",
    "    model_dir = model_base_dir / \"INT4\"\n",
    "    additional_args.update({\"weight-format\": \"int4\", \"group-size\": \"64\", \"ratio\": \"1.0\"})\n",
    "else:\n",
    "    model_dir = model_base_dir / \"FP16\"\n",
    "    additional_args.update({\"weight-format\": \"fp16\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f6c7bb34",
   "metadata": {},
   "outputs": [],
   "source": [
    "from cmd_helper import optimum_cli\n",
    "\n",
    "if not model_dir.exists():\n",
    "    if not use_preconverted.value:\n",
    "        optimum_cli(model_id, model_dir, additional_args=additional_args)\n",
    "    else:\n",
    "        ov_model_id = f\"OpenVINO/{model_id.split('/')[-1]}-{model_dir.name.lower()}-ov\"\n",
    "        !huggingface-cli download {ov_model_id} --local-dir {model_dir}"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "2bf6b6a4-0fc0-425d-acbf-5ac0df8dd993",
   "metadata": {},
   "source": [
    "## Run OpenVINO GenAI model inference\n",
    "[back to top ⬆️](#Table-of-contents:)\n",
    "\n",
    "Select device from dropdown list for running inference using OpenVINO."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "719aa55a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6bd1ea3ea00b4b75af6c71b86a8133f4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Dropdown(description='Device:', options=('CPU', 'AUTO'), value='CPU')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from notebook_utils import device_widget\n",
    "\n",
    "device = device_widget(default=\"CPU\", exclude=[\"NPU\"])\n",
    "device"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f1d71c44-761a-45f8-858c-e60a9a625dd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c771b3bc675946b8b0a628729a04e0f9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Checkbox(value=True, description='Use compressed models')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import ipywidgets as widgets\n",
    "\n",
    "model_available = (model_base_dir / \"INT4\").is_dir()\n",
    "use_quantized_models = widgets.Checkbox(\n",
    "    value=model_available,\n",
    "    description=\"Use compressed models\",\n",
    "    disabled=not model_available,\n",
    ")\n",
    "\n",
    "use_quantized_models"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "cab6790e",
   "metadata": {},
   "source": [
    "`openvino_genai.Text2ImagePipeline` represents inference pipeline for text-to-image generation. For creation pipeline instance, you should provide directory with converted to OpenVINO model and inference device."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a7230b71",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "import openvino_genai as ov_genai\n",
    "\n",
    "model_dir = model_base_dir / \"INT4\" if use_quantized_models.value else model_base_dir / \"FP16\"\n",
    "\n",
    "ov_pipe = ov_genai.Text2ImagePipeline(model_dir, device=device.value)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "75aeb184",
   "metadata": {},
   "source": [
    "Now, you can define a text prompt and other pipeline settings for image generation and run inference pipeline.\n",
    "\n",
    "> **Note**: Consider increasing `num_inference_steps` to get more precise results, but higher value will take longer time to process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "49dc632b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pipeline settings\n",
      "Input text: A cat holding a sign that says hello OpenVINO\n",
      "Image size: 256 x 256\n",
      "Seed: 42\n",
      "Number of steps: 4\n"
     ]
    }
   ],
   "source": [
    "prompt = \"A cat holding a sign that says hello OpenVINO\"\n",
    "height = 256\n",
    "width = 256\n",
    "seed = 42\n",
    "num_inference_steps = 4\n",
    "\n",
    "print(\"Pipeline settings\")\n",
    "print(f\"Input text: {prompt}\")\n",
    "print(f\"Image size: {height} x {width}\")\n",
    "print(f\"Seed: {seed}\")\n",
    "print(f\"Number of steps: {num_inference_steps}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "dc06a9c8",
   "metadata": {},
   "outputs": [
    {
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       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/4 [00:00<?, ?it/s]"
      ]
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     "output_type": "display_data"
    },
    {
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",
      "image/png": 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      "text/plain": [
       "<PIL.Image.Image image mode=RGB size=256x256>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from PIL import Image\n",
    "from tqdm.notebook import tqdm\n",
    "import sys\n",
    "\n",
    "random_generator = ov_genai.TorchGenerator(seed)\n",
    "pbar = tqdm(total=num_inference_steps)\n",
    "\n",
    "\n",
    "def callback(step, num_steps, latent):\n",
    "    if num_steps != pbar.total:\n",
    "        pbar.reset(num_steps)\n",
    "    pbar.update(1)\n",
    "    sys.stdout.flush()\n",
    "    return False\n",
    "\n",
    "\n",
    "result = ov_pipe.generate(prompt, num_inference_steps=num_inference_steps, generator=random_generator, callback=callback, height=height, width=width)\n",
    "\n",
    "pbar.close()\n",
    "\n",
    "final_image = Image.fromarray(result.data[0])\n",
    "\n",
    "final_image"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "e7b8cee1-9e46-46f6-a4ef-b3bc132aaa01",
   "metadata": {},
   "source": [
    "## Interactive demo\n",
    "[back to top ⬆️](#Table-of-contents:)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88519e1b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from gradio_helper import make_demo\n",
    "\n",
    "demo = make_demo(ov_pipe, model_name=str(model_base_dir))\n",
    "\n",
    "# if you are launching remotely, specify server_name and server_port\n",
    "#  demo.launch(server_name='your server name', server_port='server port in int')\n",
    "# if you have any issue to launch on your platform, you can pass share=True to launch method:\n",
    "# demo.launch(share=True)\n",
    "# it creates a publicly shareable link for the interface. Read more in the docs: https://gradio.app/docs/\n",
    "try:\n",
    "    demo.launch(debug=True)\n",
    "except Exception:\n",
    "    demo.launch(debug=True, share=True)"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  },
  "openvino_notebooks": {
   "imageUrl": "https://github.com/user-attachments/assets/11733314-0b31-449c-9885-12ebf6365a58",
   "tags": {
    "categories": [
     "Model Demos",
     "AI Trends"
    ],
    "libraries": [],
    "other": [
     "Stable Diffusion"
    ],
    "tasks": [
     "Text-to-Image"
    ]
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