Upload SD3_leaf_inspired_inference.ipynb

SD3_leaf_inspired_inference.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "HHxHa_96z0gM"
+      },
+      "source": [
+        "# Stable Diffusion 3 medium fine-tuned for leaf-inspired generation\n",
+        "\n",
+        "Markus J. Buehler, MIT\n",
+        "mbuehler@MIT.EDU\n",
+        "\n",
+        "https://huggingface.co/lamm-mit/stable-diffusion-3-medium-leaf-inspired/"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 531
+        },
+        "id": "vQzwg68ByEiC",
+        "outputId": "895980fe-52df-49f5-fd02-bf0b2846f12f"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+            "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.10/dist-packages (0.23.5)\n",
+            "Collecting huggingface_hub\n",
+            "  Downloading huggingface_hub-0.24.0-py3-none-any.whl (419 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m419.0/419.0 kB\u001b[0m \u001b[31m6.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (3.15.4)\n",
+            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (2023.6.0)\n",
+            "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (24.1)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (6.0.1)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (2.31.0)\n",
+            "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (4.66.4)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (4.12.2)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (3.3.2)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (3.7)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2.0.7)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2024.7.4)\n",
+            "Installing collected packages: huggingface_hub\n",
+            "  Attempting uninstall: huggingface_hub\n",
+            "    Found existing installation: huggingface-hub 0.23.5\n",
+            "    Uninstalling huggingface-hub-0.23.5:\n",
+            "      Successfully uninstalled huggingface-hub-0.23.5\n",
+            "Successfully installed huggingface_hub-0.24.0\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "application/vnd.colab-display-data+json": {
+              "pip_warning": {
+                "packages": [
+                  "huggingface_hub"
+                ]
+              },
+              "id": "991053a6adb54643aed1b64c87e5d2b8"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "!pip install -q git+https://github.com/huggingface/diffusers.git\n",
+        "!pip install --upgrade huggingface_hub"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#### The Stable Diffusion 3 medium model is gated. Get access at:\n",
+        "\n",
+        "https://huggingface.co/stabilityai/stable-diffusion-3-medium\n",
+        "\n",
+        "Make sure you add your Hugging Face token and sign in."
+      ],
+      "metadata": {
+        "id": "HaYOIlR25nb2"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "hf_token = \"hf_----\"\n",
+        "from huggingface_hub import login\n",
+        "login(token=hf_token_write)"
+      ],
+      "metadata": {
+        "id": "hlVgYHNH5hgw"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "GSfz5tNZyC7V"
+      },
+      "outputs": [],
+      "source": [
+        "from diffusers import DiffusionPipeline\n",
+        "import torch\n",
+        "import os\n",
+        "from datetime import datetime\n",
+        "from PIL import Image\n",
+        "\n",
+        "def generate_filename(base_name, extension=\".png\"):\n",
+        "    timestamp = datetime.now().strftime(\"%Y%m%d_%H%M%S\")\n",
+        "    return f\"{base_name}_{timestamp}{extension}\"\n",
+        "\n",
+        "def save_image(image, directory, base_name=\"image_grid\"):\n",
+        "\n",
+        "    filename = generate_filename(base_name)\n",
+        "    file_path = os.path.join(directory, filename)\n",
+        "    image.save(file_path)\n",
+        "    print(f\"Image saved as {file_path}\")\n",
+        "\n",
+        "def image_grid(imgs, rows, cols, save=True, save_dir='generated_images', base_name=\"image_grid\",\n",
+        "              save_individual_files=False):\n",
+        "\n",
+        "    if not os.path.exists(save_dir):\n",
+        "        os.makedirs(save_dir)\n",
+        "\n",
+        "    assert len(imgs) == rows * cols\n",
+        "\n",
+        "    w, h = imgs[0].size\n",
+        "    grid = Image.new('RGB', size=(cols * w, rows * h))\n",
+        "    grid_w, grid_h = grid.size\n",
+        "\n",
+        "    for i, img in enumerate(imgs):\n",
+        "        grid.paste(img, box=(i % cols * w, i // cols * h))\n",
+        "        if save_individual_files:\n",
+        "            save_image(img, save_dir, base_name=base_name+f'_{i}-of-{len(imgs)}_')\n",
+        "\n",
+        "    if save and save_dir:\n",
+        "        save_image(grid, save_dir, base_name)\n",
+        "\n",
+        "    return grid"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "xaeDDt0IyYvh"
+      },
+      "outputs": [],
+      "source": [
+        "repo_id_load='lamm-mit/stable-diffusion-3-medium-leaf-inspired'\n",
+        "\n",
+        "pipeline = DiffusionPipeline.from_pretrained (\"stabilityai/stable-diffusion-3-medium-diffusers\",\n",
+        "                                              torch_dtype=torch.float16\n",
+        "                                             )\n",
+        "\n",
+        "pipeline.load_lora_weights(repo_id_load)\n",
+        "pipeline=pipeline.to('cuda')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "vqdIKEdy0BrU"
+      },
+      "outputs": [],
+      "source": [
+        "prompt          = \"a cube in the shape of a <leaf microstructure>\"\n",
+        "negative_prompt = \"\"\n",
+        "\n",
+        "num_samples = 2\n",
+        "num_rows = 2\n",
+        "n_steps=75\n",
+        "guidance_scale=15\n",
+        "all_images = []\n",
+        "\n",
+        "for _ in range(num_rows):\n",
+        "    image = pipeline(prompt,num_inference_steps=n_steps,num_images_per_prompt=num_samples,\n",
+        "                     guidance_scale=guidance_scale,negative_prompt=negative_prompt).images\n",
+        "\n",
+        "    all_images.extend(image)\n",
+        "\n",
+        "grid = image_grid(all_images, num_rows, num_samples,\n",
+        "                  save_individual_files=True,\n",
+        "                  save_dir='generated_images',\n",
+        "                  base_name=\"image_grid\",\n",
+        "                 )\n",
+        "grid"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "2yGuDJTH2zvx"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "gpuType": "A100",
+      "machine_shape": "hm",
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}