{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "5rbnEz_FTJKL"
},
"outputs": [],
"source": [
"\n",
"######################################################################\n",
"!pip install -q --upgrade diffusers\n",
"!pip install -q --upgrade transformers\n",
"!pip install -q --upgrade tokenizers\n",
"######################################################################\n",
"!pip install -q --upgrade peft\n",
"######################################################################\n",
"#!pip install diffusers==0.21.1 transformers==4.33.2 tokenizers==0.13.3\n",
"######################################################################\n",
"\n",
"!pip install -q accelerate\n",
"!pip install -q safetensors\n",
"!pip install -q einops\n",
"!pip install -q onnxruntime-gpu\n",
"!pip install -q dlib\n",
"!pip install -q opencv-python\n",
"!pip install -q git+https://github.com/tencent-ailab/IP-Adapter.git"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "hThiB6kxTJKM"
},
"outputs": [],
"source": [
"import torch\n",
"from diffusers.utils import load_image\n",
"from PIL import Image\n",
"import os\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "RB9wDFckTJKN"
},
"outputs": [],
"source": [
"\n",
"os.makedirs(\"images\", exist_ok=True)\n",
"!wget --continue https://upload.wikimedia.org/wikipedia/commons/thumb/0/0f/1665_Girl_with_a_Pearl_Earring.jpg/800px-1665_Girl_with_a_Pearl_Earring.jpg -O images/Girl_with_a_Pearl_Earring.jpg\n",
"\n",
"!wget --continue https://huggingface.co/datasets/Norod78/ip-adapter-face-full-test/resolve/main/shape_predictor_5_face_landmarks.dat?download=true -O shape_predictor_5_face_landmarks.dat\n",
"\n",
"!wget --continue https://huggingface.co/datasets/Norod78/ip-adapter-face-full-test/raw/main/crop_head_dlib5.py -O crop_head_dlib5.py"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "kfvMkQD6TJKP"
},
"outputs": [],
"source": [
"import torch\n",
"from diffusers import StableDiffusionXLPipeline, DDIMScheduler, AutoencoderKL\n",
"from huggingface_hub import hf_hub_download\n",
"from diffusers.utils import load_image\n",
"from ip_adapter import IPAdapterFull\n",
"from PIL import Image\n",
"\n",
"def image_grid(imgs, rows, cols):\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",
" return grid\n",
"\n",
"noise_scheduler = DDIMScheduler(\n",
" num_train_timesteps=1000,\n",
" beta_start=0.00085,\n",
" beta_end=0.012,\n",
" beta_schedule=\"scaled_linear\",\n",
" clip_sample=False,\n",
" set_alpha_to_one=False,\n",
" steps_offset=1\n",
")\n",
"\n",
"base_model_path = \"stabilityai/stable-diffusion-xl-base-1.0\"\n",
"vae_model_path = \"madebyollin/sdxl-vae-fp16-fix\"\n",
"ip_ckpt = hf_hub_download(repo_id=\"h94/IP-Adapter\", subfolder=\"sdxl_models\", filename=\"ip-adapter-plus-face_sdxl_vit-h.safetensors\", repo_type=\"model\")\n",
"image_encoder_path = \"laion/CLIP-ViT-H-14-laion2B-s32B-b79K\"\n",
"device = \"cuda\"\n",
"\n",
"with torch.no_grad():\n",
" print(\"Loading vae\")\n",
" vae = AutoencoderKL.from_pretrained(vae_model_path).to(dtype=torch.float16)\n",
" print(\"Loading pipeline\")\n",
" pipe = StableDiffusionXLPipeline.from_pretrained(\n",
" base_model_path,\n",
" variant=\"fp16\",\n",
" torch_dtype=torch.float16,\n",
" scheduler=noise_scheduler,\n",
" vae=vae,\n",
" feature_extractor=None,\n",
" safety_checker=None\n",
" )\n",
"print(\"Done\")\n",
"\n"
]
},
{
"cell_type": "code",
"source": [
"\n",
"#lora_weights = hf_hub_download(repo_id=\"Norod78/SDXL-YarnArtStyle-LoRA\", filename=\"SDXL_Yarn_Art_Style.safetensors\", repo_type=\"model\")\n",
"lora_weights = hf_hub_download(repo_id=\"Norod78/SDXL-Psychemelt-style-LoRA\" , filename=\"SDXL_Psychemelt_style_LoRA-000007.safetensors\", repo_type=\"model\")\n",
"\n",
"############################################################################################################################################\n",
"pipe.load_lora_weights(lora_weights)\n",
"############################################################################################################################################\n"
],
"metadata": {
"id": "byQMEGplF0FD"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "ksM5XrlmTJKQ"
},
"outputs": [],
"source": [
"from ip_adapter import IPAdapterPlusXL\n",
"# load ip-adapter\n",
"with torch.no_grad():\n",
" ip_model = IPAdapterPlusXL(pipe, image_encoder_path, ip_ckpt, device, num_tokens=16)\n"
]
},
{
"cell_type": "code",
"source": [
"import crop_head_dlib5\n",
"# Detect and crop the head\n",
"cropped_head = crop_head_dlib5.detect_and_crop_head(\"images/Girl_with_a_Pearl_Earring.jpg\", factor=4.5)\n",
"image = cropped_head.resize((224, 224))\n",
"image"
],
"metadata": {
"id": "2xz5rU5OIA-R"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "xGjbgEdBTJKQ"
},
"outputs": [],
"source": [
"prompt = \"full body photo of a woman standing outdoors in a field, wearing a colorful dress in an LSD trip psychemelt style\"\n",
"negative_prompt = \"monochrome, lowres, bad anatomy, worst quality, low quality, blurry, extra limbs, nude, naked, nsfw\"\n",
"with torch.no_grad():\n",
" images = ip_model.generate(\n",
" prompt=prompt, negative_prompt=negative_prompt, pil_image=image, scale=0.85, guidance_scale=7.5, num_samples=4, width=1024, height=1280, num_inference_steps=30, seed=2024,\n",
" )\n",
"\n",
"grid = image_grid(images, 2, 2)\n",
"grid\n"
]
},
{
"cell_type": "code",
"source": [
"!wget --continue https://upload.wikimedia.org/wikipedia/commons/0/0f/SDCC_2015_-_Gal_Gadot_%2819742671671%29_%28cropped%29.jpg -O images/gal_gadot_full_body.jpg\n",
"cropped_head = crop_head_dlib5.detect_and_crop_head(\"images/gal_gadot_full_body.jpg\", factor=2.5)\n",
"image = cropped_head.resize((224, 224))\n",
"image"
],
"metadata": {
"id": "RePEtucoHcyS"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"\n",
"with torch.no_grad():\n",
" images = ip_model.generate(\n",
" prompt=prompt, negative_prompt=negative_prompt, pil_image=image, scale=0.85, guidance_scale=7.5, num_samples=4, width=1024, height=1280, num_inference_steps=30, seed=2024,\n",
" )\n",
"\n",
"grid = image_grid(images, 2, 2)\n",
"grid"
],
"metadata": {
"id": "Ic2r3eJoHn6B"
},
"execution_count": null,
"outputs": []
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"provenance": [],
"machine_shape": "hm",
"gpuType": "L4",
"private_outputs": true
},
"kernelspec": {
"display_name": "Python 3",
"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": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 0
}