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DiffSynth-Studio/examples/Diffutoon_toon_shading.ipynb
Artiprocher 0479618f5e add a jupyter example
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4",
"collapsed_sections": [
"tII_XRY-PJeo"
]
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"source": [
"# DiffSynth Studio\n",
"\n",
"Welcome to DiffSynth Studio! This is an example of Diffutoon."
],
"metadata": {
"id": "8ObdI5jCB8xy"
}
},
{
"cell_type": "markdown",
"source": [
"## Install"
],
"metadata": {
"id": "XSkKX7O2BwuM"
}
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "msCpt0pLnT8W",
"outputId": "48e084bc-c5ad-4d99-e5d9-8be686a57675"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cloning into 'DiffSynth-Studio'...\n",
"remote: Enumerating objects: 259, done.\u001b[K\n",
"remote: Counting objects: 100% (259/259), done.\u001b[K\n",
"remote: Compressing objects: 100% (168/168), done.\u001b[K\n",
"remote: Total 259 (delta 128), reused 203 (delta 81), pack-reused 0\u001b[K\n",
"Receiving objects: 100% (259/259), 967.07 KiB | 3.58 MiB/s, done.\n",
"Resolving deltas: 100% (128/128), done.\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m202.4/202.4 kB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m8.4/8.4 MB\u001b[0m \u001b[31m96.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.2/1.2 MB\u001b[0m \u001b[31m59.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.6/44.6 kB\u001b[0m \u001b[31m6.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.2/2.2 MB\u001b[0m \u001b[31m15.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m196.4/196.4 kB\u001b[0m \u001b[31m28.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.8/4.8 MB\u001b[0m \u001b[31m89.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m82.1/82.1 kB\u001b[0m \u001b[31m12.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.7/62.7 kB\u001b[0m \u001b[31m9.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Building wheel for controlnet-aux (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
"/content/DiffSynth-Studio\n"
]
}
],
"source": [
"!git clone https://github.com/Artiprocher/DiffSynth-Studio.git\n",
"!pip install -q transformers controlnet-aux==0.0.7 streamlit streamlit-drawable-canvas imageio imageio[ffmpeg] safetensors einops\n",
"%cd /content/DiffSynth-Studio"
]
},
{
"cell_type": "markdown",
"source": [
"## Download Models"
],
"metadata": {
"id": "5eCu_rlKB3kK"
}
},
{
"cell_type": "code",
"source": [
"import requests\n",
"\n",
"\n",
"def download_model(url, file_path):\n",
" model_file = requests.get(url, allow_redirects=True)\n",
" with open(file_path, \"wb\") as f:\n",
" f.write(model_file.content)\n",
"\n",
"download_model(\"https://civitai.com/api/download/models/229575\", \"models/stable_diffusion/aingdiffusion_v12.safetensors\")\n",
"download_model(\"https://huggingface.co/guoyww/animatediff/resolve/main/mm_sd_v15_v2.ckpt\", \"models/AnimateDiff/mm_sd_v15_v2.ckpt\")\n",
"download_model(\"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11p_sd15_lineart.pth\", \"models/ControlNet/control_v11p_sd15_lineart.pth\")\n",
"download_model(\"https://huggingface.co/lllyasviel/ControlNet-v1-1/resolve/main/control_v11f1e_sd15_tile.pth\", \"models/ControlNet/control_v11f1e_sd15_tile.pth\")\n",
"download_model(\"https://huggingface.co/lllyasviel/Annotators/resolve/main/sk_model.pth\", \"models/Annotators/sk_model.pth\")\n",
"download_model(\"https://huggingface.co/lllyasviel/Annotators/resolve/main/sk_model2.pth\", \"models/Annotators/sk_model2.pth\")\n",
"download_model(\"https://civitai.com/api/download/models/25820?type=Model&format=PickleTensor&size=full&fp=fp16\", \"models/textual_inversion/verybadimagenegative_v1.3.pt\")"
],
"metadata": {
"id": "9znMkpVj3qZ1"
},
"execution_count": 2,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## Run Diffutoon"
],
"metadata": {
"id": "iwOq2lWtKVYS"
}
},
{
"cell_type": "markdown",
"source": [
"### Config Template"
],
"metadata": {
"id": "tII_XRY-PJeo"
}
},
{
"cell_type": "code",
"source": [
"config_template = {\n",
" \"models\": {\n",
" \"model_list\": [\n",
" \"models/stable_diffusion/aingdiffusion_v12.safetensors\",\n",
" \"models/AnimateDiff/mm_sd_v15_v2.ckpt\",\n",
" \"models/ControlNet/control_v11f1e_sd15_tile.pth\",\n",
" \"models/ControlNet/control_v11p_sd15_lineart.pth\"\n",
" ],\n",
" \"textual_inversion_folder\": \"models/textual_inversion\",\n",
" \"device\": \"cuda\",\n",
" \"lora_alphas\": [],\n",
" \"controlnet_units\": [\n",
" {\n",
" \"processor_id\": \"tile\",\n",
" \"model_path\": \"models/ControlNet/control_v11f1e_sd15_tile.pth\",\n",
" \"scale\": 0.5\n",
" },\n",
" {\n",
" \"processor_id\": \"lineart\",\n",
" \"model_path\": \"models/ControlNet/control_v11p_sd15_lineart.pth\",\n",
" \"scale\": 0.5\n",
" }\n",
" ]\n",
" },\n",
" \"data\": {\n",
" \"input_frames\": {\n",
" \"video_file\": \"/content/video_guide.mp4\",\n",
" \"image_folder\": None,\n",
" \"height\": 1024,\n",
" \"width\": 1024,\n",
" \"start_frame_id\": 0,\n",
" \"end_frame_id\": 30\n",
" },\n",
" \"controlnet_frames\": [\n",
" {\n",
" \"video_file\": \"/content/video_guide.mp4\",\n",
" \"image_folder\": None,\n",
" \"height\": 1024,\n",
" \"width\": 1024,\n",
" \"start_frame_id\": 0,\n",
" \"end_frame_id\": 30\n",
" },\n",
" {\n",
" \"video_file\": \"/content/video_guide.mp4\",\n",
" \"image_folder\": None,\n",
" \"height\": 1024,\n",
" \"width\": 1024,\n",
" \"start_frame_id\": 0,\n",
" \"end_frame_id\": 30\n",
" }\n",
" ],\n",
" \"output_folder\": \"/content/output\",\n",
" \"fps\": 30\n",
" },\n",
" \"pipeline\": {\n",
" \"seed\": 0,\n",
" \"pipeline_inputs\": {\n",
" \"prompt\": \"best quality, perfect anime illustration, light, a girl is dancing, smile, solo\",\n",
" \"negative_prompt\": \"verybadimagenegative_v1.3\",\n",
" \"cfg_scale\": 7.0,\n",
" \"clip_skip\": 2,\n",
" \"denoising_strength\": 1.0,\n",
" \"num_inference_steps\": 10,\n",
" \"animatediff_batch_size\": 16,\n",
" \"animatediff_stride\": 8,\n",
" \"unet_batch_size\": 1,\n",
" \"controlnet_batch_size\": 1,\n",
" \"cross_frame_attention\": False,\n",
" # The following parameters will be overwritten. You don't need to modify them.\n",
" \"input_frames\": [],\n",
" \"num_frames\": 30,\n",
" \"width\": 1536,\n",
" \"height\": 1536,\n",
" \"controlnet_frames\": []\n",
" }\n",
" }\n",
"}"
],
"metadata": {
"id": "vsd2alA3PrGe"
},
"execution_count": 3,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"### Run\n",
"\n",
"Before you run the following code, please upload your input video.\n",
"\n",
"We highly recommend you to use a higher resolution for better visual quality. The default resolution of Diffutoon is 1536x1536, which requires 22GB VRAM. If you don't have enough VRAM, 1024x1024 is also acceptable."
],
"metadata": {
"id": "113QAmNHP6T_"
}
},
{
"cell_type": "code",
"source": [
"from diffsynth import SDVideoPipelineRunner\n",
"\n",
"\n",
"config = config_template.copy()\n",
"config[\"data\"][\"input_frames\"] = {\n",
" \"video_file\": \"/content/input_video.mp4\",\n",
" \"image_folder\": None,\n",
" \"height\": 1024,\n",
" \"width\": 1024,\n",
" \"start_frame_id\": 0,\n",
" \"end_frame_id\": 16\n",
"}\n",
"config[\"data\"][\"controlnet_frames\"] = [config[\"data\"][\"input_frames\"], config[\"data\"][\"input_frames\"]]\n",
"config[\"data\"][\"output_folder\"] = \"/content/output\"\n",
"config[\"data\"][\"fps\"] = 30\n",
"\n",
"runner = SDVideoPipelineRunner()\n",
"runner.run(config)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "761nbrgeKMvj",
"outputId": "aea6f1fe-8485-4eb1-ac23-9c1023b3b9cd"
},
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 16/16 [00:00<00:00, 82.74it/s]\n",
"100%|██████████| 16/16 [00:04<00:00, 3.71it/s]\n",
"100%|██████████| 10/10 [05:17<00:00, 31.78s/it]\n",
"Saving images: 100%|██████████| 16/16 [00:06<00:00, 2.38it/s]\n",
"Saving video: 100%|██████████| 16/16 [00:00<00:00, 31.93it/s]\n"
]
}
]
}
]
}
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