Rename Notebooks/b to Notebooks/Fast-Dreambooth-v1.5.ipynb

Notebooks/Fast-Dreambooth-v1.5.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "494d5ce4-5843-4d70-ae96-c1983e21b6e8",
+   "metadata": {},
+   "source": [
+    "## Dreambooth v1.5 Paperspace Notebook From https://github.com/TheLastBen/fast-stable-diffusion, if you encounter any issues, feel free to discuss them. [Support](https://ko-fi.com/thelastben)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8afdca63-eff3-4a9d-b4d9-127c0f028033",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# Dependencies"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "be74b2d5-da96-4bf4-ae82-4fe4b8abc04c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Install the dependencies\n",
+    "\n",
+    "force_reinstall= False\n",
+    "\n",
+    "# Set to true only if you want to install the dependencies again.\n",
+    "\n",
+    "\n",
+    "#--------------------\n",
+    "with open('/dev/null', 'w') as devnull:import requests, os, time, importlib;open('/notebooks/mainpaperspacev1.py', 'wb').write(requests.get('https://huggingface.co/datasets/TheLastBen/PPS/raw/main/Scripts/mainpaperspacev1.py').content); os.chdir('/notebooks');time.sleep(3);import mainpaperspacev1;importlib.reload(mainpaperspacev1);from mainpaperspacev1 import *;Deps(force_reinstall)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7a4ef4a2-6863-4603-9254-a1e2a547ee38",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "# Download the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a1ba734e-515b-4761-8c88-ef7f165d7971",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#Leave everything EMPTY to use the original model\n",
+    "\n",
+    "Path_to_HuggingFace= \"\"\n",
+    "\n",
+    "# Load and finetune a model from Hugging Face, use the format \"profile/model\" like : runwayml/stable-diffusion-v1-5\n",
+    "\n",
+    "\n",
+    "CKPT_Path = \"\"\n",
+    "\n",
+    "# Load a CKPT model from the storage.\n",
+    "\n",
+    "\n",
+    "CKPT_Link = \"\"\n",
+    "\n",
+    "# A CKPT direct link, huggingface CKPT link or a shared CKPT from gdrive.\n",
+    "\n",
+    "\n",
+    "#----------------\n",
+    "MODEL_NAME=dl(Path_to_HuggingFace, CKPT_Path, CKPT_Link)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4c6c4932-e614-4f5e-8d4a-4feca5ce54f5",
+   "metadata": {},
+   "source": [
+    "# Create/Load a Session"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b6595c37-8ad2-45ff-a055-fe58c6663d2f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "Session_Name = \"\"\n",
+    "\n",
+    "# Enter the session name, it if it exists, it will load it, otherwise it'll create an new session.\n",
+    "\n",
+    "\n",
+    "Session_Link_optional = \"\"\n",
+    "\n",
+    "# Import a session from another gdrive, the shared gdrive link must point to the specific session's folder that contains the trained CKPT, remove any intermediary CKPT if any.\n",
+    "\n",
+    "\n",
+    "#-----------------\n",
+    "[PT, WORKSPACE, Session_Name, INSTANCE_NAME, OUTPUT_DIR, SESSION_DIR, CONCEPT_DIR, INSTANCE_DIR, CAPTIONS_DIR, MDLPTH, MODEL_NAME, resume]=sess(Session_Name, Session_Link_optional, MODEL_NAME if 'MODEL_NAME' in locals() else \"\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5698de61-08d3-4d90-83ef-f882ed956d01",
+   "metadata": {},
+   "source": [
+    "# Instance Images"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bc2f8f28-226e-45b8-8257-804bbb711f56",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "Remove_existing_instance_images= True\n",
+    "\n",
+    "# Set to False to keep the existing instance images if any.\n",
+    "\n",
+    "\n",
+    "IMAGES_FOLDER_OPTIONAL=\"\"\n",
+    "\n",
+    "# If you prefer to specify directly the folder of the pictures instead of uploading, this will add the pictures to the existing (if any) instance images. Leave EMPTY to upload.\n",
+    "\n",
+    "\n",
+    "Smart_crop_images= True\n",
+    "\n",
+    "# Automatically crop your input images.\n",
+    "\n",
+    "\n",
+    "Crop_size = 512\n",
+    "\n",
+    "# Choices: \"512\", \"576\", \"640\", \"704\", \"768\", \"832\", \"896\", \"960\", \"1024\"\n",
+    "\n",
+    "# Check out this example for naming : https://i.imgur.com/d2lD3rz.jpeg\n",
+    "\n",
+    "\n",
+    "#-----------------\n",
+    "uplder(Remove_existing_instance_images, Smart_crop_images, Crop_size, IMAGES_FOLDER_OPTIONAL, INSTANCE_DIR, CAPTIONS_DIR, False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0e93924f-a6bf-45d5-aa77-915ad7385dcd",
+   "metadata": {},
+   "source": [
+    "# Manual Captioning"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c5dbcb29-b42f-4cfc-9be8-83355838d5a2",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Open a tool to manually caption the instance images.\n",
+    "\n",
+    "#-----------------\n",
+    "caption(CAPTIONS_DIR, INSTANCE_DIR)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c90140c1-6c91-4cae-a222-e1a746957f95",
+   "metadata": {},
+   "source": [
+    "# Concept Images"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "55c27688-8601-4943-b61d-fc48b9ded067",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Remove_existing_concept_images= True\n",
+    "\n",
+    "# Set to False to keep the existing concept images if any.\n",
+    "\n",
+    "\n",
+    "IMAGES_FOLDER_OPTIONAL=\"\"\n",
+    "\n",
+    "# If you prefer to specify directly the folder of the pictures instead of uploading, this will add the pictures to the existing (if any) concept images. Leave EMPTY to upload.\n",
+    "\n",
+    "\n",
+    "#-----------------\n",
+    "uplder(Remove_existing_concept_images, True, 512, IMAGES_FOLDER_OPTIONAL, CONCEPT_DIR, CAPTIONS_DIR, True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2a4aa42a-fd68-41ad-9ba7-da99f834e2c1",
+   "metadata": {},
+   "source": [
+    "# Dreambooth"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "612d8335-b984-4f34-911d-5457ff98e507",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Resume_Training = False\n",
+    "\n",
+    "# If you're not satisfied with the result, Set to True, run again the cell and it will continue training the current model.\n",
+    "\n",
+    "\n",
+    "UNet_Training_Steps=1500\n",
+    "\n",
+    "UNet_Learning_Rate = \"4e-6\"\n",
+    "\n",
+    "# If you use 10 images, use 1500 steps, if you're not satisfied with the result, resume training for another 200 steps, and so on ...\n",
+    "\n",
+    "\n",
+    "Text_Encoder_Training_Steps=300\n",
+    "\n",
+    "Text_Encoder_Learning_Rate= \"1e-6\"\n",
+    "\n",
+    "# 350-600 steps is enough for a small dataset, keep this number small to avoid overfitting, set to 0 to disable, set it to 0 before resuming training if it is already trained.\n",
+    "\n",
+    "\n",
+    "Text_Encoder_Concept_Training_Steps=0\n",
+    "\n",
+    "# Suitable for training a style/concept as it acts as regularization, with a minimum of 300 steps, 1 step/image is enough to train the concept(s), set to 0 to disable, set both the settings above to 0 to fintune only the text_encoder on the concept, set it to 0 before resuming training if it is already trained.\n",
+    "\n",
+    "\n",
+    "External_Captions= False\n",
+    "\n",
+    "# Get the captions from a text file for each instance image.\n",
+    "\n",
+    "\n",
+    "Style_Training=False\n",
+    "\n",
+    "# Further reduce overfitting, suitable when training a style or a general theme, don't check the box at the beginning, check it after training for at least 800 steps. (Has no effect when using External Captions)\n",
+    "\n",
+    "\n",
+    "Resolution = 512\n",
+    "\n",
+    "# Choices : \"512\", \"576\", \"640\", \"704\", \"768\", \"832\", \"896\", \"960\", \"1024\"\n",
+    "# Higher resolution = Higher quality, make sure the instance images are cropped to this selected size (or larger).\n",
+    "\n",
+    "#---------------------------------------------------------------\n",
+    "\n",
+    "Save_Checkpoint_Every_n_Steps = False\n",
+    "\n",
+    "Save_Checkpoint_Every=500\n",
+    "\n",
+    "# Minimum 200 steps between each save.\n",
+    "\n",
+    "\n",
+    "Start_saving_from_the_step=500\n",
+    "\n",
+    "# Start saving intermediary checkpoints from this step.\n",
+    "\n",
+    "\n",
+    "#-----------------\n",
+    "resume=dbtrain(Resume_Training, UNet_Training_Steps, UNet_Learning_Rate, Text_Encoder_Training_Steps, Text_Encoder_Concept_Training_Steps, Text_Encoder_Learning_Rate, Style_Training, Resolution, MODEL_NAME, SESSION_DIR, INSTANCE_DIR, CONCEPT_DIR, CAPTIONS_DIR, External_Captions,  INSTANCE_NAME, Session_Name, OUTPUT_DIR, PT, resume, Save_Checkpoint_Every_n_Steps, Start_saving_from_the_step, Save_Checkpoint_Every)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bf6f2232-60b3-41c5-bea6-b0dcc4aef937",
+   "metadata": {},
+   "source": [
+    "# Test the Trained Model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1263a084-b142-4e63-a0aa-2706673a4355",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "Previous_Session_Name=\"\"\n",
+    "\n",
+    "# Leave empty if you want to use the current trained model.\n",
+    "\n",
+    "\n",
+    "Custom_Path = \"\"\n",
+    "\n",
+    "# Input the full path to a desired model.\n",
+    "\n",
+    "\n",
+    "User = \"\"\n",
+    "\n",
+    "Password= \"\"\n",
+    "\n",
+    "# Add credentials to your Gradio interface (optional).\n",
+    "\n",
+    "\n",
+    "Use_localtunnel = False\n",
+    "\n",
+    "# If you have trouble using Gradio server, use this one.\n",
+    "\n",
+    "\n",
+    "#-----------------\n",
+    "configf=test(Custom_Path, Previous_Session_Name, Session_Name, User, Password, Use_localtunnel) if 'Session_Name' in locals() else test(Custom_Path, Previous_Session_Name, \"\", User, Password, Use_localtunnel)\n",
+    "!python /notebooks/sd/stable-diffusion-webui/webui.py $configf"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53ccbcaf-3319-44f5-967b-ecbdfa9d0e78",
+   "metadata": {},
+   "source": [
+    "# Upload The Trained Model to Hugging Face"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2c9cb205-d828-4e51-9943-f337bd410ea8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Save it to your personal profile or collaborate to the public [library of concepts](https://huggingface.co/sd-dreambooth-library)\n",
+    "\n",
+    "Name_of_your_concept = \"\"\n",
+    "\n",
+    "# Leave empty if you want to name your concept the same as the current session.\n",
+    "\n",
+    "\n",
+    "Save_concept_to = \"My_Profile\"\n",
+    "\n",
+    "# Choices : \"Public_Library\", \"My_Profile\".\n",
+    "\n",
+    "\n",
+    "hf_token_write = \"\"\n",
+    "\n",
+    "# Create a write access token here : https://huggingface.co/settings/tokens, go to \"New token\" -> Role : Write, a regular read token won't work here.\n",
+    "\n",
+    "\n",
+    "#---------------------------------\n",
+    "hf(Name_of_your_concept, Save_concept_to, hf_token_write, INSTANCE_NAME, OUTPUT_DIR, Session_Name, MDLPTH)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "881d80a3-4ebf-41bc-b68f-ac1cacb080f3",
+   "metadata": {},
+   "source": [
+    "# Free up space"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7403744d-cc45-419f-88ac-5475fa0f7f45",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Display a list of sessions from which you can remove any session you don't need anymore\n",
+    "\n",
+    "#-------------------------\n",
+    "clean()"
+   ]
+  }
+ ],
+ "metadata": {
+  "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": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}