Other Scripts added to cells
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nawnie
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/nawnie/EveryDream/blob/main/EveryDream_Tools.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "uJfwih4wAVgw"
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},
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"source": [
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"# Please read the documentation here before you start.\n",
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"\n",
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"I suggest reading this doc before you connect to your runtime to avoid using credits or being charged while you figure it out.\n",
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"\n",
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"[Auto Captioning Readme](doc/AUTO_CAPTION.md)\n",
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"\n",
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"This notebook requires an Nvidia GPU instance. Any will do, you don't need anything power. As low as 4GB should be fine.\n",
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"\n",
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"Only colab has automatic file transfers at this time. If you are using another platform, you will need to manually download your output files."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "lWGx2LuU8Q_I"
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},
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"outputs": [],
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"source": [
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"#download repo\n",
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"!git clone https://github.com/victorchall/EveryDream.git\n",
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"# Set working directory\n",
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"%cd EveryDream"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "RJxfSai-8pkD"
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},
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"outputs": [],
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"source": [
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"# install requirements\n",
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"!pip install torch=='1.12.1+cu113' 'torchvision==0.13.1+cu113' --extra-index-url https://download.pytorch.org/whl/cu113\n",
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"!pip install pandas>='1.3.5'\n",
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"!git clone https://github.com/salesforce/BLIP scripts/BLIP\n",
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"!pip install timm\n",
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"!pip install fairscale=='0.4.4'\n",
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"!pip install transformers=='4.19.2'\n",
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"!pip install timm\n",
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"!pip install aiofiles"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"#Extract Frames from video\n",
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"\n",
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"Here we will use the folder input_vid and upload in the same way we did our images"
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],
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"metadata": {
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"id": "huQSI8Y-Bboz"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"!python /scripts/extract_video_frames.py \\\n",
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"--vid_dir input_vid \\\n",
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"--out_dir output/vid \\\n",
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"--format png \\\n",
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"--interval 10 "
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],
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"metadata": {
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"id": "RDuBL4k8Avz-"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"Move the extracted frames to the input directory for captions"
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],
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"metadata": {
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"id": "iqcUzcRuCTLR"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"!cp -r output/vid input"
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],
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"metadata": {
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"id": "Uv8wAHSQAvrm"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "sbeUIVXJ-EVf"
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},
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"source": [
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"# Upload your input images into the EveryDream/input folder\n",
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"\n",
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""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "bscWH13SAVgz"
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},
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"source": [
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"## Please read the documentation for information on the parameters\n",
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"\n",
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"[Auto Captioning](doc/AUTO_CAPTION.md)\n",
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"\n",
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"*You cannot have commented lines between uncommented lines. If you uncomment a line below, move it above any other commented lines.*\n",
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"\n",
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"*!python must remain the first line.*\n",
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"\n",
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"Default params should work fairly well."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "4TAICahl-RPn"
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},
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"outputs": [],
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"source": [
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"!python scripts/auto_caption.py \\\n",
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"--img_dir input \\\n",
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"--out_dir output \\\n",
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"#--format mrwho \\\n",
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"#--min_length 34 \\\n",
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"#--q_factor 1.3 \\\n",
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"#--nucleus \\\n",
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"\n",
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"## mutiple files can be targeted in succession\n",
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"\n",
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"#!python scripts/auto_caption.py \\\n",
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"#--img_dir input/subfolder \\\n",
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"#--out_dir output/subfolder \\\n",
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"#--format mrwho \\\n",
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"#--min_length 34 \\\n",
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"#--q_factor 1.3 \\\n",
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"#--nucleus \\"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Laion Downloader\n",
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"\n",
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"* --laion_dir: directory with laion parquet files, default is ./laion\n",
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"\n",
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"* --search_text: csv of words with AND logic, ex \\\"photo,man,dog\\\"\n",
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"\n",
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"* --out_dir: directory to download files to, ive defaulted this to inputs so they can be captioned \n",
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"\n",
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"* --log_dir: directory for logs, if ommitted will not log, logs may be large!\n",
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"\n",
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"* --column:column to search for matches, defaults is 'TEXT', but you could use 'URL' if you wanted\",\n",
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"\n",
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"* --limit: max number of matching images to download, warning: may be slightly imprecise due to concurrency and http errors, defaults is 100\n",
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"\n",
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"* --min_hw: min height AND width of image to download, default is 512\n",
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" \n",
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"* --force: forces a full download of all images, even if no search is provided, USE CAUTION!\n",
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"\n",
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"* --parquet_skip: skips the first n parquet files on disk, useful to resume\n",
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" \n",
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"* --verbose: additional logging of URL and TEXT \n",
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" \n",
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"* --test: skips downloading, for checking filters, use with \"--verbose\"\n"
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],
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"metadata": {
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"id": "wY2f2LkPGSVa"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"!python scripts/download_laion.py \\\n",
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"--laion_dir ./laion \\\n",
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"--search_text \"photo,man,dog\" \\\n",
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"#--out_dir input \\\n",
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"#--log_dir logs \\\n",
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"#--column TEXT \\\n",
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"#--limit 100 \\\n",
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"#--min_hw 512 \\\n",
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"#--force False \\\n",
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"#--parquet_skip 0 \\\n",
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"#--Verbose False \\\n",
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"#--test not \\\n"
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],
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"metadata": {
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"id": "cxw60TTmEy2C"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"Here we can take our now captioned images and replace generic terms with our subjects\n",
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"\n",
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"* --find: will search for a word in this case man\n",
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"\n",
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"* --replace: will replace our found word with in this case VictorChall\n",
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"\n",
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"* --append_only: this will allow us to add a tag at he end "
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],
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"metadata": {
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"id": "EBdLelNpDjYc"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"!python scripts/filename_replace.py \\\n",
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"--img_dir output \\\n",
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"--find \"man\" \\\n",
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"--replace \"VictorChall\""
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],
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"metadata": {
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"id": "6Y1md3OHAvhw"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"Now we can chose to create text files based on our file names, this is usefull for images with very long discriptions or tag list, windows has a limit of 256 characters, and files will not transfer correctly to a windows program if they are longer, moving these files in a zip is fine however and causes no issues\n"
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],
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"metadata": {
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"id": "W0MspWmXJQuc"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"!python scripts/createtxtfromfilename.py"
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],
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"metadata": {
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"id": "BpvenvyQJr9b"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"Compress our images "
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],
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"metadata": {
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"id": "boVkDsiWJ_-P"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"/content/EveryDream/scripts/compress_img.py \\\n",
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"--img_dir output \\\n",
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"--out_dir output/compressed_images \\\n",
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"--max_mp 1.5 \n",
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"#--overwrite False \\\n",
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"#--Quality 95 \\\n",
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"#--noresize False \\\n",
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"#--delete \\"
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],
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"metadata": {
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"id": "F6QYfylhKAII"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "HBrWnu1C_lN9"
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},
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"source": [
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"## Download your DataSet from EveryDream/output\n",
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"\n",
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"If you're on a colab you can use the cell below to push your output to your Gdrive."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "ldW2sDLcAVgz"
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},
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"outputs": [],
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"source": [
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"from google.colab import drive\n",
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"drive.mount('/content/drive')\n",
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"\n",
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"!mkdir /content/drive/MyDrive/Auto_Data_sets\n",
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"!cp -r output/ /content/drive/MyDrive/Auto_Data_sets"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "B-HFqbP4AVgz"
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},
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"source": [
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"## If not on colab/gdrive, the following will zip up your files for extraction\n",
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"\n",
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"You'll still need to use your runtime's own download feature to download the zip.\n",
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"\n",
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""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "SVa80mrKAVg0"
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},
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"outputs": [],
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"source": [
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"!pip install patool\n",
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"\n",
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"import patoolib\n",
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"\n",
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"!mkdir output/zip\n",
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"\n",
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"!zip -r output/zip/output.zip output"
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]
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}
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],
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"metadata": {
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"colab": {
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"provenance": [],
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"include_colab_link": true
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},
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"kernelspec": {
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"display_name": "Python 3.10.5 ('.venv': venv)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python",
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"version": "3.10.5"
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},
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"vscode": {
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"interpreter": {
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"hash": "faf4a6abb601e3a9195ce3e9620411ceec233a951446de834cdf28542d2d93b4"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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