diff --git a/image_metadata_extraction(2).ipynb b/image_metadata_extraction(2).ipynb new file mode 100644 index 0000000000000000000000000000000000000000..cb020ac763bf67e8687ea9834de3ea82bfeda112 --- /dev/null +++ b/image_metadata_extraction(2).ipynb @@ -0,0 +1,269 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Dependencies" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "pip install pillow datasets pandas pypng uuid\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Preproccessing" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import uuid\n", + "import shutil\n", + "\n", + "def rename_and_move_images(source_dir, target_dir):\n", + " # Create the target directory if it doesn't exist\n", + " os.makedirs(target_dir, exist_ok=True)\n", + "\n", + " # List of common image file extensions\n", + " image_extensions = ('.jpg', '.jpeg', '.png', '.gif', '.bmp', '.tiff')\n", + "\n", + " # Walk through the source directory and its subdirectories\n", + " for root, dirs, files in os.walk(source_dir):\n", + " for file in files:\n", + " # Check if the file has an image extension\n", + " if file.lower().endswith(image_extensions):\n", + " # Generate a new filename with UUID\n", + " new_filename = str(uuid.uuid4()) + os.path.splitext(file)[1]\n", + " \n", + " # Construct full file paths\n", + " old_path = os.path.join(root, file)\n", + " new_path = os.path.join(target_dir, new_filename)\n", + " \n", + " # Move and rename the file\n", + " shutil.move(old_path, new_path)\n", + " print(f\"Moved and renamed: {old_path} -> {new_path}\")\n", + "\n", + "# Usage\n", + "source_directory = \"images\"\n", + "target_directory = \"train\"\n", + "\n", + "rename_and_move_images(source_directory, target_directory)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Examine Metadata For Stable Diffusion PNGs\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from PIL import Image\n", + "import os\n", + "\n", + "# Set the path to the train directory\n", + "train_directory = \"train\"\n", + "\n", + "# Get any PNG image file from the train directory\n", + "image_file = None\n", + "for file_name in os.listdir(train_directory):\n", + " if file_name.endswith('.png'):\n", + " image_file = os.path.join(train_directory, file_name)\n", + " break\n", + "\n", + "# Check if an image was found\n", + "if image_file:\n", + " # Open the image\n", + " with Image.open(image_file) as img:\n", + " print(f\"Filename: {image_file}\")\n", + " \n", + " # Extract and display image size (width, height)\n", + " print(f\"Size: {img.size}\")\n", + " \n", + " # Extract and display image mode (RGB, RGBA, etc.)\n", + " print(f\"Mode: {img.mode}\")\n", + " \n", + " # Extract and display image format\n", + " print(f\"Format: {img.format}\")\n", + " \n", + " # Extract and display image info (metadata)\n", + " print(\"Metadata:\")\n", + " for key, value in img.info.items():\n", + " print(f\" {key}: {value}\")\n", + "else:\n", + " print(\"No PNG image found in the train directory.\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Extract the Metadata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import png\n", + "import pandas as pd\n", + "import re\n", + "\n", + "# Directory containing images\n", + "image_dir = 'train'\n", + "metadata_list = []\n", + "\n", + "# Mapping of possible keys to standardized field names\n", + "field_mapping = {\n", + " 'parameters': 'prompt',\n", + " 'seed': 'seed',\n", + " 'steps': 'steps',\n", + " 'cfg scale': 'cfg',\n", + " 'cfg_scale': 'cfg',\n", + " 'cfg-scale': 'cfg',\n", + " 'guidance': 'guidance',\n", + " 'sampler': 'sampler_name',\n", + " 'sampler_name': 'sampler_name',\n", + " 'version': 'version',\n", + " 'rng': 'rng',\n", + " 'size': 'size'\n", + "}\n", + "\n", + "def extract_metadata_from_png(image_path):\n", + " \"\"\"\n", + " Extracts metadata from all tEXt chunks in a PNG image.\n", + " Args:\n", + " image_path (str): Path to the PNG image.\n", + " Returns:\n", + " dict: A dictionary containing extracted metadata.\n", + " \"\"\"\n", + " metadata = {}\n", + " try:\n", + " with open(image_path, 'rb') as f:\n", + " reader = png.Reader(file=f)\n", + " for chunk_type, chunk_data in reader.chunks():\n", + " if chunk_type == b'tEXt':\n", + " # Decode the tEXt chunk\n", + " chunk_text = chunk_data.decode('latin1')\n", + " # Split into key and value using null byte as separator\n", + " if '\\x00' in chunk_text:\n", + " key, value = chunk_text.split('\\x00', 1)\n", + " key = key.lower().strip()\n", + " value = value.strip()\n", + " # Map the key to standardized field name if it exists\n", + " if key in field_mapping:\n", + " standardized_key = field_mapping[key]\n", + " metadata[standardized_key] = value\n", + " except Exception as e:\n", + " print(f\"Error reading PNG file {image_path}: {e}\")\n", + " return metadata\n", + "\n", + "def parse_parameters(parameters):\n", + " \"\"\"\n", + " Parses the 'parameters' string to extract individual fields.\n", + " \"\"\"\n", + " # Extract prompt (everything before the first recognized field)\n", + " prompt_end = min((parameters.find(field) for field in ['Steps:', 'CFG scale:', 'Guidance:', 'Seed:'] if field in parameters), default=-1)\n", + " prompt = parameters[:prompt_end].strip() if prompt_end != -1 else parameters\n", + "\n", + " # Extract other fields\n", + " fields = {\n", + " 'steps': r'Steps: (\\d+)',\n", + " 'cfg': r'CFG scale: ([\\d.]+)',\n", + " 'guidance': r'Guidance: ([\\d.]+)',\n", + " 'seed': r'Seed: (\\d+)',\n", + " 'width': r'Size: (\\d+)x\\d+',\n", + " 'height': r'Size: \\d+x(\\d+)',\n", + " 'rng': r'RNG: (\\w+)',\n", + " 'sampler_name': r'Sampler: (\\w+)',\n", + " 'version': r'Version: (.+)$'\n", + " }\n", + "\n", + " parsed = {'prompt': prompt}\n", + " for key, pattern in fields.items():\n", + " match = re.search(pattern, parameters)\n", + " parsed[key] = match.group(1).strip() if match else 'N/A'\n", + "\n", + " return parsed\n", + "\n", + "# Loop through all PNG images in the directory\n", + "for file_name in os.listdir(image_dir):\n", + " if file_name.lower().endswith('.png'):\n", + " image_path = os.path.join(image_dir, file_name)\n", + " metadata = extract_metadata_from_png(image_path)\n", + " \n", + " # Parse the 'parameters' field\n", + " if 'prompt' in metadata:\n", + " parsed_metadata = parse_parameters(metadata['prompt'])\n", + " else:\n", + " parsed_metadata = {field: 'N/A' for field in field_mapping.values()}\n", + " \n", + " # Add file name to metadata\n", + " parsed_metadata['file_name'] = file_name\n", + " \n", + " metadata_list.append(parsed_metadata)\n", + "\n", + "# Convert the metadata list to a DataFrame\n", + "metadata_df = pd.DataFrame(metadata_list)\n", + "\n", + "# Define the desired column order\n", + "desired_columns = ['file_name', 'seed', 'prompt', 'steps', 'cfg', 'sampler_name', 'guidance', 'version', 'width', 'height', 'rng']\n", + "\n", + "# Ensure all desired columns are present\n", + "for col in desired_columns:\n", + " if col not in metadata_df.columns:\n", + " metadata_df[col] = 'N/A'\n", + "\n", + "# Reorder the DataFrame columns\n", + "metadata_df = metadata_df[desired_columns]\n", + "\n", + "# Save the metadata to a CSV file\n", + "metadata_csv_path = os.path.join(image_dir, 'metadata.csv')\n", + "metadata_df.to_csv(metadata_csv_path, index=False)\n", + "print(\"Metadata extraction complete. Metadata saved to:\", metadata_csv_path)\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.11.10" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/train/011372d4-6655-415b-ba06-ac6a6ecf5d43.png b/train/011372d4-6655-415b-ba06-ac6a6ecf5d43.png new file mode 100644 index 0000000000000000000000000000000000000000..d7cc30021481f7e20b86e0ae13f0d799488a9e64 --- /dev/null +++ b/train/011372d4-6655-415b-ba06-ac6a6ecf5d43.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4e694647a69cf4f6c01fc0d03829e7711f269e85707caba96dfa0f0234638a56 +size 1120773 diff --git a/train/01d5eb73-c5bc-4fe0-8ae8-2ce17c34e9b1.png 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