PNG to CSV Converter
Convert PNG images to CSV format, extracting pixel data, color analysis, and image metadata.
Upload PNG Image
Drop your PNG file here or click to select
Higher values extract fewer pixels for better performance with large images.
CSV Result
CSV output will appear here
Upload a PNG image and click "Convert to CSV"
Why Convert PNG to CSV?
Converting PNG images to CSV format makes image data accessible for analysis, processing, and visualization in various applications:
- Data Analysis: Extract pixel data for numerical analysis in spreadsheets or data analysis tools.
- Machine Learning: Create datasets for training image processing and computer vision models.
- Color Analysis: Study color distribution and frequencies for design, art, or scientific research.
- Data Visualization: Use image data to create custom visualizations and charts.
- Image Processing: Convert image data for custom processing algorithms or filters.
- Education: Understand how digital images are structured at the pixel level.
Key Features
Extraction Modes
- • Pixel Data: Extract RGB/A values and positions for individual pixels.
- • Color Analysis: Generate statistics on color distribution and frequency.
- • Metadata: Extract image dimensions, average colors, luminance, and more.
Customization Options
- • Adjustable pixel sampling rate for large images
- • Filter for most frequent colors or extract all colors
- • Include/exclude transparent pixels
- • Customizable CSV columns (position, RGBA, hex codes)
- • Visual CSV preview with color swatches
How to Use
- Upload a PNG image using the file uploader.
- Select an Extraction Mode:
- Pixel Data: Extracts individual pixel information (position, color values).
- Color Analysis: Analyzes color distribution and frequency.
- Metadata: Extracts overall image information.
- Configure Options:
- For Pixel Data: Set the sampling rate to control how many pixels are extracted.
- For Color Analysis: Choose between all colors or only unique colors and set a maximum color count.
- For CSV formatting: Select which data columns to include (position, RGBA, hex).
- Click the "Convert to CSV" button.
- Preview the generated CSV data in the table view.
- Copy the CSV to your clipboard or download it as a file.
Extraction Modes Explained
Pixel Data Mode
This mode extracts information about individual pixels from the image. You can adjust the sampling rate to reduce the output size for large images. Each row in the CSV represents a single pixel, with options to include:
- X/Y coordinates of the pixel
- Red, Green, Blue, and Alpha (transparency) values
- Hexadecimal color code representation
Ideal for detailed image analysis, creating pointillist visualizations, or extracting specific pixel information.
Color Analysis Mode
This mode analyzes the color distribution in the image. It counts the occurrence of each unique color and provides frequency information. Options include:
- Extracting all unique colors or only the most frequently used colors
- Setting a maximum number of colors to include in the output
- Including or excluding fully transparent pixels
Perfect for palette extraction, color scheme analysis, or studying the color composition of images.
Metadata Mode
This mode extracts overall information about the image, including:
- Image dimensions (width, height) and aspect ratio
- Average RGB color values across the image
- Average luminance (brightness) and predominant tone
- Percentage of transparent pixels
Useful for cataloging images, creating image databases, or quick analysis of image characteristics.
Practical Applications
Data Analysis & Visualization
- • Extract image data for analysis in spreadsheets
- • Create custom data visualizations from image information
- • Generate heatmaps from image pixel intensity
- • Analyze color distributions for design research
Machine Learning & AI
- • Create training datasets for image recognition models
- • Extract features for computer vision algorithms
- • Prepare image data for clustering and classification
- • Convert image data for custom neural network inputs
Creative & Educational
- • Study color composition in art and photography
- • Create generative art from image data
- • Teach concepts of digital imaging and pixel structure
- • Convert images for alternative visualization methods
- • Extract color palettes from reference images for design projects
Frequently Asked Questions
What's the maximum image size this tool can handle?
The maximum file size for upload is 10MB. However, for large images (high resolution), we recommend using the pixel sampling option in Pixel Data mode to extract a representative subset of pixels rather than every pixel. This improves performance and produces more manageable CSV files.
Why would I use the Color Analysis mode instead of Pixel Data mode?
Color Analysis mode focuses on the distribution of colors rather than individual pixels. This is useful when you're interested in the overall color composition of an image rather than specific pixel locations. It produces a much smaller CSV file with statistics about color frequency, which is ideal for palette extraction or studying color usage in images.
Are my image files stored on your servers?
No, all processing happens directly in your browser using client-side JavaScript. Your image files are never uploaded to our servers, ensuring complete privacy and security.
Can I use this tool for images other than PNG?
This tool is specifically designed for PNG images. PNG is ideal because it supports transparency (alpha channel) and lossless compression, ensuring accurate pixel data extraction. If you need to convert other image formats to CSV, consider converting them to PNG first.
What's the format of the CSV output?
The CSV format depends on the extraction mode and options you select. By default, it includes a header row and the data columns you've enabled (position, RGBA values, hex codes). Each row represents either a pixel (in Pixel Data mode), a unique color (in Color Analysis mode), or a property-value pair (in Metadata mode). The columns are separated by commas, following standard CSV format.
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