Resize a folder of images with Pillow while keeping the originals

01Define the resizing rule first

The goal is to fit every image inside a 300 by 300 pixel box while preserving its aspect ratio. Images that are already smaller than that box are not enlarged. The source images remain unchanged, and every resized copy is written to a separate output folder.

For an image with width W and height H, calculate scale as the smaller of 300/W, 300/H, and 1. Then calculate the new width and height from that single scale factor. Using one factor for both dimensions prevents stretching.

scale = min(300 / width, 300 / height, 1)
new_width = int(width * scale)
new_height = int(height * scale)

02Create a synthetic image folder

The following files are synthetic and were created specifically for this article. The setup script makes four simple PNG images with known dimensions. Their visual content is unimportant; the dimensions are chosen so that every expected resize result can be checked by hand.

from pathlib import Path
from PIL import Image

SOURCE = Path("outputs") / "image_resize_demo"
IMAGES = {
    "landscape.png": ((800, 600), (220, 80, 80)),
    "portrait.png": ((600, 800), (80, 120, 220)),
    "small.png": ((200, 100), (80, 180, 100)),
    "wide.png": ((1200, 300), (180, 120, 60)),
}

SOURCE.parent.mkdir(parents=True, exist_ok=True)
SOURCE.mkdir()  # Stop if this synthetic source already exists.

for filename, (size, color) in IMAGES.items():
    image = Image.new("RGB", size, color)
    target = SOURCE / filename
    image.save(target, format="PNG")

python create_resize_demo.py

The four originals contain 1,340,000 pixels in total: 480,000 + 480,000 + 20,000 + 360,000. Pixel count is useful for understanding the example, but it is not the same as file size in bytes because PNG compression depends on image content.

03Calculate the four expected dimensions by hand

For landscape.png, the limiting dimension is width: 300/800 = 0.375. Multiplying both dimensions by 0.375 gives 300 by 225. For portrait.png, height is limiting: 300/800 = 0.375, producing 225 by 300.

small.png already fits because both dimensions are at or below 300. The scale is capped at 1, so it remains 200 by 100. For wide.png, width limits the result: 300/1200 = 0.25, giving 300 by 75.

The resized copies therefore contain 177,500 pixels in total. The originals are still present separately, so this number is not a statement about disk-space savings.

04Resize the folder into a new destination

Save the following script as batch_image_resize.py. It processes PNG, JPEG, and WebP files directly inside SOURCE. It does not recursively search subfolders. The destination is created with mkdir without exist_ok, so an existing output directory causes the script to stop instead of mixing new results with an earlier run.

from pathlib import Path
from PIL import Image, ImageOps

SOURCE = Path("outputs") / "image_resize_demo"
OUTPUT_DIR = Path("outputs") / "image_resize_result"
MAX_WIDTH = 300
MAX_HEIGHT = 300
SUPPORTED = {".png", ".jpg", ".jpeg", ".webp"}


def target_size(width: int, height: int) -> tuple[int, int]:
    scale = min(MAX_WIDTH / width, MAX_HEIGHT / height, 1)
    new_width = max(1, int(width * scale))
    new_height = max(1, int(height * scale))
    return new_width, new_height


def main() -> None:
    if not SOURCE.is_dir():
        raise FileNotFoundError(f"Source folder not found: {SOURCE}")
    if MAX_WIDTH < 1 or MAX_HEIGHT < 1:
        raise ValueError("Maximum dimensions must be positive integers.")

    source_resolved = SOURCE.resolve()
    output_resolved = OUTPUT_DIR.resolve()
    if source_resolved == output_resolved:
        raise ValueError("SOURCE and OUTPUT_DIR must be different.")

    OUTPUT_DIR.parent.mkdir(parents=True, exist_ok=True)
    OUTPUT_DIR.mkdir()  # Refuse to reuse an existing destination.

    candidates = sorted(
        path for path in SOURCE.iterdir()
        if path.is_file() and path.suffix.lower() in SUPPORTED
    )

    resized_count = 0
    unchanged_size_count = 0

    for source_path in candidates:
        output_path = OUTPUT_DIR / source_path.name
        if output_path.exists():
            raise FileExistsError(f"Output already exists: {output_path}")

        with Image.open(source_path) as opened:
            image = ImageOps.exif_transpose(opened)
            image.load()
            old_size = image.size
            new_size = target_size(*old_size)

            if new_size == old_size:
                result = image.copy()
                unchanged_size_count += 1
            else:
                result = image.resize(new_size, Image.Resampling.LANCZOS)
                resized_count += 1

            save_options = {}
            if source_path.suffix.lower() in {".jpg", ".jpeg"}:
                save_options["quality"] = 90
            result.save(output_path, **save_options)
            result.close()

        print(f"{source_path.name}: {old_size[0]}x{old_size[1]} -> {new_size[0]}x{new_size[1]}")

    print(f"Processed {len(candidates)} images.")
    print(f"Resized: {resized_count}; already within limit: {unchanged_size_count}.")
    print(f"Output folder: {OUTPUT_DIR.as_posix()}")


if __name__ == "__main__":
    main()

ImageOps.exif_transpose applies an image's EXIF orientation before the resize calculation when such orientation data exists. The synthetic PNG files have no such orientation requirement, so their displayed dimensions remain the dimensions listed above.

05Compare the expected output

Because filenames are processed in sorted order, the expected console lines are landscape.png, portrait.png, small.png, and wide.png. Three images become smaller and one remains at its original dimensions.

landscape.png: 800x600 -> 300x225
portrait.png: 600x800 -> 225x300
small.png: 200x100 -> 200x100
wide.png: 1200x300 -> 300x75
Processed 4 images.
Resized: 3; already within limit: 1.
Output folder: outputs/image_resize_result

The execution matched the expected output. Check the dimensions, the file count, and preservation of the original images in outputs/image_resize_demo.

06Verify the generated images yourself

Do not rely only on filenames or console text. Open the resulting files and inspect their dimensions. The following optional checker reads both folders and reports dimensions. It performs no writes.

from pathlib import Path
from PIL import Image

SOURCE = Path("outputs") / "image_resize_demo"
OUTPUT_DIR = Path("outputs") / "image_resize_result"

for source_path in sorted(SOURCE.glob("*.png")):
    output_path = OUTPUT_DIR / source_path.name
    with Image.open(source_path) as original, Image.open(output_path) as resized:
        print(
            f"{source_path.name}: "
            f"original={original.size}, output={resized.size}"
        )

• Confirm that every output width is at most 300 and every output height is at most 300.
• Confirm that landscape.png remains 4:3, portrait.png remains 3:4, and wide.png remains 4:1.
• Confirm that small.png remains 200 by 100 instead of being enlarged to 300 by 150.
• Compare modification times or hashes if you need additional evidence that the source files themselves were not rewritten.
• Run the resize script a second time without changing OUTPUT_DIR. It should stop with FileExistsError before processing another batch.

07Recognize common errors

If processing fails after some files have been written, the script does not delete those partial results. Keep the destination for investigation or use a new output directory after correcting the problem.

08Understand the limits before using real images

This example handles only files directly inside one folder and supports PNG, JPEG, and WebP extensions. It does not reproduce a nested directory tree, resize animated frames individually, preserve every form of metadata, or guarantee that color-management information survives unchanged.

Resampling changes pixel data. Even when an image keeps the same dimensions, opening and saving it can change its encoded bytes or metadata. JPEG output is lossy and this script saves JPEG copies with quality 90; that does not preserve the original JPEG bitstream or original compression settings.

The int calculation rounds fractional dimensions downward. For arbitrary source sizes, the resulting pixel ratio can therefore differ slightly from the mathematical ratio because image dimensions must be whole numbers. The synthetic dimensions in this guide divide exactly, so the four expected results require no ambiguous rounding.

Execution and verification record

ChatGPT Python tool · Python 3.13.5 · Pillow 12.3.0

• Created landscape.png 800×600, portrait.png 600×800, small.png 200×100, and wide.png 1200×300.
• The actual source pixel total is 1,340,000, not 1,240,000.
• The resize run produced exactly 300×225, 225×300, 200×100, and 300×75.
• The output pixel total is 177,500, matching the article.
• Console output exactly matched the expected seven lines, including 'Processed 4 images.' and 'Resized: 3; already within limit: 1.'.
• The optional checker printed the expected original and output dimensions for all four files.
• There were 4 files in the source folder and 4 files in the output folder.
• SHA-256 hashes of all four source files were unchanged after resizing, confirming the originals were not rewritten.
• Running the resize script again with the same OUTPUT_DIR raised FileExistsError before processing another batch.
• Local recheck on 2026-09-21 with Python 3.12.14: the corrected example passed; source preservation and overwrite protection also passed.

References

The explanations and examples were written for this site. See the official sources below for the related behavior and concepts.

• Official Pillow documentation · Image module ↗ (New tab)
• Official Pillow documentation · ImageOps module ↗ (New tab)
• Official Pillow documentation · Image file formats ↗ (New tab)
• Official Python 3.12 documentation · pathlib ↗ (New tab)