Bulk Image Resizer
Resize multiple images at once.
Drag & drop images here, or browse files
Resize multiple JPG, PNG, and WebP photos at once in your browser.
Browser-local processing
Selected image data is processed in your browser and is not uploaded for conversion.
Bounded batch queue
Process up to 30 images with two workers. Actual memory use depends on device and image dimensions.
Flexible resize controls
Aspect ratio lock, contain, center crop, percentage scale, or custom dimensions.
How to Batch Resize Images in Your Browser
Resize a batch to consistent pixel dimensions for a product listing, social post, or email attachment. Choose whether each result should fit inside a box, crop to fill it, or stretch to exact dimensions.
Selected images are resized in your browser and are not uploaded to a conversion server. To restore work after a refresh, this tool saves the selected files and resized outputs in this browser for up to 7 days; Reset clears the saved batch. Normal page and asset requests reach our host. If you allow analytics, FivoTools records limited tool-usage events, not image content or filenames. Download each resized image separately; the output filename includes its dimensions.
For an in-depth comparison of when to scale pixel dimensions versus when to compress file bytes, read the Image Resizing vs. Image Compression guide.
Aspect Ratios and Example Digital Dimensions
An aspect ratio represents the proportional relationship between an image's width and its height. Maintaining proportions prevents distortion and unnatural skewing. The following are example pixel sizes and aspect ratios, not guaranteed current requirements for a social platform or upload service:
| Aspect Ratio | Example Resolutions | Common Applications |
|---|---|---|
| 16:9 Widescreen | 1920 × 1080 (Full HD), 1280 × 720 (HD) | Desktop displays, video thumbnails, website hero banners |
| 1:1 Square | 1080 × 1080, 512 × 512, 256 × 256 | Social feed posts, eCommerce catalog thumbnails, profile avatars |
| 9:16 Vertical | 1080 × 1920 (Full HD Vertical) | Mobile stories, vertical video feeds, smartphone lockscreens |
| 4:3 Standard Photo | 1600 × 1200, 1024 × 768 | Digital camera captures, tablet displays, presentation slides |
| 1.91:1 Social Card | 1200 × 630 | Open Graph (OG) social share previews for web links |
Understanding Fit Modes: Contain vs. Cover vs. Stretch
When adapting an existing image to specific target width and height boundaries, choosing the intended fit behavior ensures predictable results:
Fit Inside (Contain)
Scales the original image proportionally until it fits within the target canvas. The full image remains visible without cropping; the export keeps its proportions and may be smaller than one or both requested bounds. Resizing may change pixel detail.
Crop to Fill (Cover)
Scales the image proportionally to fill the target canvas, then crops the centered excess. Check the preview to make sure important content remains inside the crop.
Stretch (Exact Dimensions)
Maps the image to the exact target width and height without preserving the original proportions. This can visibly distort people, products, and other shapes; use it only when that change is acceptable.
Decoded Pixel RAM Limits: Why Device Memory Matters
Compressed file size is different from the memory needed for a decoded canvas. One RGBA pixel buffer uses four bytes per pixel, before additional browser, decode, preview, or intermediate-buffer memory.
For example, a single 8,000 × 6,000 RGBA pixel buffer requires:
Decoded previews, canvas buffers, other tabs, and browser overhead all use memory. The limits below bound this tool's work but cannot guarantee that every device can process every accepted image without slowing down or running out of memory.
- Batch size is capped at 30 images, with a 30 MB maximum per file.
- Source and target canvas dimensions are capped at 50 megapixels each.
- Resizing runs at most two image jobs at a time. Canvas buffers are released after each operation; preview and output URLs are revoked when files are removed, cleared, or the page is unloaded.
Choosing the Ideal Output Format
- WebP (.webp): The format supports lossy and lossless encoding and alpha transparency. This tool uses the browser's encoder; actual size and receiving-app support vary, so check the exported file.
- JPEG (.jpg): Widely supported for photographs, but it cannot retain transparency. Confirm the receiving app accepts JPEG.
- PNG (.png): Lossless for the pixels supplied to the encoder and supports transparency. It may produce a larger file than the source.
Browser-local processing
Output method and limitations
The browser decodes each accepted image, draws the chosen crop or fit to a canvas, then encodes the result. A canvas export creates a new raster image; it does not retain the original file's EXIF or GPS metadata. Browser image decoders and output encoders can vary, so inspect the saved dimensions, transparency, orientation, and file type before using it.
See the MDN canvas export reference, the PNG specification, andGoogle's WebP container documentation.
Frequently Asked Questions
How do I resize an image without losing quality or causing blurriness?
Resizing changes the sampled pixel grid and can remove detail, especially when reducing dimensions or using a low-resolution source. Upscaling cannot restore detail that was not in the original and may look soft. Start with the best available original and inspect the export at its intended display size.
What is the difference between image resizing and image compression?
Resizing changes pixel width and height. Compression changes how those pixels are encoded and can change the file size. A resize may also change file size, but neither operation guarantees a particular number of bytes. If a destination sets both pixel and byte limits, check both after export.
Which output format should I choose: WebP, JPEG, or PNG?
Choose based on the destination's supported formats and whether transparency matters. JPEG is widely supported but does not retain transparency. PNG stores the exported pixels losslessly and can retain alpha transparency. WebP supports lossy and lossless encoding and transparency, but compare the actual result and confirm that the receiving app accepts it.
Why does browser-local bulk resizing enforce batch and megapixel limits?
A single 8,000 × 6,000 RGBA canvas buffer would use about 192 MB for pixel data alone (width × height × 4 bytes). This tool limits batches to 30 files, each no larger than 30 MB, checks source and target dimensions against 50 megapixels, and runs at most two image jobs at a time. Browser and device memory use varies and can be higher because of decoding, previews, other tabs, and intermediate buffers.
What is the difference between Contain, Cover, and Stretch fit modes?
Fit Inside (Contain) scales the full image proportionally without cropping; the exported dimensions may be smaller than one or both requested bounds. Crop to Fill (Cover) scales proportionally and crops the centered excess to fill the exact target dimensions. Stretch maps the image to the exact width and height and can distort its proportions. Resampling may change detail in every mode.
Are camera EXIF and GPS metadata tags preserved?
Canvas export creates a new image from rendered pixels; original EXIF, GPS, camera model, and timestamp tags are not preserved. The browser may apply orientation while decoding, so check that the exported image is upright before using it.
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