Process multiple images at once with consistent settings. Apply resize, format conversion, compression, and filters to bulk images efficiently.
You have 200 product photos that all need resizing, format conversion, and watermarking. Doing them one by one would take hours. The batch processor lets you apply the same set of operations, resize, convert, compress, rename, to dozens or hundreds of images at once. Upload the batch, configure your settings, and let it run.
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Convert images to Base64 encoded strings for embedding in CSS, HTML, or JavaScript. Multiple output formats available.
Resize and scale images with smart aspect ratio control. Supports custom dimensions, percentage scaling, social media presets, and batch resizing while maintaining image quality.
Convert images between PNG, JPG, WebP, AVIF, BMP formats. Features quality control, transparency support, and batch conversion for efficient workflow.
You have 120 raw photos that all need the same resize, format change, and compression for a gallery.
Input
120 JPGs · resize w1600 · → WebP q80 · strip metadata
Output
A ZIP of 120 optimised WebP files, pipeline applied identically
Defining the steps once and running them across the whole set guarantees consistency and saves an hour of repetitive editing. All processing is local, so a client’s full shoot never leaves the machine.
You have 200 product photos that all need resizing, format conversion, and watermarking. Doing them one by one would take hours. The batch processor lets you apply the same set of operations, resize, convert, compress, rename, to dozens or hundreds of images at once. Upload the batch, configure your settings, and let it run.
Resize, compress, and rename hundreds of product photos to consistent specifications.
Process entire photoshoots, resize for web, compress for email, and rename by sequence.
Convert and resize images in bulk when moving content between platforms with different requirements.
The Image Batch Processor queues any number of files chosen through a single `image/*` multi-select input and runs one operation across the whole queue. Pick a mode in the Custom Settings tab (Resize, Convert, or Filter) or tap a Quick Preset: Instagram Square (1080x1080), Instagram Story (1080x1920), Thumbnail (150x150 PNG), Web Optimized (1200px WebP 80%), HD Wallpaper (1920x1080), Convert to WebP, Convert to PNG, Black & White (grayscale), or Vintage Sepia. Every image is decoded onto an HTML canvas and emitted with `canvas.toBlob`, so all work happens locally in the browser tab and no upload ever occurs. Images process sequentially, one at a time, with a 50ms `setTimeout` gap between them to keep the UI responsive; a progress bar tracks completed/total, and a live Size Comparison panel sums original versus processed bytes and shows the percentage saved.
The three modes behave differently and it is worth knowing how. Convert (`convertImageFormat`) honors the chosen output format (PNG, JPEG, or WebP) and the 10-100% quality slider, and when targeting JPEG it first paints a solid white background before drawing, so any transparency is flattened to white rather than kept. Filter (`applyFilter`) operates per-pixel: grayscale uses the luma weights 0.299R + 0.587G + 0.114B, and sepia applies the classic sepia matrix (0.393/0.769/0.189 for red, etc.); the filter list also exposes Invert, Brighten, High Contrast and Saturate. Filter output is always written as PNG at full quality, so the quality slider is hidden for filters and for any conversion already set to PNG (it only appears for resize/convert with a lossy format).
Resize (`resizeImage`) uses high-quality canvas smoothing (`imageSmoothingQuality = 'high'`), but two batch-path quirks are worth knowing. First, the component never passes an output format to the resizer, so resized files are emitted as PNG regardless of the format buttons or quality slider, which is why a preset like Web Optimized (nominally WebP 80%) effectively writes PNG when run as a resize. Second, although a 'maintain aspect ratio' toggle and an on-screen tip ('set width or height to 0 for auto calculation') suggest you can leave one dimension at 0 to auto-fit, the batch code substitutes `resizeWidth || 800` and `resizeHeight || 600` before calling `resizeImage`, so a 0 becomes 800 or 600 and the auto-aspect branch never fires; the default 1200x0 setting therefore produces a fixed 1200x600 rather than an aspect-preserved 1200px-wide image. Processing can be paused and resumed at any point (it skips already-completed items on resume) and Reset All re-queues every image as pending to re-run with new settings. Download All does not bundle a ZIP archive; instead it iterates the completed blobs and triggers a separate `downloadBlob` save for each file, naming them processed-N-originalname.ext, and individual images can also be downloaded one at a time from the queue grid.
There is no hard limit, but performance depends on your browser and device. Batches of 50-100 images typically process smoothly.
Yes. Stack resize, convert, and compress operations. They are applied in sequence to each image.
The processor continues with the remaining images. Failed files are reported at the end so you can retry them.
Images are decoded, edited, and exported entirely inside this browser tab. No originals, exports, or metadata are uploaded.