https://damaheritage.com/Product-image workflows for online sellers, platform references and reproducible browser tests.enhttps://damaheritage.com/guides/fit-vs-fill/https://damaheritage.com/guides/fit-vs-fill/Mon, 07 Sep 2026 00:00:00 GMTCompare downloadable square exports from one portrait photo, then choose whether to preserve the source edges or fill the frame. Updated 2026-10-20. The same cup photograph fitted and cropped into square exports. Choose the detail to protect Choose Fit when the entire photograph must remain visible. The empty part of the output receives a background color. Choose Fill when covering the whole output is more important than retaining the source edges. Inspect exactly what is removed before accepting it. A photograph and the product inside it have different boundaries. Fit preserves the source rectangle, including any empty background already in that rectangle. It does not find a cup handle, remove a background or equalize the apparent sizes of different products. Read the worked example The source photograph below is portrait-shaped. Fitting it to a square preserves its top and bottom and introduces white side margins. Filling the square removes some of the background above and below the cup. In this particular composition, the cropped area is mostly background; a taller product in the same source frame could lose an important detail. The exported pixels, rather than the names of the settings, settle the comparison. Download both square results and open them at the same display size. Compare the cup rim, base, painted decoration and surrounding background. Changing the composition can change which mode is appropriate. Repeat in any image editor Use an editor with a canvas or crop control. Keep a copy of the original. A resize control alone may only change dimensions while preserving the original ratio; it may not create a square canvas at all. 1. Set the destination canvas, for example 800 × 800 pixels, and preserve the source proportions. 2. For Fit, scale until the entire source fits inside the canvas and choose the background deliberately. 3. For Fill, scale until the canvas is covered, then position the crop around the details that must survive. 4. Export each variation separately from the original. Open the saved files and compare them side by side. 5. Inspect the final marketplace draft as well, because the destination can apply another crop. When neither mode works If Fit makes the product too small, inspect the empty space in the original before increasing the output resolution. A tighter source composition can help more than a larger canvas. If Fill removes a handle, accessory or quantity-defining piece, reposition the crop or retain the complete frame. When a small source is enlarged, extra pixels do not restore a blurred label. Image Prep leaves enlargement off by default. Its margin applies to Fit, and Fill uses the chosen crop position. The reference example enables enlargement so both modes can cover the requested square; match that choice when reproducing it. This is an editorial explanation of a documented workflow, not a claim of first-hand selling experience. Examples are illustrative or reproducible; browser output and marketplace presentation can vary. Reference: MDN: drawImage scaling and source/destination rectangles — https://developer.mozilla.org/en-US/docs/Web/API/CanvasRenderingContext2D/drawImagehttps://damaheritage.com/guides/thumbnail-crop-checklist/https://damaheritage.com/guides/thumbnail-crop-checklist/Mon, 07 Sep 2026 00:00:00 GMTUse downloadable square, landscape and portrait crop examples to find edge risks, then verify the actual Etsy listing preview. Updated 2026-10-20. Three actual crops of the same cup image. Identify meaningful edges Before testing a crop, identify what tells a shopper what is included: the whole silhouette, a handle, a cable, a matching piece or packaging. A crop that removes that context can change the meaning of a listing even when the main object remains visible. The examples below start from one square export. A centered landscape frame removes image content vertically; a portrait frame removes it horizontally. This is a reproducible geometry example. Etsy's actual placement, focal position and current listing controls remain the final presentation check. Test three viewing sizes Check the full source, the crop and a small thumbnail. A label can survive the crop but become unreadable when the image is reduced. A narrow object can remain complete yet become difficult to recognize. The output needs to communicate clearly at the size at which it will be seen. Use the three downloadable examples to separate clipping from scale. The portrait crop of a padded square can remove empty side margins rather than the product. Conversely, a landscape crop may remove source content above and below the subject. A removed pixel count alone does not judge whether the crop is useful. 1. Write down the outermost meaningful detail before changing the frame. 2. View each crop at approximately its eventual thumbnail size. 3. Inspect whether the item, included quantity and key distinguishing detail are still clear. 4. Use a separate detail image when small lettering cannot be read in the main thumbnail. Verify inside Etsy Etsy's image guidance recommends leaving enough border for square, portrait and landscape thumbnail views. It also provides a thumbnail adjustment tool when creating or editing a listing. Use that tool instead of assuming a locally prepared square dictates every placement. The platform reference on this site keeps the current pixel and file-type guidance in one place. 1. Upload one representative image to a draft rather than replacing a whole image set immediately. 2. Open the thumbnail adjustment and inspect the views Etsy currently offers. 3. Check that repositioning one view has not hidden an important edge in another. 4. Reopen the saved draft at phone and desktop sizes before publishing. Repair the source composition When a crop clips the product, add space around the source or move the crop to protect it. When all views look too distant, use a tighter source image with sufficient breathing room. Repeatedly increasing pixel dimensions does not repair the relationship between the product and its background. Do not crop away pieces merely to make the main image more dramatic. A main image that stays truthful and readable is preferable to a tighter crop that suggests a different quantity or hides a distinguishing feature. This is an editorial explanation of a documented workflow, not a claim of first-hand selling experience. Examples are illustrative or reproducible; browser output and marketplace presentation can vary. Reference: Etsy: image requirements and thumbnail best practices — https://help.etsy.com/hc/en-us/articles/115015663347-Requirements-and-Best-Practices-for-Images-in-Your-Etsy-Shophttps://damaheritage.com/guides/consistent-product-grid/https://damaheritage.com/guides/consistent-product-grid/Mon, 07 Sep 2026 00:00:00 GMTSee why identical image dimensions can still produce uneven product sizes, using two downloadable exports of the same photograph. Updated 2026-10-20. The same cup at two apparent sizes on identical square canvases. Compare the subject, not just pixels If two files have the same width and height but the products look different in size, inspect the space around each subject. Equal canvases do not equalize the objects inside them. A source with more empty background produces a smaller-looking product when the whole photo is fitted into the same frame. The paired example uses one photograph at two scales on identical 800 × 800 canvases. This isolates source occupancy from product differences. It is a controlled reference example, not a screenshot of a Shopify theme. Find which layer differs Start with the downloaded images outside the storefront. If the products already look uneven there, adjust the source framing. If they look consistent outside the store but different inside it, inspect the theme's image ratio, crop, container dimensions and responsive settings. A wide or tall product can legitimately occupy a different amount of visual space. Matching every object to the same height may exaggerate a tiny accessory beside a large item. Choose a consistent presentation rule for a product family rather than forcing unlike products to look physically identical. 1. Open two representative source images at the same display size. 2. Compare the subject's top, bottom and side margins. 3. Normalize the source framing where appropriate, then export to a shared aspect ratio. 4. Inspect the resulting grid inside the actual storefront theme on a phone and desktop. Choose a useful canvas A square canvas is convenient for many product groups, while tall or wide objects may work better in another ratio. The current Shopify image requirements and square-image recommendation are linked in the separate platform reference. Choose output resolution after deciding the framing; a pixel recommendation does not select a composition for you. Image Prep can fit or crop a complete source rectangle. It cannot detect the product boundary or automatically trim empty background. To standardize subject scale, adjust the original in an editor with manual crop or positioning controls, then run a small export test. Check the finished collection Shopify documents that themes can request consistent CDN sizes and that different image sizes are created for different theme areas. A shared upload ratio therefore helps but does not control every displayed crop. Check both collection and product pages after saving a theme change. If a theme setting solves the display issue, avoid destructively recropping every original. Keep the originals, record which presentation setting changed, and test a portrait and a landscape image before processing the remaining catalog. This is an editorial explanation of a documented workflow, not a claim of first-hand selling experience. Examples are illustrative or reproducible; browser output and marketplace presentation can vary. Reference: Shopify: product images, collection ratios and theme behavior — https://help.shopify.com/en/manual/products/product-media/product-media-typeshttps://damaheritage.com/guides/file-size-and-quality/https://damaheritage.com/guides/file-size-and-quality/Mon, 07 Sep 2026 00:00:00 GMTCompare measured exports from photographs, text, patterns and noise, then select a format without assuming the smallest file always looks best. Updated 2026-10-20. Photographic and synthetic inputs used in the downloadable format comparison. Choose by content and destination Start with a format the destination supports. For an opaque photograph, JPG is a useful baseline; WebP is another option when accepted. PNG can suit sharp graphics and transparency, but photographs may become much larger. The measured files below show why the content matters: a pattern behaves differently from a photograph. Choose dimensions before comparing compression. All outputs in each table row use the same normalized pixels. The quality parameter is an encoder instruction, not a percentage of visual quality, and the same numeric setting does not make JPG and WebP perceptually identical. Handle transparent backgrounds JPG cannot carry an alpha channel. Converting a transparent graphic to JPG requires a background choice. A white label on a transparent background can appear to disappear on white, while a black composite can create an unwanted dark rectangle. Image Prep deliberately composites every export onto its selected background, including PNG and WebP outputs. It is therefore unsuitable when the task requires retaining transparent pixels. Use an editor with an explicit alpha-preserving export for that task. The separate transparent sample below lets you inspect white and black composites without guessing. Inspect the visual cost Download the files and view them at normal display size, then at 100%. Inspect fine lettering, diagonals, high-contrast edges and texture. A lower byte count is not useful if a product label becomes unreadable or a texture loses important detail. In this reference set, the woven pattern's PNG is much smaller than its JPG, while the seeded noise JPG is smaller than its WebP. Random noise is a stress case rather than a normal product photograph. These examples overturn a blanket format ranking, but do not tell you which format every future photograph needs. 1. Make each variation from the same original, with unchanged dimensions and background. 2. Record actual MIME type and bytes; a browser can fall back to another format. 3. Compare important detail at the size your customer will see. 4. Repeat with an image containing different detail before choosing a batch setting. 5. Upload a representative result to the intended destination and inspect its saved preview. Keep an editable original Repeatedly saving a lossy export can compound damage. Keep an original and start every new comparison from it. Enlarging a blurred source adds pixels without restoring the missing information. Canvas export creates a newly encoded file; it is not an archival copy of original EXIF/IPTC metadata and color-profile behavior. Compare important colors with the original and keep the source separately. PNG ignores the canvas quality parameter, which is why the tool disables that slider for PNG. This is an editorial explanation of a documented workflow, not a claim of first-hand selling experience. Examples are illustrative or reproducible; browser output and marketplace presentation can vary. Reference: MDN: toBlob formats, quality, PNG defaults and fallback — https://developer.mozilla.org/en-US/docs/Web/API/HTMLCanvasElement/toBlobhttps://damaheritage.com/guides/product-photo-workflow/https://damaheritage.com/guides/product-photo-workflow/Mon, 07 Sep 2026 00:00:00 GMTInspect a downloadable three-file ZIP, then build a repeatable product-code naming and export routine without changing your originals. Updated 2026-10-20. Three reference image exports with sequential product filenames. Choose a stable product code Use one product code per batch so an exported filename tells you which item it belongs to. For example, MUG-042-001.jpg combines a stable product code with the image sequence. Keep the originals in another folder; the export folder should contain copies that can be recreated. The downloadable archive below contains three real image files and the exact names generated by this site's filename function. Extract the ZIP and inspect it before adapting the scheme to your own catalog. A filename organizes files; it does not establish storefront image order or guarantee search rankings. Prove one export first Begin with a landscape image, a portrait image and a detail image. Keep the output settings the same. Open the saved results outside the browser to check dimensions, framing and important details. One representative test is cheaper to repair than an incorrectly cropped full batch. In any editor, set an export folder, retain the original extension only if it matches the actual encoded type, and record the resize rule. If you use Image Prep, every file receives the same prefix and settings. Prefix characters outside A–Z letters, digits, hyphens and underscores become hyphens; an empty prefix becomes product. 1. Choose the product code, destination ratio, dimensions and accepted file type. 2. Prepare a small representative set and open a saved copy. 3. Check that the number of exported files equals the expected successful inputs. 4. Inspect the names and actual file types before uploading. 5. Arrange the primary image and remaining order inside the marketplace. Understand ordering and gaps Image Prep assigns numbers in the order displayed after selection. Operating-system file pickers can return a different order from the one you expected, and this tool does not offer drag-to-reorder. Use the visible list as the export-order reference. If input 2 fails, the successful files can be numbered 001 and 003. The gap preserves the connection to the failed input. Review the errors, then remove or replace the failed file and prepare again if continuous numbering is required. Never assume that a ZIP containing some successful files means the entire batch succeeded. Close and reuse the batch ZIP collects the exports in one archive; it does not necessarily make already compressed images substantially smaller. Extract it and open representative files. A webpage can request a download but cannot prove that you saved and extracted it successfully. Saved settings belong to this device's browser profile. They include the filename prefix, so replace the previous product code before a new batch. They do not save photos in a cloud library, sync to another device or substitute for a backup. Clear the batch when finished, and use Forget saved settings to remove the optional stored recipe. This is an editorial explanation of a documented workflow, not a claim of first-hand selling experience. Examples are illustrative or reproducible; browser output and marketplace presentation can vary. Reference: MDN: localStorage persistence and browser restrictions — https://developer.mozilla.org/en-US/docs/Web/API/Window/localStoragehttps://damaheritage.com/guides/browser-image-troubleshooting/https://damaheritage.com/guides/browser-image-troubleshooting/Mon, 07 Sep 2026 00:00:00 GMTSeparate file-type errors, excessive pixel counts, memory pressure and blocked downloads using a small repeatable diagnostic sequence. Updated 2026-10-20. Two files with equal dimensions and different compressed byte counts. Identify where it failed Separate three stages: reading the source, preparing the output and saving the result. An unsupported source needs conversion or recovery. A processing failure can require fewer pixels or a smaller batch. A successful export with no saved file needs a download check. Repeating every step without identifying the stage hides the useful clue. Compressed bytes and pixel count describe different demands. The actual files below have equal dimensions but different byte sizes. Their one-buffer estimates are equal; total browser memory use has not been measured. This is why reducing dimensions can help even when the original file looks small on disk. If selection rejects the file This tool accepts JPG, PNG and static WebP and checks image headers instead of trusting the extension. Renaming HEIC to JPG does not convert it. Animated PNG/WebP, GIF and SVG are outside its supported scope. Convert a supported copy in a trusted editor, keeping the original. Image Prep limits inputs to 24 megapixels, 20 MB per file, 20 files and 100 MB total. A file can meet a marketplace's requirements and still exceed these tool limits. If the source will not open in another editor either, recover a complete original rather than repeatedly uploading a damaged copy. If preparation stalls Cancel, preserve any successful results and test one failing image by itself. Then reduce output dimensions and close other demanding tabs. Memory pressure depends on device, browser and other activity; a product limit is a safeguard rather than a capacity guarantee. 1. Note the failed filename and the exact displayed message. 2. Try that file alone using smaller dimensions. 3. Compare another supported file at the same settings. 4. If both fail, retry in a current browser after reloading and without unrelated tabs. 5. If only one source fails, convert it from a complete original and retry. If the download is missing Check the browser's downloads list and any save-location prompt. The tool says download requested because it cannot inspect your Downloads folder. If the archive fails, save individual successful images or prepare a smaller batch. Outputs are capped at 12 megapixels each and 100 MB per batch. If a saved file has the wrong extension, inspect its actual format rather than renaming it to force acceptance. Browser encoding can fall back to PNG; the tool uses the returned MIME type to choose the filename. Open the downloaded file before sending it to a marketplace. If settings disappear A private browser window, blocked storage or cleared site data can remove saved settings. You can still use the controls without storing them. Browser settings are not a cross-device account and should not contain confidential product or customer information. If the problem remains reproducible, report the page, browser, operating system, input type and dimensions, chosen settings and exact error. The linked tracker is public, so provide a non-private test file rather than a customer's photograph. This is an editorial explanation of a documented workflow, not a claim of first-hand selling experience. Examples are illustrative or reproducible; browser output and marketplace presentation can vary. Reference: MDN: canvas export behavior and failure cases — https://developer.mozilla.org/en-US/docs/Web/API/HTMLCanvasElement/toBlobhttps://damaheritage.com/marketplace/etsy/https://damaheritage.com/marketplace/etsy/Tue, 22 Sep 2026 00:00:00 GMTCheck Etsy's supported photo types, pixel recommendations, upload-size warnings and thumbnail workflow using directly linked Etsy help sources. Last checked 2026-10-21. Check the file type before exporting Etsy's current image guidance lists JPG, GIF, PNG, SVG and HEIC. It does not list WebP, even though Image Prep can export WebP and Image QA can inspect it. For an Etsy upload, choose JPG or PNG in this tool and confirm the file type in the listing draft. Renaming a WebP file does not convert it. Etsy says animated GIFs and transparent PNGs are not supported as expected; transparent areas may appear black. Image Prep composites transparent inputs onto the selected background, so choose that background deliberately. Check Etsy's linked requirements again if its supported formats change. Treat pixel dimensions as guidance, not a magic threshold Etsy recommends listing images at least 2000 pixels wide and high. Its image guidance also says the first photo should be at least 635 pixels in both dimensions to avoid reduced search appearance. The Search Visibility page likewise recommends at least 2000 pixels in both dimensions for the main photo; this does not require every source to be exactly square. These are platform recommendations; meeting a pixel count alone does not guarantee search placement, acceptance or a sharp result. The guidance allows a landscape or square first image and recommends leaving room around the subject for thumbnail treatment. Do not enlarge a small original just to hit a number: added canvas pixels cannot restore missing detail. Use Etsy's own thumbnail adjustment tool to inspect the actual crop. Upload size advice is not one universal cap Etsy's image-requirements page warns that files over 1 MB may not finish uploading, especially on a slow connection. This is troubleshooting advice, not a guaranteed upload cap. The current listing-creation page does not provide a separate universal byte limit. Connection conditions and the upload flow matter. If an upload stalls, test one image on a stable connection, then reduce dimensions or JPG quality in small steps and compare the result. Keep text, texture and product edges legible. Check the draft listing rather than treating a particular kilobyte target as a platform rule. Check composition, color and the final listing Etsy may compress images after upload, which can make them look less sharp. Etsy also converts images to sRGB; if colors shift, convert the source to sRGB before uploading and compare the listing preview with the original. The Search Visibility page checks more than image dimensions: it also calls out a clear main photo of one finished product rather than a collage, at least one listing photo, category details and shop/customer-service signals. Treat the page as a diagnostic checklist, not a ranking promise. Image optimization cannot replace accurate listing information or a useful product offer. A repeatable pre-publish check Use representative images that expose different risks: the main product view, an edge-sensitive detail and an image containing small text or transparency. A crop preview catches some framing problems, but only Etsy's own draft and thumbnail previews show how the platform currently presents the upload. 1. Confirm that the export type is supported by Etsy; use JPG or PNG from Image Prep. 2. Check the source dimensions and composition without enlarging a low-detail original to chase a number. 3. Inspect the exported file at normal size and at 100%, including edges, text and important color. 4. Upload one representative file to a draft and inspect Etsy's thumbnail adjustment and listing preview. 5. If an upload times out, test one file and adjust dimensions or compression gradually instead of assuming a universal size cap. 6. Record the official source and checked date when you reuse this workflow. Known limits Image QA can identify a file type and dimensions; Image Prep can create local exports. Neither tool checks Etsy account status, listing policy, image attractiveness, accurate product representation or the exact crop on every search and collection surface. A correct export is one technical check, not a promise of visibility or sales. Reference: Etsy: Requirements and Best Practices for Images in Your Etsy Shop — https://help.etsy.com/hc/en-us/articles/115015663347-Requirements-and-Best-Practices-for-Images-in-Your-Etsy-Shop Reference: Etsy: How to Use the Search Visibility Page — https://help.etsy.com/hc/en-gb/articles/25869947521175-How-to-Use-the-Etsy-Search-Visibility-Page Reference: Etsy: How to Create a Listing — https://help.etsy.com/hc/en-us/articles/115015628707-How-to-Create-a-Listinghttps://damaheritage.com/marketplace/shopify/https://damaheritage.com/marketplace/shopify/Tue, 22 Sep 2026 00:00:00 GMTCurrent Shopify image limits, format guidance and collection-image behavior, with a practical check that accounts for theme crops and this site's tool limits. Last checked 2026-10-20. Current image limits and accepted formats Shopify's product-media documentation, checked October 20, 2026, says product and collection images can be up to 5000 × 5000 pixels or 25 megapixels, and must be smaller than 20 MB. It lists PNG as the preferred format for most product images, followed by JPEG; it also lists TIFF, BMP, GIF, SVG, HEIC and WebP. It also supports animated GIF and WebP, unlike this site's static-image tools. Shopify's image service selects a format supported by each customer's web client. The 2048 × 2048 square recommendation applies to square product images that usually display best; it is not a universal upload requirement. Use the current linked help page if a platform rule matters to your workflow, because requirements can change. Why the collection can still look uneven Shopify says consistent aspect ratios for featured images can help collection images appear the same size side by side. It also notes that themes can request consistent sizes from Shopify's CDN and that different image sizes are created for different theme areas. A matching source ratio can improve consistency, but theme crops and responsive layouts still affect the final display. Equal output canvases do not equalize the size of the objects inside them. If one source product fills 80% of its frame and another fills 40%, fitting both into the same square preserves the apparent-size difference. Added padding surrounds the source rectangle; it does not detect or trim empty background around a product. 1. Choose the featured-image ratio used by the product family or theme, rather than assuming square is always best. 2. Use Fit to preserve all source edges. Use Fill only if the part removed by cropping is genuinely expendable. 3. Compare one portrait and one landscape product at the same output dimensions; note whether empty source margins cause unequal object scale. 4. Upload representative images and inspect both the collection grid and product page on phone and desktop. Shopify limits versus Image Prep limits Shopify allows images up to 5000 pixels per edge and 25 megapixels. Image Prep is deliberately smaller: it limits each output to 4096 pixels per edge and 12 megapixels. Shopify may accept file types this tool cannot open; Image Prep supports JPG, PNG and static WebP. A platform-valid file is not automatically within this browser tool's limits. Seller Operations Lab cannot see your store theme, its custom image settings or Shopify's final CDN response. Use the live theme preview as the presentation check; use this reference for the linked platform facts and the tool pages for local file checks. Reference: Shopify: Product media types — https://help.shopify.com/en/manual/products/product-media/product-media-typeshttps://damaheritage.com/experiments/jpg-png-webp/https://damaheritage.com/experiments/jpg-png-webp/Tue, 22 Sep 2026 00:00:00 GMTSix downloadable inputs and actual format exports show how photographs, text, patterns and noise change file-size results. Last checked 2026-10-20. What stayed constant Every row uses one normalized PNG input. Dimensions, background and source pixels remain unchanged while the format changes. Photographs are fitted to the canvas; the generated cases already use the target size. The normalized inputs are published so a repeat test does not depend on recreating a museum download or a drawing. The transparent test graphic is deliberately flattened to white before the three-format comparison. Its byte counts are therefore not an alpha-preservation test. The file-quality guide separately shows the transparent source and white/black composites. Interpret the trade-off Repeated structures can compress efficiently in PNG. Random noise contains many unpredictable pixels and is deliberately difficult to compress. A photograph of a real fabric or a detailed label can behave differently from either generated fixture. Byte counts are reproducible; acceptable quality is a viewing decision. Compare important detail at normal display size and at 100%. No visual-quality score, marketplace acceptance, sales improvement or device-speed claim was measured. 1. Choose a destination-supported format before optimizing bytes. 2. Compare outputs from the same input and dimensions. 3. Inspect label text, edges and texture rather than only file size. 4. Repeat with a second relevant image before committing to a batch setting. Question: Does one image format always produce the smallest useful file? Method: Normalize two CC0 photographs and four generated test fixtures to the same 1200 × 900 opaque canvas. Encode each unchanged input as JPG and WebP at quality 85 and as lossless PNG. Record dimensions, actual bytes and SHA-256 for the downloadable files. Result: WebP is smaller than JPG for both photographs in this set. PNG strongly favors the repeated woven pattern, while the seeded noise has a smaller JPG than WebP. The table and downloadable files are the result; no universal winner is implied. Limitation: Quality 85 is an encoder parameter, not equal perceptual quality across formats. The photographs were already JPEG-compressed before normalization. Synthetic stress cases do not represent a random sample of product photos. Browser and marketplace encoders can produce different files. Reference: Evidence generator and recorded input sources — https://github.com/huynjuunn-glitch/Milo/blob/main/scripts/generate-evidence.mjs Reference: MDN: toBlob format and quality behavior — https://developer.mozilla.org/en-US/docs/Web/API/HTMLCanvasElement/toBlobhttps://damaheritage.com/experiments/crop-geometry/https://damaheritage.com/experiments/crop-geometry/Tue, 22 Sep 2026 00:00:00 GMTInspect actual square, landscape and portrait files from one image, with the retained dimensions and removed edges explained. Last checked 2026-10-20. Calculate the retained frame For a square of side S, a centered 4:3 crop retains a height of 3S/4 and removes S/8 from each vertical edge. A 3:4 crop retains a width of 3S/4 and removes S/8 from each horizontal edge. With S = 800, that is 100 pixels at each affected edge. The same fractions apply to a larger square: a 2000 × 2000 source loses 250 pixels at each affected edge. A non-square source requires its own calculation. Do not carry the square example over to every source ratio. Judge the content removed The padded cup example has spare space at its sides, so removing side pixels need not remove the cup. The same crop could clip a handle in a tighter composition. Compare the actual product boundary, not merely the retained percentage. Use the separate thumbnail checklist to assess meaning, readability and the final marketplace preview. Its job is a publishing decision; this page provides the file geometry behind that decision. Question: Which edges disappear when a square image is center-cropped? Method: Start from the published 800 × 800 square export. Extract an 800 × 600 landscape frame and a 600 × 800 portrait frame with equal removal on opposite edges. Save both resulting image files. Result: The 4:3 export removes 100 pixels from both top and bottom; the 3:4 export removes 100 from both left and right. The downloadable images show what those pixels contained. Limitation: This is a controlled crop demonstration, not an Etsy screenshot or evidence that every storefront uses the same focal point. Reference: MDN: drawImage source and destination rectangles — https://developer.mozilla.org/en-US/docs/Web/API/CanvasRenderingContext2D/drawImagehttps://damaheritage.com/experiments/browser-limits/https://damaheritage.com/experiments/browser-limits/Tue, 22 Sep 2026 00:00:00 GMTCompare actual compressed file sizes with a transparent pixel-buffer calculation, without claiming a device memory benchmark. Last checked 2026-10-20. The file and its decoded pixels JPEG and WebP store an encoded representation. To display or manipulate it, a browser decodes image information and may create canvases, thumbnails and additional buffers. Compression efficiency therefore does not describe all working-memory costs. The four-bytes-per-pixel model is useful for explaining scale. It is not a claim that every browser uses exactly that representation for every operation. High-bit-depth sources, decoder storage and implementation details can require a different amount. Use the distinction to diagnose When a tab struggles, test one image and reduce dimensions before assuming that changing the extension will fix it. Reducing both width and height by half reduces pixel count to one quarter; the visual result must still be sufficient for the destination. Image Prep limits batch size and output pixels to reduce risk. Those safeguards are not a guarantee that a low-memory device can complete the maximum batch. The troubleshooting guide gives the recovery procedure without presenting a theoretical estimate as a device benchmark. Question: Why can a small file still demand substantial working memory? Method: Read the dimensions and byte count of the published JPEG files. Separately calculate width × height × 4 as a teaching estimate for one 8-bit RGBA pixel buffer. Result: A 1200 × 900 cup photo and a 1200 × 900 noise image have different compressed sizes but the same 4,320,000-byte one-buffer estimate. This result is arithmetic based on actual file dimensions. Limitation: No total browser RAM, processing speed or mobile-device capacity was measured. Extra copies, decoders, canvases, color formats and other tabs change real memory use. Reference: MDN: ImageData pixel representations — https://developer.mozilla.org/en-US/docs/Web/API/ImageData Reference: MDN: createImageBitmap — https://developer.mozilla.org/en-US/docs/Web/API/Window/createImageBitmap