When multiple large images need to be uniformly cropped into fixed-size smaller images, manually cropping them one by one using photo editing software is very time-consuming and prone to issues such as inconsistent sizes, missed cuts, and chaotic naming. This article uses batch image processing as an example to introduce how to use the "Split Image into Multiple Smaller Images" feature in HeSoft Doc Batch Tool to automatically split multiple JPG images by specified width and height, and output them to corresponding folders. The article will explain the complete workflow of adding files, setting fixed width and height, continuing to save, and starting the processing, supplemented by before-and-after effects and operational screenshots, suitable for scenarios such as material organization, web image slicing, and training data preparation.
In daily office work, design collaboration, content operations, or data organization, a common need arises: you have many JPG, JPEG, PNG, and other image files, each of which is large, and you need to split them uniformly into small tiles of a fixed width and height. If you only have one or two to process, manually cropping them with an image editing software is acceptable; but if you have dozens or hundreds of images, repeatedly opening, cropping, saving, and renaming them consumes a lot of time, and it is easy to encounter problems like missing an image, inconsistent crop sizes, or mixed-up output files.
This article addresses the problem of "batch splitting many image files into small images by a fixed width and height." Using office software like HeSoft Doc Batch Tool , you can batch import image files, set the width and height for each small image at once, and then let the software complete the splitting automatically. Its core value is not single-image editing, but batch processing files to reduce repetitive labor, making mechanical operations like image splitting controllable, uniform, and reusable.
Applicable Scenarios: When is it suitable to batch split images by a fixed width and height?
Batch image splitting is not only for designers. If your work involves a large amount of image material and you need to split large images into small, uniformly-sized ones, you can use this method. Common scenarios include:
First, slicing assets for web or mobile interfaces. For example, a batch of banners, long images, or scene images need to be cut into fixed-size pieces for easier loading, layout, or partial display on a page. If each image is measured and cropped manually, efficiency is very low.
Second, archiving image assets. In photography, operations, and teaching materials, there are often large landscape, product, or screenshot images that need to be split into small-sized images for thumbnails, partial assets, or secondary editing. After cutting by a fixed width and height, the file sizes are uniform, making subsequent retrieval and use more convenient.
Third, dataset preparation. Some image recognition, annotation, or training tasks require original large images to be cut into tiles of fixed sizes, such as 200×200, 256×256, or 512×512. Batch splitting can quickly generate a large number of uniformly-sized small images.
Fourth, splitting office materials. Some scanned images, flowcharts, map screenshots, or display images are quite long and inconvenient to insert directly into documents, PPTs, or system backends. Splitting them into smaller images allows for separate use. Although the examples in this article are JPG images, a similar approach to batch image processing is also applicable to the organization needs of common image formats.
Result Preview: Multiple large images before processing become multiple folders of small images after processing
First, look at the file status before processing. In the screenshot, you can see that the current files to be processed are 5 JPG images, named 1.jpg, 2.jpg, 3.jpg, 4.jpg, and 5.jpg. Each image is a complete large image. If processed traditionally, you would need to open and manually crop each one.
After batch processing is complete, the output results become much clearer. In the processed screenshot, folders named 1, 2, 3, 4, and 5 appear at the top, which can typically be understood as output directories corresponding one-to-one with the original images. After selecting one of these folders, the split small images can be seen below, such as 01.jpg, 02.jpg, 03.jpg, all the way to 28.jpg. This means that one original large image has been cut into multiple small JPG files according to the set fixed width and height.
The advantage of this output structure is very clear: the splitting results for each original image are stored separately, making them less likely to be confused; the small images are named sequentially, making them easy to check and reference; and if one original image generates a large number of small images, it does not affect the management of results from other images.
Steps: Using office software to batch split images into multiple small images
The specific operations are described below in the order of the screenshots. The software interface shown here displays " HeSoft Doc Batch Tool " in the top left corner; it is a tool-oriented software for batch processing office files. Although the screenshot example processes image files, the software's focus is on improving file processing efficiency through batch operations, rather than having users repeat numerous manual steps.
Step 1: Enter Picture Tools and select "Split image into multiple small images"
After opening the software, select "Picture Tools" from the tool categories on the left. The main area will display multiple image-related functions, such as adding watermarks, enhancing image effects, and converting images to PNG, BMP, GIF, JPG, etc. According to the needs of this article, you need to find and enter the function "Split image into multiple small images". In the screenshot, this function is the 3rd item in the Picture Tools list, with the description "Batch split a large image into many small images".
The purpose of this step is to first clarify the type of batch task to be performed. Because there are many functions in Picture Tools, choosing format conversion or watermarking would not achieve a fixed-size split. After entering "Split image into multiple small images", the software will guide you through a wizard process, where you can follow the subsequent steps to add images, set the splitting method, and choose the save location.
Step 2: Add the image files to be processed or import from a folder
After entering the function page, you can see buttons at the top like "Add Files", "Import Files from Folder", "Clear", and "More". For a small number of images, you can click "Add Files" to select specific images; if the images are centrally stored in one folder, it is more suitable to use "Import Files from Folder" to add all images from that folder to the processing list at once.
The screenshot shows that 5 records have been imported, with names 1.jpg, 2.jpg, 3.jpg, 4.jpg, 5.jpg; the table also displays information like path, extension, creation time, and modification time. There are a few details worth noting: First, after importing, check if the record count is correct; the bottom of the screenshot shows "Record Count: 5", confirming all 5 images have been added. Second, you can check the file path in the table to avoid accidentally adding images from other directories. Third, if a file does not need to be processed, you can use the delete button in the operation column to remove it.
After verifying the files, click "Next" at the bottom. The expected result of this step is that all images to be split are in the processing queue, and the software is ready to proceed to the splitting parameter settings page.
Step 3: Choose fixed width and height splitting, and enter the width and height for each small image
On the "Set processing options" page, you can see the "Split Method" area. The screenshot provides two options: "Average Split" and "Fixed Size Split". The core requirement of this article is to cut by a fixed width and height, so "Fixed Size Split" should be selected.
After selecting Fixed Size Split, you need to fill in the "Width of each small image" and "Height of each small image". In the screenshot example, the width is filled in as 200, and the height is also filled in as 200, indicating the software will try its best to split each original image into multiple small images according to the 200×200 specification. This setup is very suitable for scenarios requiring uniform small image sizes, such as web assets, image training slices, regular thumbnails, etc.
It is recommended to decide the width and height based on the actual application. If they will be used for web display, set them according to the page card size; if for algorithm training, according to the training model requirements; if just for manual viewing and archiving, you can choose a size more convenient for previewing. Regardless of the settings, the key is that all images use the same set of parameters, avoiding the size inconsistencies caused by manual cropping.
After completing the width and height settings, click "Next". The expected result of this step is that the software now knows what size each small image should be generated, and you only need to set the output location and start processing.
Step 4: Set the save location and start batch processing
The wizard at the top of the screenshot shows subsequent steps including "Set Save Location" and "Start Processing". After completing the processing option settings, you need to proceed to the save location step and choose the output directory for the split small images. It is recommended not to output directly to the original image directory; it's better to create a dedicated result folder, such as "Image Split Results" or a folder named after the project, making subsequent checks more convenient.
The purpose of setting the save location is to manage original images and split results separately, avoiding file confusion. Especially during batch processing, one large image might generate a dozen, dozens, or even more small images. If they are scattered directly in the original directory, finding them later would be very troublesome. Coupled with the post-processed screenshot, it can be seen that the software creates corresponding result folders for the original images. Users can enter each folder to view the resulting small images.
After confirming the save location, proceed to the "Start Processing" step and execute the processing. Once processing is complete, open the output directory to see the small image files arranged by number. If many images are processed, it's advisable to spot-check a few folders first to confirm that the small image sizes, content order, and output quantity meet expectations before subsequent use.
Common Problems and Notes
1. What is the difference between Fixed Size Split and Average Split? From the screenshot, the software offers "Average Split" and "Fixed Size Split". Fixed Size Split is suitable when you have a specific small image size in mind, such as 200×200; Average Split leans more towards dividing the image according to some averaging rules. The requirement of this article is "by fixed width and height", so Fixed Size Split should be chosen.
2. Why are multiple folders generated after processing? From the post-processing effect, folders like 1, 2, 3, 4, 5 appear in the output directory. This structure typically corresponds to the original 1.jpg, 2.jpg, 3.jpg, 4.jpg, 5.jpg. This avoids small images split from different originals being mixed together and makes it easier to trace back to the original image.
3. Why are the small images named like 01.jpg, 02.jpg, etc.? The post-processing screenshot shows the small images are arranged in sequential numbering like 01.jpg, 02.jpg, 03.jpg. This naming method makes it easy to view the splitting results in order and convenient to reference later in systems, documents, or asset libraries.
4. After setting 200×200, will the edge tiles all be a full 200×200? This depends on whether the original image dimensions are perfectly divisible by 200, as well as the software's processing rules for edge areas. As the screenshot does not show options for edge padding or cropping, it is recommended during actual use to check the small images in the last row and last column after processing. If a project has strict size requirements, you should first test with a small number of sample images.
5. Is it necessary to back up the original images before batch processing? It is recommended to keep the original images. Although batch tools typically output results to a new location, backing up original files is a safe practice for any batch processing task. Especially when a large volume of assets is involved, the original images are the basis for re-setting parameters and splitting again later.
Summary: Replace repetitive cropping with a batch tool to quickly get uniformly-sized small images
Batch splitting large images into small images by a fixed width and height is fundamentally a file processing task that is highly repetitive but has very clear rules. Manual operation is not only slow but also prone to problems like inconsistent sizes, chaotic naming, and file omissions. Using HeSoft Doc Batch Tool , you can use the "Split image into multiple small images" function within "Picture Tools" to add multiple JPG images to the list at once, select Fixed Size Split, fill in the width and height, set the save location, and start processing.
As seen in the example from this article, before processing there were 5 independent large images; after processing, corresponding folders were generated based on the originals, with multiple sequentially-named small JPG files output within those folders. For office scenarios involving large quantities of images, this batch method can significantly reduce repetitive labor and improve material organization and delivery efficiency. It is recommended that you first test and confirm the appropriate width and height parameters with a few sample images before batch processing your complete image library.