When a folder contains a large number of images such as jpg and png, checking file paths, sizes, creation dates, modification dates, resolutions, and camera metadata one by one is very time-consuming. This article explains how to use the file information statistics function in office software to batch summarize the basic attributes and detailed image information of multiple pictures into an Excel spreadsheet, which is suitable for material management, image archiving, project delivery list creation, and digital asset inventory.
In daily office work and content management, many people encounter this problem: a folder contains dozens, hundreds, or even thousands of images, and they need to organize each image's file name, full path, extension, file size, creation time, modification time, resolution, as well as metadata like shooting device, color space, exposure, ISO, and focal length. Relying on right-click properties, image viewers, or manual entry in Excel is not only inefficient but also prone to omissions and errors.
This article addresses this typical repetitive task: using office software like HeSoft Doc Batch Tool , you can batch-collect information from many image files at once and aggregate it into an Excel spreadsheet. Its core value is not single-image viewing, but batch processing for a large number of files, especially suitable for users needing to create image asset ledgers, project file lists, gallery inventories, file audits, and delivery records.
Applicable Scenarios: When You Need to Batch-Collect Image Information
Batch-collecting image paths, resolutions, and metadata is suitable for many office scenarios. For example, a design team needs to organize a list of image assets for a project, needing to know both which directory the image is in and whether the image dimensions meet delivery requirements; operations personnel need to check if event assets are all in jpg or png format, and collect the size and modification time of each image; photography or educational resource managers need to aggregate metadata like camera model, shooting time, and exposure parameters; archivists might need to uniformly register image files scattered across folders into Excel for easier retrieval and archiving.
For just one or two images, manual viewing is certainly possible. But as the number of images increases, manual methods create three obvious problems: first, paths are long and copying is error-prone; second, fields like resolution, width, height, and size must be checked item by item, which is extremely inefficient; third, image metadata is extensive, and manual organization struggles to maintain field consistency. Using the file information statistics feature can output all this information to a spreadsheet at once, making subsequent filtering, sorting, and anomaly checking in Excel much more convenient.
Effect Preview: From Scattered Image Files to a Structured Excel List
Before processing, images exist only as a file list within a folder. As shown in the screenshot, file names include ClassNotesImage.jpg, CourseSummaryImage.jpg, ExamPreparationImage.jpg, GrammarReviewImage.jpg, etc. While names and some time information can be viewed in the file explorer, you cannot directly view the full path, resolution, camera information, and more metadata in bulk.
After processing, the software aggregates the image information into an Excel spreadsheet. The table contains not only the sequence number, name, path, extension, size, folder path, creation time, and modification time, but also details like image width, image height, color space, related metadata fields, camera manufacturer, camera model, lens model, ISO sensitivity, aperture value, etc. In this way, content originally scattered across file properties and image metadata is transformed into tabular data that can be filtered, sorted, and archived.
Steps: Using the File Information Statistics Feature to Batch Export Image Info
Step 1: Enter the File Information Statistics Feature under File Organization
After opening HeSoft Doc Batch Tool , you can see multiple tool categories on the left, such as File Organization, Word Tools, Excel Tools, PowerPoint Tools, PDF Tools, Text Tools, Image Tools, etc. Based on the screenshot, for this operation, select "File Organization" on the left, then click "File Information Statistics" in the feature cards on the right. This feature's description is batch-collecting various files' names, paths, sizes, times, and metadata information, perfectly matching the need to summarize image information.
The purpose of this step is to enter the wizard page specifically for collecting file attributes. Note that although we are dealing with images, the task here is not editing image content but collecting file information and detailed image information. Therefore, the entry point is "File Information Statistics" under "File Organization," not a pure image editing function.
Step 2: Add Image Files or Import Images from a Folder
Upon entering the "File Information Statistics" page, buttons like "Add File," "Import Files from Folder," "Clear," and "More" are provided at the top. For a small number of images, you can click "Add File" to select specific files; if images are centrally stored in a directory, it is more recommended to use "Import Files from Folder," which adds all images from the folder to the pending processing list at once.
In the screenshot, 20 records have been imported. The list displays basic fields like sequence number, name, path, extension, creation time, and modification time. For instance, the file path starts with D:\test\folders\, and the extension is jpg. The record count of 20 at the bottom indicates that the image files to be collected have been successfully added to the list.
The expected result of this step is to confirm in the software list that all images needing statistics have appeared. Users can check against the names and paths to verify correct import. If unwanted files are imported, they can be removed using the delete operation on the right; if the list content does not meet expectations, you can use "Clear" and re-add. The interface also provides "Filter" and "Sort" buttons, suitable for assisting in searching and organization when there are many files.
Step 3: Enter Processing Options and Check 'Image File Detailed Information'
After confirming the image list is correct, click "Next" at the bottom of the page to enter "Set Processing Options." In the screenshot, the processing options area is displayed as "Additional Information," containing checkboxes like Word File Details, Excel File Details, PPT File Details, PDF File Details, Text File Details, and Image File Details.
As the current goal is to collect image paths, resolutions, and metadata information, you need to check "Image File Details." From the processed Excel results, checking this option adds detailed image-related fields to the output table, such as image width, image height, color space, and several metadata fields. For jpg images, many files might also contain information like shooting device, lens, exposure, ISO, etc. Whether these values appear ultimately depends on whether the original image saved the relevant metadata.
Step 4: Set Save Location and Start Processing
After completing the selection of image file details, continue clicking "Next." The wizard interface shows subsequent steps including "Set Save Location" and "Start Processing." After setting the save location for the result file as prompted, you can proceed to the start processing stage. Since the goal of this feature is to aggregate the collected results into a spreadsheet, processing will produce a file list that can be opened with Excel.
The purpose of this step is to specify where the collected results will be saved, avoiding the issue of not finding the output file after processing. It is recommended to save the output spreadsheet in a folder related to the image project, such as the project data directory, asset delivery directory, or report directory. This makes subsequent review and archiving clearer.
Key Fields to Focus on in the Output Spreadsheet
The processed Excel spreadsheet contains many fields. It is recommended to focus on the following categories. The first category is basic file information, including name, path, extension, size, folder path, creation time, and modification time. These fields help you quickly build an image asset inventory, determining where the file comes from, if there are duplicates, and if it was recently modified.
The second category is image dimension information, including image width and image height. For scenarios like e-commerce main images, event posters, courseware illustrations, and website graphics, whether the resolution meets requirements is critical. Exporting width and height to Excel allows direct filtering for images that do not meet size standards.
The third category is image metadata information, such as color space, camera manufacturer, camera model, lens model, ISO sensitivity, etc. For managing photography assets, organizing evidence images, or classifying video archives, this metadata provides more source and shooting information. However, it should be noted that not all images contain complete metadata; some may have had their metadata removed after compression, forwarding, or secondary export.
Common Issues and Notes
Why Is Metadata Empty for Some Images?
Whether image metadata can be collected depends on whether the original file contains this information. Many jpg images captured by phones or cameras retain some EXIF information, but if an image has been screenshotted, compressed, downloaded from the web, shared on social platforms, or re-exported by certain software, the metadata might be removed. Therefore, it is normal for some metadata fields to be empty in the table, and this does not necessarily indicate a processing failure by the software.
Can It Only Process JPG Images?
The example screenshots imported jpg files, so this article uses JPG images as an example. When actually organizing images, common extensions also include jpeg, png, bmp, gif, webp, etc. It is advisable to check the file type and business requirements before importing. If you only need to collect jpg files, you can filter by extension in the folder first, or verify via the list after importing.
How to Avoid Disorganized Collection Results?
It is recommended to organize the folder structure before importing, placing images from the same project, batch, or source in a relatively clear directory. The collection results will include the full path and folder path; if the source folder naming is standardized, the exported Excel list will be easier to read. For asset inventories spanning multiple folders, the path field is particularly important for helping later locate the original file.
What Subsequent Processing Can Be Done in Excel?
After exporting to Excel, you can filter image formats by extension, sort by file size to find oversized images, identify recently updated assets by modification time, filter files with non-compliant dimensions by image width and height, and classify photography assets by fields like camera model or ISO. Compared to manual recording, a structured spreadsheet is better suited for review, reporting, and long-term archiving.
Summary: Transforming Image Information Collection from Manual Entry to Batch Generation
Batch-collecting image paths, resolutions, and metadata essentially offloads repetitive, tedious, and error-prone file information organization to office software. Using the "File Information Statistics" feature of HeSoft Doc Batch Tool , users only need to import images, check "Image File Details," set the save location, and start processing to aggregate the names, paths, times, dimensions, and metadata of a large number of images into an Excel spreadsheet.
If you are organizing image assets, creating file lists, verifying project delivery materials, or managing a photography library, it is recommended to prioritize this batch collection method. It can significantly reduce the time spent viewing properties one by one, making image inventory, filtering, and archiving more efficient and accurate.