simimg 0.5.1

Similar Image Finder

Similar Image Finder (Simimg)

Description

This is a python GUI for displaying pictures grouped according to similarity. The main aim of the program is to help identify groups of holiday snaps that resemble each-other and efficiently inspect those groups. It allows to easily keep only the best photos.

The program is not designed to identify the same but modified pictures (recompressed jpgs, cropped images or adapted colours, etc.). Although it can be used for this there are many and better solutions available.

Upon starting Simimg from the command line, by default it will load the pictures it finds in the startup directory and sub-directories into the GUI. These are settings that can be changed within the GUI by clicking on settings. In particular in the case you want to use the program by clicking on its icon, you may want to set an empty startup directory.

You can play with different options that take into account how similar two pictures are. These are the panels in the left section of the finder window. You can activate a condition by clicking on it name. The following options exist:

• Some gradient metrics adapted from ImageHash (dhash). Basically these measure whether two images have similar patterns of brighter and darker regions.

• I have also implemented measurements of how similar the colours are between two images, as well as between 5 regions (the four corners and the central part). The measurement in HSV (hue-saturation-value) is supposed the best reflect how human perceive image information.

• You can further select the maximum allowed time-span between the moments the pictures were taken in order to be considered a match.

• You can match on camera model. This means that to pictures are considered to be a match if they were taken with the same camera.

• Finally you can match on image shape. You can choose:

  • portrait/landscape: width smaller/larger or equal to height

  • exact: width/height are identical

  • some percentage difference allowed

Some of the selection criteria have additional parameters that you can play with.

Each condition has a Must Match checkbox. If this is switched on, only those pairs that satisfy this condition are considered matches. Note that:

1. Must Match has no effect if only one condition is active.

2. If some condition(s) have Must Match set, other conditions without Must Match have no effect.

3. When multiple conditions are active and no Must Match is set two images are considered a pair if any of the conditions is satisfied.

The actual use is to be able to better drill down the list. For example it allows to show only those groups that have similar colours and are taken with the same camera by switch on Must Match for both conditions

What matching groups are shown?

When the program starts, there are no active conditions and thumbnails of all files are shown in a grid sorted by filename.

Once some conditions are activated or changed the display will be updated.

For each picture that has some matches in the collection, the groups of matching thumbnails will be shown in a line. The only exception is a group that is already displayed in its entirety as a subgroup on another line.

Note that completely identical files (exact copies of some image file) will not be shown twice. Instead one thumbnail will be shown with a green border around it.

Note that for reasons of speed, the maximum number of thumbnails that will be shown will not exceed about 300.

Available functions

Thumbnail buttons

You can click on the Hide or Delete button below each image.

• Hide will remove the thumbnail from the display but it will not delete the file from your hard-disk.

• Delete will remove the file from the display and from your hard-disk.

(De)selecting thumbnails

You can select thumbnails by clicking on them; its background will turn blue to indicate that it is selected.

Pressing the Control (Ctrl) key while clicking will select or deselect the entire line of thumbnails.

Pressing the Shift key while clicking will select all thumbnails between the current image and the last selected image.

Clicking in an empty area of the thumbnail display area deselects all images. Pressing the little red check-mark button () in the toolbar area (top-left) also deselects all thumbnails.

Pressing Ctrl+a selects all thumbnails.

Actions for selected thumbnails

The Play button () in the toolbar will show a window that allows to view the selected images in larger versions (Ctrl+v).

The Minus button () will hide all selected thumbnails (Ctrl+h)

The Red-X button () will delete all selected thumbnails (Ctrl+d)

Actions in the viewer window

One design goal is a clean interface with a lot of room for the pictures themselves. Therefore there are no action buttons in the viewer.

The follow actions are available in the viewer window:

• F1 or i: show a short help window

• arrow right, scroll-wheel up or n: show the next picture

• arrow left, scroll-wheel down or p: show the previous picture

• delete or d: delete the picture from disk

• escape of q: quit the viewer

Technical remarks

Some of the calculations can be time-consuming and Simimg tries to be clever about not recalculating. It will store the calculated values in a database for future use. It recognises the pictures files by their MD5-hash which means that even if you move files or rename them, their image properties will not be recalculated.

It attempts to do the most expensive calculations in parallel making optimal use of the CPU capabilities.

I have seen quite a variety of 'success', meaning that some algorithm detects matches that I myself would also call a match. It depends a lot on the set of images that one uses as input. I find it useful to play around a bit with selecting different algorithms and playing with the numerical limits. To help with this, the tooltip of the limit selectors will tell you at which value the first match happens and at which value more than 10 matches are found.

In my experience, for the purpose of detecting the most interesting similar holiday pictures the "Average" and "Perception" algorithms can be useful but the "HSV (5 regions)" in the Colours Conditions gives the best results.

The other conditions should be considered optional to further limit the shown matches.

Credit

This project uses the following open source packages:

• Python: version 3

• tkinter that should normally come with your python

• pillow for image reading and processing.

• The tooltip code is adapted from an example found on Daniweb.

Some of the algorithms used have been inspired by code found at imagedupes, pyimagesearch and imageHash.