duplicate_images 0.11.10
Finds equal or similar images in a directory containing (many) image files
Requires Python: >=3.12

# Finding Duplicate Images

Finds equal or similar images in a directory containing (many) image files.

Official home page: https://github.com/lene/DuplicateImages

Development page: https://gitlab.com/lilacashes/DuplicateImages

PyPI page: https://pypi.org/project/duplicate-images

## Usage

Installing:
```shell
$ pip install duplicate_images
```

Printing the help screen:
```shell
$ find-dups -h
```

Quick test run:
```shell
$ find-dups $IMAGE_ROOT 
```

Typical usage:
```shell
$ find-dups $IMAGE_ROOT --parallel --progress --hash-db hashes.json
```

### Supported image formats

* JPEG and PNG (tested quite thoroughly)
* HEIC (experimental support, tested cursorily only)
* All other 
  [formats supported](https://pillow.readthedocs.io/en/latest/handbook/image-file-formats.html) by 
  the `pillow` Python Imaging Library should work, but are not specifically tested. 

#### Explicitly allow huge images

The `PIL` image library, which is used as backend, limits the size of images to 178956970 pixels by
default, to guard against memory exhaustion. For larger images, specify the maximum image size in 
pixels with the `--max-image-pixels` option.

### Image comparison algorithms

Use the `--algorithm` option to select how equal images are found. The default algorithm is `phash`.

`ahash`, `colorhash`, `dhash`, `dhash_vertical`, `phash`, `phash_simple`, `whash`, `crop_resistant`:
seven different image hashing algorithms. See https://pypi.org/project/ImageHash for an introduction
on image hashing and https://tech.okcupid.com/evaluating-perceptual-image-hashes-at-okcupid-e98a3e74aa3a 
for some gory details which image hashing algorithm performs best in which situation. For a start I 
recommend using `phash`, and only evaluating the other algorithms if `phash` does not perform 
satisfactorily in your use case.

### Image similarity threshold configuration

Use the `--hash-size` parameter to tune the precision of the hashing algorithms. For the `colorhash`
algorithm the hash size is interpreted as the number of bin bits and defaults to 3. For all other
algorithms the hash size defaults to 8. For `whash` it must be a power of 2.

Use the `--max-distance` parameter to tune how close images should be to be considered duplicates.
The argument is a positive integer. Its value is highly dependent on the algorithm used and the 
nature of the images compared, so the best value for your use case can oly be found through 
experimentation. 

**NOTE:** using the `--max-distance` parameter slows down the comparison considerably with large
image collections, making the runtime complexity go from O(N) to O(N<sup>2</sup>). If you want to 
scan collections with at least thousands of images, it is highly recommended to tune the desired 
similarity threshold with the `--hash-size` parameter alone, if that is at all possible. 
The '--max-distance' parameter it's incompatible with --group parameter.

**NOTE:** the `--max-distance` parameter conflicts with tho `--group` parameter. You can only use 
one at a time.

### Pre-storing and using image hashes to speed up computation

Use the `--hash-db ${FILE}.json` or `--hash-db ${FILE}.pickle` option to store image hashes in the 
file `$FILE` in JSON or Pickle format and read image hashes from that file if they are already 
present there. This avoids having to compute the image hashes anew at every run and can 
significantly speed up run times.

### Handling matching images either as pairs or as groups

By default, matching images are presented as pairs. With the `--group` CLI option, they are handled
as a group containing all matching images.

Example: `1.jpg`, `2.jpg` and `3.jpg` in the current folder `.` are equal.

```shell
$ find-dups .
1.jpg 2.jpg
1.jpg 3.jpg
2.jpg 3.jpg
$ find-dups . --group
1.jpg 2.jpg 3.jpg
```

### Actions for matching image groups

Use the `--on-equal` option to select what to do to pairs of equal images. The default action is 
`print`.
- `delete-first` or `d1`: deletes the first of the files in the group
- `delete-last` or `dl`: deletes the last of the files in the group
- `delete-biggest` or `d>`: deletes the file with the biggest size
- `delete-smallest` or `d<`: deletes the file with the smallest size
- `move-first` or `m1`: moves the first of the files in the group to the folder specified with the
  `--move-to` option
- `move-last` or `ml`: moves the last of the files in the group to the folder specified with the
  `--move-to` option
- `move-biggest` or `m>`: moves the file with the biggest size to the folder specified with the
  `--move-to` option
- `move-smallest` or `m<`: moves the file with the smallest size to the folder specified with the
  `--move-to` option
- `symlink-smaller`: delete the smaller files and replace them to a symlink to the biggest file
- `symlink-bigger`: delete the bigger files and replace them to a symlink to the smallest file
- `eog`: launches the `eog` image viewer to compare the files in the group (*deprecated* by `exec`)
- `xv`: launches the `xv` image viewer to compare the files in the group (*deprecated* by `exec`)
- `print`: prints the files in the group
- `print_inline`: like `print` but without newline
- `quote`: prints the files in the group quoted for POSIX shells
- `quote_inline`: like `quote` but without newline
- `exec`: executes a command (see `--exec` argument below)
- `none`: does nothing; may be useful for benchmarking and testing

The `move-*` actions require the `--move-to` option to specify the target folder. Additionally, the
`--move-recreate-path` option can be set to reproduce the directory structure of the source files in
the target folder.

The `--exec` argument allows calling another program when the `--on-equal exec` option is given.
You can pass a command line string like `--exec "program {1} {2}"` where `{1}` and `{2}` are
replaced by the matching pair files (or first two files in a group), quoted so the shell recognizes
the files properly. The wildcard `{*}` expands to all files in a matching group, which when called
with the `--group` argument may be more than two images considered equal.

#### Examples:
* `--exec "open -a Preview -W {1} {2}"`: Opens the files in MacOS Preview app and waits for it.
* `--exec "ls -s {*}"`: Prints the size (in blocks) next to all files.
* `--exec 'for i in {*}; do dirname $i; basename $i; done'`: Shows the directory and the filename
  separately for all files.

### Parallel execution

Use the `--parallel` option to utilize all free cores on your system for calculating image hashes.
Optionally, you can specify the number of processes to use with `--parallel $N`.

To execute the `--on-equal` actions in parallel, use the `--parallel-actions` option, which also can
take an optional number of processes to use as argument.

### Excluding subfolders

Use the `--exclude-dir` option to exclude subfolders of `$IMAGE_ROOT` from the search. The argument
is a regular expression matching the subfolder names to be excluded. Multiple arguments can be 
passed to `--exclude-dir` to exclude multiple subfolders. 

The argument(s) given to `--exclude-dir` may be regular expressions. These regular expressions are 
matched only against the directory name, not the file name.

#### Examples

Exclude subfolder `$IMAGE_ROOT/foo`:
```shell
$ find-dups $IMAGE_ROOT --exclude-dir $IMAGE_ROOT/foo
```
Exclude all subfolders named `foo` or `bar`:
```shell
$ find-dups $IMAGE_ROOT --exclude-dir foo bar
```

### Slow execution

`find-dups` can also use an alternative algorithm which exhaustively compares all images to each
other, being O(N<sup>2</sup>) in the number of images. This algorithm is selected automatically if
`--max-distance` is not 0.

You can use the `--slow` option to use this alternative algorithm specifically. The `--slow` switch
is mutually exclusive with the `--group` switch.

### Progress bar and verbosity control

- `--progress` prints a progress bar each for the process of reading the images, and the process of 
  finding duplicates among the scanned image
- `--debug` prints debugging output
- `--quiet` decreases the log level by 1 for each time it is called; `--debug` and `--quiet` cancel
  each other out

## Development notes

Needs Python3, Pillow imaging library and `pillow-heif` HEIF plugin to run, additionally Wand for 
the test suite.

Uses Poetry for dependency management.

### Installation

From source:
```shell
$ git clone https://gitlab.com/lilacashes/DuplicateImages.git
$ cd DuplicateImages
$ pip3 install poetry
$ poetry install
```

### Running

```shell
$ poetry run find-dups $PICTURE_DIR
```
or
```shell
$ poetry run find-dups -h
```
for a list of all possible options.

### Test suite

Running it all:
```shell
$ poetry run pytest
$ poetry run mypy duplicate_images tests
$ poetry run flake8
$ poetry run pylint duplicate_images tests
$ poetry run bandit -r duplicate_images
```
or simply 
```shell
$ .git_hooks/pre-push
```
Setting the test suite to be run before every push:
```shell
$ cd .git/hooks
$ ln -s ../../.git_hooks/pre-push .
```

### Publishing

A tag is created and the new version is published automatically by GitLab CI on every successful
merge to `master`.

#### Prerequisites

For every Merge Request to `master` it is checked that:
- the `version` number in `pyproject.toml` is not an already existing git tag
- the `CHANGELOG.md` contains an entry for the current version number

#### PyPI

There is a job in GitLab CI for publishing to `pypi.org` that runs as soon as a new tag is added, 
which happens automatically whenever a MR is merged. The tag is the same as the `version` in the 
`pyproject.toml` file. For every MR it needs to be ensured that the `version` is not the same as an 
already existing tag.

To publish the package on PyPI manually:
```shell
$ poetry config repositories.testpypi https://test.pypi.org/legacy/
$ poetry build
$ poetry publish --username $PYPI_USER --password $PYPI_PASSWORD --repository testpypi && \
  poetry publish --username $PYPI_USER --password $PYPI_PASSWORD
```
(obviously assuming here that username and password are the same on PyPI and TestPyPI)

#### Updating GitHub mirror

The GitHub repo `git@github.com:lene/DuplicateImages.git` is set up as a push mirror in GitLab CI, 
but mirroring is flaky at the time and may or may not succeed. The CI job `PushToGithub` should take
care of mirroring to GitHub after every merge to `master`.

To push to the GitHub repository manually (assuming the GitHub repo is set up as remote `github`):
```shell
$ git checkout master
$ git fetch
$ git pull --rebase
$ git tag  # to check that the latest tag is present
$ git push --tags github master 
```

#### Creating Releases on GitHub

The CI job `CreateGithubRelease` creates a Release on GitHub, which can then be found under
https://github.com/lene/DuplicateImages/releases.

### Profiling

#### CPU time
To show the top functions by time spent, including called functions:
```shell
$ poetry run python -m cProfile -s tottime ./duplicate_images/duplicate.py \ 
    --algorithm $ALGORITHM --action-equal none $IMAGE_DIR 2>&1 | head -n 15
```
or, to show the top functions by time spent in the function alone:
```shell
$ poetry run python -m cProfile -s cumtime ./duplicate_images/duplicate.py \ 
    --algorithm $ALGORITHM --action-equal none $IMAGE_DIR 2>&1 | head -n 15
```

#### Memory usage
```shell
$ poetry run fil-profile run ./duplicate_images/duplicate.py \
    --algorithm $ALGORITHM --action-equal none $IMAGE_DIR 2>&1
```
This will open a browser window showing the functions using the most memory (see 
https://pypi.org/project/filprofiler for more details).

## Contributors

- Lene Preuss (https://github.com/lene): primary developer
- Mike Reiche (https://github.com/mreiche): support for arbitrary actions, speedups
- https://github.com/beijingjazzpanda: bug fix