The fastest Android super.img dumper, made in Python.
- Extremely fast - Best in its class, see speed below
- Unsparse support - Automatically unsparses images without any dependancies
- Smart extraction - Automatically skips empty partitions
- Selective usage - unsuper can extract only specific partitions or just unsparse the image
Download the script, or clone into the repository if you want to contribute / fork.
Download and install Python (3.6 and later) and add it to PATH.
Install the numpy module using pip install numpy.
Follow Usage. You'll need to type "python" before calling the script, the directions don't include that for simplicity.
Simply run pip install unsuper to install the latest version globally.
You'll also need to run pip install numpy as V2.0.0 and newer versions use Numpy for faster extraction. If this is not possible (e.g. on Termux), run pip install unsuper==1.0 to download the first version instead.
If you don't want to install Python, simply download and use the latest executable binary for your operating system from the releases page.
unsuper can unsparse a 6.67GB super.img in only 11 seconds, and dump all available partitions in ~12 seconds on an average NVMe disk with the default of 4 threads. This puts the total extraction time to under 25 seconds, faster than any other competitor. This also means that V2.x extracts partitions up to 2.5x faster compared to V1.0.
Performance may vary based on the amount of threads and disk speeds. More threads doesn't always equal to higher speeds.
unsuper's usage is extremely easy: just state the path to your super.img and start. If no output directory is stated, unsuper will create an "extracted_partitions" folder under your home directory and use it as default.
Extra arguements come AFTER the positional arguements.
positional arguments:
super_image Path to super.img file
output_dir Output directory for extracted partitions (default: extracted_partitions)
options:
-h, --help show this help message and exit
--version show program's version number and exit
-p, --partitions PARTITIONS [PARTITIONS ...]
Specific partition names to extract (vendor, product etc.) (default: extract all)
-j, --jobs JOBS Number of parallel extraction threads (default: 4)
-q, --quiet Suppress progress output
--list List available partitions and exit
--temp-dir TEMP_DIR Directory for temporary unsparse file (default: system temp directory)
--unsparse Unsparse image and save to output directory
--dump-metadata Dump partition metadata to metadata.json in output directory
For example, if you want to extract the system_a partition using 6 threads:
unsuper.py /path/to/super.img /output_path --partitions system_a --jobs 6
And so on.
unsuper can also simply unsparse an image and save it to a specified directory:
unsuper.py /path/to/super.img /output_path --unsparse
Or list all available partitions and clean after:
unsuper.py /path/to/super.img --list
If the --list arguement is used with --partitions, it will calculate the specified partitions' sizes and exit.
If the --unsparse arguement is used along with --partitions or --list, the unsparse image will be saved to the output directory and reused for extraction rather than creating a temporary one.
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