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Multi format supported disk image converter.

Usage:

  1. Simple conversion
image_converter -i input_file.[mfm|raw|d77|hfe|fdx] -o output_file.[mfm|raw|d77|hfe|fdx] -v
  1. Merge images to generate a chimera image
image_converter -i input_file1.[mfm|raw|d77|hfe|fdx] [-i input_file2.[mfm|raw|d77|hfe|fdx]] [-i ...] -o output_file.[mfm|raw|d77|hfe|fdx] -v
Option Option parameters Description
-i in_file Specify input file. mfm, raw, d77, hfe, and fdx are supported.
The image converter can accept multiple image files as input. The converter will inspect all tracks in the images, select the best tracks among the images, and generates a merged image (a chimera image).
-o out_file Specify output file. mfm, raw, d77, hfe, and fdx are supported.
-n Normalize pulse pitch.
The converter will collect the statistics data of pulse pitch (pulse-to-pulse distance) for each track data and perform pitch normalization during the image format conversion process. With normalized data, the VFO operation will get stable and reading accuracy may improve.
-vfo vfo_type Specify VFO type. This option is effective only when D77 is specified as output.
0:vfo_simple, 1:vfo_fixed, 2:vfo_pid, 3:vfo_pid2, 9:vfo_experimental
-gain low high VFO gain setting. Effective only for D77. e.g. -gain 0.2 1.0
-raw Generate a VFX-RAW image. Effective only for a VFX image generation.
-auto_trim Automatic track data trimming. This feature automatically find the best point to trim down the track data so that the bottom of the track data and the top of the track data is stitched seamlessly.
You need to have a *.raw disk image with read_overlap to utilize this feature.
-v Verbose mode.
  • Supported image formats:
    • hfe : HxC disk emulator format (input only)
    • mfm : My original MFM bit stream format (input and output)
    • raw : My original MFM bit stream format captured by floppy_disk_shield_2d for Arduino
    • d77 : D77/D88 disk image format (input and output)
    • fdx : Disk image format for FDX68, FDD emulator

How -auto_trim feature work:

  1. Find address marks from a track data.
  2. Separate AMs for the 1st spin and the 2nd spin.
  3. Find the match AM pair from the 1st spin and the 2nd spin.
  4. Calculate the position of the top of the 2nd spin from the pair of AM found.
  5. Search the best stitching position by comparing the correlation of the FD data pulse pattern around the top of the 2nd spin.
  6. Trimm the track data at the stitching point found.