PPM2FLI(1)PPM2FLI(1)NAMEppm2fli - create a FLI animation from a set of static images
SYNOPSISppm2fli [ options ] [ list-file [ animation-file ] ]
DESCRIPTION
The program ppm2fli generates a FLI/FLC-animation from a series of
images. The file list-file contains a list of the names of image
files, one per line separated by the new-line character. These images
are merged together in the supplied order. The generated animation is
written to animation-file.
The file formats which can be read directly are PPM, PGM and PBM (ascii
and raw: magic 'P1' to 'P6') as well as FBM (mapped 8bpp and rgb
24bpp). Ppm2fli can invoke external filters which convert other file
formats to the PPM or FBM standard. For example such filters are
included in the PBMPLUS, NETPBM and FBM packages. Together with these
packages a large number of graphic formats can be handled.
The generation of the animation is done in two separate steps:
- Computation of a common color table for all images
- Quantization of the images and computing the FLI/FLC frames
The first step is done by scanning all images and using a modified ver‐
sion of the Octree algorithm to compute a color table from the shades
found in the images. This color table is supposed to be a -- more or
less -- best fit to the color shades which were found in the images.
When the input images are already quantized the result depends on the
number of colors which they use altogether. If this number is equal or
less than the given maximum (default: 256), the scanning step just
evaluates these colors and assembles the color table without any modi‐
fication. When the input images contain more colors, some colors are
put together and assigned to an average value, until the total number
is sufficiently low.
Alternatively it's possible to generate the color table by scanning
only one image, a so called map image. It may be one from the given
list or an extra image. This procedure is faster but the resulting
color table may be less suitable for the other images.
Third possibility is to do the quantization separately and generate an
extra color table for each image. This may result in a change of the
color table between the frames of the FLI animation. However, the pro‐
gram tries to keep the color table as static as possible.
The area of the image that the final animation produces when played is
denoted as display_area. Default is a display_area of 640x480 pixels.
It is allowed that the size of the input images varies. If the width
of an input image is greater than the width of the display_area, an
equal number of pixels is removed from each side of the input image.
If the width of an input image is less than the width of the dis‐
play_area, this results in the creation of a border around the image
(default: center the image in the display_area). The same is done in
vertical direction.
QUANTIZE OPTIONS-I Perform an individual quantize of each image independently of
all other images. In this case no common table is used and it
may occur that new colors are loaded between the FLI/FLC frames.
Usually a common color table should be preferred. Only when
this results in very poor quantization of the images a varying
color table is recommended.
-Qc numcolors
Employ numcolors as the maximum number of colors used in the
quantized images (range: 9-256; default: 256). A low value may
result in a poor quantization.
-Qd bits
Employ bits as the color depth used in the color map of the
quantized images (range: 2-8; default: 8). Lower values reduce
the number of colors in the quantized images.
-Qn nodelimit
Set the maximum number of nodes that the Octree is allowed to
have in the second-deepest level. A larger value may result in
a better quantization but slows down the scanning of the images.
Recommended values: between one time and four times the numcol‐
ors value (range: 16-2048; default: 512). See section "TECHNI‐
CAL NOTES" for more details.
-Qr reducelevels
Set the number of levels which are considered when reducing the
Octree (range: 0-8; default: 8). See section "TECHNICAL NOTES"
for more details.
-m file
The common color table is generated by scanning only the image
in the given file. Usually this is much faster than scanning
all images, but the color table represents only colors which
occur in the given image. If this image is not representative
for the others, their quantization may become very poor.
-w file
The generated color table is written to the given file as a
256x1 PPM ascii image. Then the program terminates without
assembling the fli animation. Later this color table file can
be used with the `-m' option to generate the fli animation.
When the `-w' option is given the parameter animation-file can
be omitted. If both `-m' and `-w' are given also the parameter
list-file isn't necessary.
FLI/FLC OPTIONS
-D Include additionally update information with respect to the
frame before the last. Default: generated FLI chunks hold
update information only for the immediately preceding frame.
In both cases, the resulting animations work with standard play‐
ers. The additional update information is useful for players
that use the double buffering technique (see TECHNICAL NOTES
section below).
-N Same as `-D' but instead of the frame before the last the update
information with respect to the following frame is included.
This allows the play in reverse direction with the XAnim player.
Note that `-D' and `-N' exclude each other.
-O Generate output using the older FLI format associated with magic
number 0xAF11. Some older players cannot handle newer FLI ani‐
mations associated with the magic number 0xAF12 (these are some‐
times known as FLC files). Use the old LC_CHUNKS (12) instead
of DELTA_CHUNKS (7), and COLOR_CHUNKS (11) instead of
COLOR_256_CHUNKS (4), and set default resolution to 320x200
instead of the usual 640x480.
-b color
If a particular input image does not cover the entire dis‐
play_area, employ the specified color for all pixels in the bor‐
der area. Default: zero (See also `+/-ox'). To evaluate which
number a certain color has the `-w' option can be used. By that
the color table is written to a file (ascii) and then the
desired color can be looked up in the table.
-g widthxheight
This defines the width and height of the display_area (allowed
range: from 10x10 to 1280x1024). If an odd value of width is
specified, it is automatically incremented by one. A particular
FLI player may only support a limited set of resolutions. In
principle, VGA resolution (320x200) should always work. For
players supporting the newer style of FLIs (FLCs) associated
with the magic number 0xAF12, 640x480 should also work.
+/-ox hor_position
Disable the automatic centering of input images in horizontal
direction. Place the input images at a fix position in the dis‐
play_area. When `+ox' is used the left border of the input
images is kept fix independently of the width of the images.
The value gives the distance between the left border of the dis‐
play_area and the left border of the input image. When `-ox' is
used the right border of the input images is kept fix. The
value gives the distance between the right border of the dis‐
play_area and the right border of the input image. In both
cases negative values can be specified. Then the respective
border of the input images is outside of the display_area and a
part of the images is cut off. The option can be used to place
input images with varying width at a certain position in the
display_area, or to animate a certain section of larger input
images.
+/-oy vert_position
Identical to `+/-ox', but controls the vertical position. When
`+oy' is used the number of pixels from the upper border of the
display_area to the upper border of the input images is set.
Respectively `-oy' controls the position with respect to the
lower border.
-s speed
Use the specified speed to be stored in the header of the FLI
file. The FLI standard requires a speed value in the file.
Some players use this number as default when no other speed is
given. The meaning of the speed argument depends on the FLI
format in use. Higher values reduce the speed. For old format
FLIs, the value specifies the number of video ticks between two
frames (default: 5). For new format FLIs, the delay between two
frames is specified in 1/1000 seconds rather than video ticks
(default: 72/1000 seconds, resulting in approximately 15 frames
per second).
GENERAL OPTIONS-v Print internal information to stdout. `-vv' causes even more
things to be written.
+/-f filter
Use the specified filter when reading the input images. This is
necessary when other than the default formats are used or when
the input files are compressed (see the examples below). The
reading is done using the popen subroutine. If `-f' is used the
specified filter is supposed to read from stdin. The command
used in the popen statement has the form `filter < image'. In
the case of `+f' the image name if passed as argument to the
filter program. In both cases the filter program has to write
the converted image to stdout. The option overwrites the filter
defined by the environment variable PPM2FLIFILTER.
-t Test the file magic of the input files before using the read
filter. Only files which have no PPM, PGM, PBM or FBM format
are read through the given filter. By default all files are
read through a given filter. When no filter is specified the
`-t' option has no effect.
ENVIRONMENT
A frequently used read filter can be defined using the environment
variable PPM2FLIFILTER. The name of the filter can be preceded by a
`+' or `-' sign (see the example below). The `-' sign as first charac‐
ter corresponds to the usage of `-f' in the command line and a `+'
works like `+f'. By default `-' is assumed which means that the filter
reads from stdin.
EXAMPLES
Basic Usage
Assume the existence of a series of PPM images which have the names
image01.ppm,
image02.ppm,
image03.ppm,
etc.
The goal is to produce a FLI animation from these files in the given
order. First the list-file is prepared. We choose the name
`pics.list' for this file. The file is generated by:
% ls -1 image??.ppm > pics.list
Note that this only works if no other files in the directory match the
specified pattern and the desired order corresponds to the numbering
system in the file names. In the second step a FLI file with the name
`anim.fli' is generated using the command:
% ppm2fli pics.list anim.fli
The generated animation has the resolution 640x480. Assume that the
given images are only 320x240. Then they appear in the middle of the
640x480 display area and are surrounded by a border area. To avoid
this border we fit the FLI resolution at the pixel size of the input
images. This can be done by:
% ppm2fli-g 320x240 pics.list anim.fli
In the next example we begin with a series of 768x512 images. The goal
is to animate these images, cutting off the top 20 lines of each image.
Again the name of the list-file is `pics.list' and the name of the gen‐
erated FLI file is `anim.fli'.
The appropriate command line is:
% ppm2fli-g 768x492 +oy -20 pics.list anim.fli
Note 1):
492 = 512 - 20.
Note 2):
If in the given example the `+oy' option was omitted, 10 lines
at the top and bottom would be cut off.
Read Filters
We assume that all input images are in the GIF format and that we have
the PBMPLUS package with the program giftoppm installed. Like in the
example described above we create a list file with the names of the GIF
files. Then the FLI is generated by the command
% ppm2fli-fgiftoppm pics.list anim.fli
In this case all images given in `pics.list' have to be in GIF format.
If we use the FBM package instead of PBMPLUS we have to use another
utility. Now the command line looks like
% ppm2fli-ffbcat pics.list anim.fli
The utility fbcat converts the GIF images to FBM format which is read
by ppm2fli. Because fbcat understands also other formats, like SUN
raster or FBM, the input files can have different formats.
It is also possible to use shell scripts as filters. For instance we
want to animate a ray-tracer scene. The images were generated by POV-
Ray but we made a big mess. Some are stored in QRT format, some as TGA
files and others are already converted to PPM. To save disk space some
files are compressed by gzip. We are in luck because we used always
the correct extensions in the file names. We have gunzip installed and
the utilities qrttoppm and tgatoppm are available. We edit a shell
script with the following content:
#! /bin/ksh
name=$1
cmd=cat
function isit
{
base=${name%.$1}
if test "$name" = "$base.$1"; then cmd=$2; fi;
}
isit "gz" "gunzip"
isit "qrt" "qrttoppm"
isit "qrt.gz" "(gunzip | qrttoppm)"
isit "tga" "tgatoppm"
isit "tga.gz" "(gunzip | tgatoppm)"
$cmd < $name
The script is stored as `myfilter' in the current directory (... chmod
a+x myfilter). To use this filter we type
% ppm2fli +fmyfilter pics.list anim.fli
Note that now `+f' is required because our filter doesn't read from
stdin. It needs the file name as parameter to choose the corresponding
utility. The given script works only for the Bourne/Korn shell.
When the filter requires additional parameters they can be passed in an
easy way. For instance works
% ppm2fli-f "gzip -d" pics.list anim.fli
for a series of "gzipped" input files.
Even more complicated things are possible. For example the ghostscript
program can be used as read filter to animate a series of PS images.
The necessary option may look like
-f "gs -g320x480 -q -r36 -sDEVICE=ppm -sOutputFile=- -"
which works for the `tiger.ps' example. Note that to reduce the data
flow `ppmraw' should be preferred to the `ppm' device.
When a certain filter is often used, the environment variable PPM2FLI‐
FILTER can be set to define the filter. In a bash environment this may
look like
% export PPM2FLIFILTER=-fbcat
Then always the fbcat utility is used as read filter unless something
else is defined in the command line.
Usage of a Map File
Again we assume a series of images, but now the goal is to produce two
animations with a different order of the images. For this purpose we
edit by hand two list files `order1.lst' and `order2.lst'. To save
time and to avoid a repeated scanning of the input images the scanning
is done in a separate step. The result of the scanning is the common
color table. This table has to be stored in an extra file. We choose
the name `ct.ppm' for this file. Then the first step looks like:
% ppm2fli-w ct.ppm order1.lst
In the next step the first animation is generated:
% ppm2fli-m ct.ppm order1.lst order1.fli
And finally:
% ppm2fli-m ct.ppm order2.lst order2.fli
Usually, if no individual quantization is used, all images are read
twice. Once for generating the color table and the second time when
the quantize & assembling is done. Thus, the options `-m' and `-w' can
help to save a lot of time, especially when the input files are com‐
pressed or have another file format and each reading through a filter
requires more time.
Note that the map file is not read through a given filter. Thus, this
file always has to be in one of the formats which can be read directly.
Quantization using an external utility
A modified version of the Octree algorithm is implemented in ppm2fli.
By default this algorithm is used when the input files contain more
than 256 colors. This maximum of colors can be changed to lower values
using the option `-Qc'. Sometimes it may be desirable to use a differ‐
ent quantization algorithm. In the following example we want to ani‐
mate a ray-tracer scene generated by the POV-Ray program. The image
files are in gzipped QRT format and we have the PBM package with the
utility qrttoppm installed. Again the list-file with the names of the
QRT images has the name `pics.list'. The quantization shall be done
with the ppmquant program of the PBM package, because it offers the
possibility of Floyd-Steinberg error diffusion. Nevertheless we would
like to get a FLI animation where the color table is static. Then we
do in the first step
% ppm2fli pics.list -w ct.ppm -f"(gunzip | qrttoppm)"
By that the color table is evaluated by the Octree algorithm and stored
in the file `ct.ppm'. To avoid a exceeding command line we edit a
shell script with the content
#! /bin/csh
gunzip | qrttoppm | ppmquant -fs -map ct.ppm
and store this file as `myquant' in the current directory (... chmod
a+x myquant). When this is done we generate the FLI animation
`anim.fli' by the command
% ppm2fli pics.list anim.fli -m ct.ppm -fmyquant
Note that usually the Floyd-Steinberg error diffusion results in a
large number of isolated pixels in the quantized image. This is used
to avoid the typical color steps which occur in regions with smooth
transitions between different colors. But the compression method used
in the FLI format is inefficient when too many isolated pixels occur
within an image. Thus, the better image quality is payed by a much
larger size of the FLI file.
TECHNICAL NOTES
The Modified Octree Algorithm
The Octree algorithm does the quantization in three phases:
(1) Scanning of the image
(2) Reduction of the Octree
(3) Mapping
First the images are scanned to evaluate what colors are present. For
this purpose internally a list of colors is created. To speed up the
sorting a tree structure -- the so called Octree -- is used rather than
a linear list. This tree structure has a main node which can have up
to 8 sub-nodes. Each sub-note itself can have again 8 sub-sub-nodes
and so on. So the sub-nodes can be regarded as sub-trees.
A geometric interpretation exists for the sorting of RGB colors by the
Octree: A RGB color can be regarded as a point with coordinates
(red,green,blue) in a 3-dimensional space. The orthogonal coordinate
system of this space has axis in the directions red, green and blue.
Total black is defined as the origin of this space (0,0,0). Because of
the discrete 8bit representation of each RGB component the point
(255,255,255) corresponds to maximum bright white. All possible
256*256*256 > 16 Million
RGB combinations form a regular three-dimensional grid in this space.
The grid can be covered by a cube with side length 255. This cube cor‐
responds to the main node of the Octree. The sorting is done by subdi‐
viding the cube symmetrically in 8 sub-cubes of equal size. The sub-
cubes contain the points
1. (r,g,b) = ( 0 - 127, 0 - 127, 0 - 127)
2. (r,g,b) = ( 0 - 127, 0 - 127, 128 - 255)
3. (r,g,b) = ( 0 - 127, 128 - 255, 0 - 127)
4. (r,g,b) = ( 0 - 127, 128 - 255, 128 - 255)
5. (r,g,b) = (128 - 255, 0 - 127, 0 - 127)
6. (r,g,b) = (128 - 255, 0 - 127, 128 - 255)
7. (r,g,b) = (128 - 255, 128 - 255, 0 - 127)
8. (r,g,b) = (128 - 255, 128 - 255, 128 - 255)
These sub-cubes correspond to sub-nodes of the main node in the Octree.
At the beginning all 8 bits of the RGB values are taken into account
when sorting the colors. It is checked for a pixel in which sub-cube
its color belongs. Then it is checked if a corresponding sub-node for
this sub-cube already exists. If not a new node in the Octree is gen‐
erated which represents this sub-cube. Then the sub-cube itself is
divided in eight sub-sub-cubes and so on. The subdivision is done
until the color is located in the finest cube which contains only one
of the possible discrete RGB points. This results in 8 levels of sub-
cubes, which all represent a node in different levels of the Octree.
The nodes in the finest level (also called deepest level), which have
no sub-nodes, are called leaves.
The sorting procedure is done for all pixels in the input images.
Additionally the modified algorithm does for each sub-cube a count of
the pixels which where located in this cube. Furthermore a sum of the
RGB values is computed for all pixels in each sub cube.
In principle all pixels in a true color picture can have different
shades. Thus, the Octree might grow and grow, and it may become impos‐
sible to store the information for all nodes in the main memory. Of
course this depends on the content of the input images. To avoid a
very large Octree a reduction is done, when the number of nodes that
the Octree has in the second-deepest level exceeds a certain threshold.
The reduction is done by throwing away all leaves in the deepest level.
The sorting is stopped in the second-deepest level where the nodes of
the Octree are now leaves. But, theoretically 7 levels still allow
128*128*128 > 2 Million
different RGB combinations or possible finest sub-cubes. So it can be
necessary to reduce the level of sort accuracy further until the Octree
remains small enough. But this may cause later a poor result of the
quantization, because all pixels which colors share a common leaf of
the Octree will have the same color in the resulting quantized image.
Thus, it is desirable to keep the accuracy level a high as possible and
a compromise between computational effort and quantize quality has to
be obtained.
In the second phase of the quantization the color table is computed.
For this purpose the Octree which was generated during the scanning
process has to be reduced further until the number of leaves is lower
(or equal) than the specified maximum of colors. Compared to the
reduction during the scanning process, which is done only "level-wise",
the final reduction is performed in a more complicated way. It is
taken into account how many pixels belong to each node in the Octree.
The node with the minimum pixel count is searched. It's sub-trees are
discarded and it becomes a leaf. This is repeated until the number of
leaves is low enough. Then for each leaf the average color values are
computed: The sums of the red, green and blue values are divided by the
number of pixels. These averaged RGB values are replaced by the near‐
est integers and the resulting numbers are taken as entry in the color
table.
After the color table is generated the final stage is done. All pixels
in the images are sorted again using the -- now reduced -- Octree until
a leaf is reached. Then the pixel is mapped to the respective entry in
the color table. For all pixels which were used during the scanning
process a leaf in the reduced Octree exists. This leaf represents a
cube in the color space that contains the color of the pixel (beside
other colors depending on the level of the leaf).
In some circumstances it is useful to be able to map also images which
were not scanned previously. If such an "unknown" image is mapped pix‐
els may occur which have colors that are not represented by any leaf in
the Octree. These "unknown" colors are located in cubes which were not
considered previously. The sorting process is extended to handle also
such situations. In all cases the sorting starts regularly and it is
evaluated in which sub-cube the color of a pixel belongs. If a node
for this sub-cube exists in the Octree the search is continued regu‐
larly. If no node exists -- this means no scanned pixel had a color
which belonged to the same sub-cube -- an extra procedure is started.
For all sub-nodes that exist the distance in the 3-dimensional color
space between the color of the pixel and the average color of this sub-
node is computed (NOTE: In ppm2fli the maximum norm is used as the dis‐
tance, not the geometric distance). Then the search is continued with
the sub-node that represents the lowest distance. The procedure is
repeated until a leaf is reached. Like in the regular case the pixel
is mapped to the color of this leaf. If this extra search procedure is
necessary for some pixels, ppm2fli counts them and writes in a message
how many "non-fitting" pixels were found.
Controlling the quantization
In the following we assume that the maximum number of colors was deter‐
mined previously and the numcolors parameter is kept fix. Usually this
value is 256 anyway. Then the program has two parameters by which the
selection of the output color table can be controlled. These are the
nodelimit and the reducelevels parameters. The first one sets the max‐
imum number of nodes in the second-finest level. Like described above
the level of the Octree is reduced when during the scanning of the
input images this value is exceeded. With a deeper level in the
Octree, finer nuances between output colors are possible. This is use‐
ful when smooth transitions are present in the input images. Typi‐
cally, steps occur in such transitions due to the quantization. These
steps may be reduced when a larger nodelimit is used and the final
Octree is one level deeper. The depth of the Octree can be watched
using the `-vv' option. After the scanning of each file a lines occurs
which look like
Octree - node count (5): 1 8 23 66 228 999 0 0 0
The number in the brackets indicates the deepest level. Then follow
the number of nodes in each level from 0 to 8. The zero level contains
only the main node of the Octree and the first number is always one.
Recommended values of nodelimit are between one time and four times the
numcolors value. Higher values increase the computational effort and
slow down the scanning process.
The reducelevels parameter controls the final reduction of the Octree.
It determines the number of levels in which the search for the node
with the minimum pixel count is done. When reducelevels is zero, the
reduction is done only in the finest level. Therefore, the resulting
Octree contains leaves only in two different levels: the deepest and
the second-deepest.
The influence of this parameter on the color table becomes clear in the
following example: Assume a 640x480 image which shows a small, bright-
red object in front of a green dominated background. The small object
consists of only 1000 pixels. The green and blue components of the
colors in this object are zero. The red values rage from 150 to 250.
In the green background the red and blue values are zero. The green
values rage from 1 to 255. For each of this green values much more
than 1000 pixels can be found in the image (which has more than 300,000
pixels). Thus, we have a total of
101+255=356
different colors in the image. We assume that the nodelimit parameter
is larger than 356. Then the Octree has a leaf for each color after
the scanning. Until now no reduction was necessary. But now 100
leaves have to be removed from the Octree. By default, the nodes in
all levels are searched for the node with minimum pixel count. This
will be always a node which represents a red color, because the 1000
red pixels can't stand the statistical superiority of the green back‐
ground. What happens is that all red pixels are going to receive the
same (averaged) red by the quantization and the green nuances in the
background are resolved in an optimal way.
When the reduction is limited to the finest level, the number of leaves
that represent red colors can only be reduced by a factor of 8. From
101 leaves 13 will remain and the same number of entries in the color
table is occupied by red shades. Thus, the red object doesn't look
totally poor like in the first case. Now the green background has to
be represented by 12 entries less. The preference of shades with
higher pixel count is limited with a zero reducelevels value. By
default, the nodes in all levels may be turned to leaves, which results
in the strongest preference of dominant shades in the color table.
Also the statistic of the reduced Octree can be watched using the `-vv'
option. When the scanning is finished a lines occurs which look like
Octree - leaf count (4): 0 4 14 53 184 0 0 0 0
The number in the brackets indicates the deepest leaf level. This is
followed by the number of leaves in each level from 0 to 8.
In general, the effect of changes of the above mentioned parameters
depends strongly on the input data. To get optimal results, some
experiments with different values should be done.
FLI/FLC optimization for special players
One special feature of ppm2fli is activated by the `-D' option. By
that the program generates optimized animations for players which use
double buffering. A double-buffer player uses two buffers for the dis‐
play. When playing an animation both buffers have to be updated sepa‐
rately. For this a the player needs the update information with
respect to the frame which was located previously in the same buffer.
This frame is not the last one, which was processed in exactly the
other buffer, but the frame before the last. Ordinary FLI/FLC anima‐
tions contain in each frame the update information with respect to the
previous frame. Thus a double buffer player has to combine somehow the
updates of two FLI frames to make the changes in one of the buffers.
This becomes much easier when the FLI already contains this information
in each frame. Still the animation can be played with a regular
player. In this case only some unnecessary updates are done which may
slow down the animation.
A second special feature is activated by the `-N' option. Then the
frames of the generated FLI animation contain the update information
with respect to the last and the following frame. This allows the ani‐
mation to be played in reverse direction. For instance with the XAnim
player the play direction can be altered interactively. This may help
when visualizing and analyzing some unsteady phenomena or just can be
used as a fancy effect. Together with the utility unflick an existing
FLI animation can easily be converted to be suitable for reverse play.
SEE ALSOfbm(1), unflick(1), and ppm(5)REFERENCES
The quantization is based on the Octree algorithm introduced by Michael
Gervautz and Werner Purgathofer (Technical University Vienna, Austria).
It is described in the article `A Simple Method for Color Quantization:
Octree Quantization' published in Graphic Gems edited by Andrew Glass‐
ner pp. 287 ff.
ACKNOWLEDGMENTS
The special feature, to generated FLI animations which can be played
forward and backward, is based on contributions and ideas of Marc
Podlipec (podlipec@wellfleet.com). This manual page includes parts
form that one of fbm2fli which was assembled by R. P. C. Rodgers
(rodgers@nlm.nih.gov).
AUTHOR
Klaus Ehrenfried (klaus.ehrenfried@tu-berlin.de). Release of January
2002.
http://vento.pi.tu-berlin.de/fli.html
11 January 2002 PPM2FLI(1)
