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Elphel
image-compression
Commits
625e9d15
Commit
625e9d15
authored
Jun 23, 2022
by
Bryce Hepner
Browse files
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Made some changes, have to rerun everything
parent
00cfa297
Changes
3
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Showing
3 changed files
with
80 additions
and
31 deletions
+80
-31
FullTester.ipynb
FullTester.ipynb
+62
-21
WorkingPyDemo.py
WorkingPyDemo.py
+18
-10
first_dic.npy
first_dic.npy
+0
-0
No files found.
FullTester.ipynb
View file @
625e9d15
...
@@ -2,7 +2,7 @@
...
@@ -2,7 +2,7 @@
"cells": [
"cells": [
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count":
1
,
"execution_count":
2
,
"metadata": {},
"metadata": {},
"outputs": [],
"outputs": [],
"source": [
"source": [
...
@@ -15,7 +15,7 @@
...
@@ -15,7 +15,7 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 1
5
,
"execution_count": 1
9
,
"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
...
@@ -51,12 +51,29 @@
...
@@ -51,12 +51,29 @@
" file_sizes_old.append((os.path.getsize(images[i])))\n",
" file_sizes_old.append((os.path.getsize(images[i])))\n",
"file_sizes_new.append(os.path.getsize(\"first_dic.npy\"))\n",
"file_sizes_new.append(os.path.getsize(\"first_dic.npy\"))\n",
"print(len(newnamesforlater))\n",
"print(len(newnamesforlater))\n",
"print(np.sum(file_sizes_new)/np.sum(file_sizes_old))"
"print(np.sum(file_sizes_new)/np.sum(file_sizes_old))
\n
"
]
]
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 16,
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 260942, 231302]\n"
]
}
],
"source": [
"print(file_sizes_new)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
...
@@ -70,12 +87,12 @@
...
@@ -70,12 +87,12 @@
"source": [
"source": [
"pngsizes = []\n",
"pngsizes = []\n",
"for i, filename in enumerate(images):\n",
"for i, filename in enumerate(images):\n",
" newimage = Image.open(filename)\n",
"
#
newimage = Image.open(filename)\n",
" newimage = np.array(newimage)\n",
"
#
newimage = np.array(newimage)\n",
" newimage = newimage[1:]\n",
"
#
newimage = newimage[1:]\n",
" with open(newnamesforlater[i][:-4] + \".png\", 'wb') as f:\n",
"
#
with open(newnamesforlater[i][:-4] + \".png\", 'wb') as f:\n",
" writer = png.Writer(newimage.shape[1], newimage.shape[0], greyscale=True, bitdepth=16)\n",
"
#
writer = png.Writer(newimage.shape[1], newimage.shape[0], greyscale=True, bitdepth=16)\n",
" writer.write(f, newimage)\n",
"
#
writer.write(f, newimage)\n",
" # imageio.imwrite(newnamesforlater[i][:-4] + \".png\", newimage)\n",
" # imageio.imwrite(newnamesforlater[i][:-4] + \".png\", newimage)\n",
" # newimage.close()\n",
" # newimage.close()\n",
" pngsizes.append(os.path.getsize(newnamesforlater[i][:-4] + \".png\"))\n",
" pngsizes.append(os.path.getsize(newnamesforlater[i][:-4] + \".png\"))\n",
...
@@ -118,7 +135,7 @@
...
@@ -118,7 +135,7 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count":
17
,
"execution_count":
5
,
"metadata": {},
"metadata": {},
"outputs": [],
"outputs": [],
"source": [
"source": [
...
@@ -157,7 +174,7 @@
...
@@ -157,7 +174,7 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count":
19
,
"execution_count":
6
,
"metadata": {},
"metadata": {},
"outputs": [],
"outputs": [],
"source": [
"source": [
...
@@ -167,14 +184,14 @@
...
@@ -167,14 +184,14 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count":
20
,
"execution_count":
9
,
"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
"name": "stdout",
"name": "stdout",
"output_type": "stream",
"output_type": "stream",
"text": [
"text": [
"0.61
85872808807661
\n"
"0.61
77078151903203
\n"
]
]
}
}
],
],
...
@@ -182,6 +199,9 @@
...
@@ -182,6 +199,9 @@
"lwz_sizes = []\n",
"lwz_sizes = []\n",
"for i, filename in enumerate(images):\n",
"for i, filename in enumerate(images):\n",
" newimage = Image.open(filename)\n",
" newimage = Image.open(filename)\n",
" newimage = np.array(newimage)\n",
" newimage = newimage[1:]\n",
" newimage = Image.fromarray(newimage)\n",
" newimage.save(newnamesforlater[i][:-4]+ \"lzw\" + \".tiff\", compression='tiff_lzw', tiffinfo={317: 2})\n",
" newimage.save(newnamesforlater[i][:-4]+ \"lzw\" + \".tiff\", compression='tiff_lzw', tiffinfo={317: 2})\n",
"\n",
"\n",
" lwz_sizes.append(os.path.getsize(newnamesforlater[i][:-4]+ \"lzw\" + \".tiff\"))\n",
" lwz_sizes.append(os.path.getsize(newnamesforlater[i][:-4]+ \"lzw\" + \".tiff\"))\n",
...
@@ -190,7 +210,24 @@
...
@@ -190,7 +210,24 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 22,
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.3575310312509913\n"
]
}
],
"source": [
"print((np.sum(lwz_sizes) - np.sum(file_sizes_new))/np.sum(lwz_sizes))"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
...
@@ -240,15 +277,18 @@
...
@@ -240,15 +277,18 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count":
28
,
"execution_count":
1
,
"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
{
"name": "stdout",
"ename": "NameError",
"output_type": "stream",
"evalue": "name 'all_image_extractor' is not defined",
"text": [
"output_type": "error",
"1178\n",
"traceback": [
"1178\n"
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m/home/bryce/git/master/FullTester.ipynb Cell 13'\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> <a href='vscode-notebook-cell:/home/bryce/git/master/FullTester.ipynb#ch0000012?line=0'>1</a>\u001b[0m all_files \u001b[39m=\u001b[39m all_image_extractor(scenes)\n\u001b[1;32m <a href='vscode-notebook-cell:/home/bryce/git/master/FullTester.ipynb#ch0000012?line=1'>2</a>\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39mlen\u001b[39m(all_files))\n\u001b[1;32m <a href='vscode-notebook-cell:/home/bryce/git/master/FullTester.ipynb#ch0000012?line=2'>3</a>\u001b[0m \u001b[39mfor\u001b[39;00m i, item \u001b[39min\u001b[39;00m \u001b[39menumerate\u001b[39m(all_files):\n\u001b[1;32m <a href='vscode-notebook-cell:/home/bryce/git/master/FullTester.ipynb#ch0000012?line=3'>4</a>\u001b[0m \u001b[39m# print(item[-18:])\u001b[39;00m\n",
"\u001b[0;31mNameError\u001b[0m: name 'all_image_extractor' is not defined"
]
]
}
}
],
],
...
@@ -257,6 +297,7 @@
...
@@ -257,6 +297,7 @@
"print(len(all_files))\n",
"print(len(all_files))\n",
"for i, item in enumerate(all_files):\n",
"for i, item in enumerate(all_files):\n",
" # print(item[-18:])\n",
" # print(item[-18:])\n",
" print(item[-4:])\n",
" if item[-4:] == \"..png\":\n",
" if item[-4:] == \"..png\":\n",
" os.remove(item)\n",
" os.remove(item)\n",
"scenes = file_extractor(folder_name)\n",
"scenes = file_extractor(folder_name)\n",
...
...
WorkingPyDemo.py
View file @
625e9d15
...
@@ -9,6 +9,7 @@ from sklearn.neighbors import KernelDensity
...
@@ -9,6 +9,7 @@ from sklearn.neighbors import KernelDensity
from
collections
import
Counter
from
collections
import
Counter
import
numpy.linalg
as
la
import
numpy.linalg
as
la
from
time
import
time
from
time
import
time
from
time
import
sleep
import
tifffile
as
tiff
import
tifffile
as
tiff
folder_name
=
"images"
folder_name
=
"images"
outputlocation
=
""
outputlocation
=
""
...
@@ -506,11 +507,12 @@ if __name__ == "__main__":
...
@@ -506,11 +507,12 @@ if __name__ == "__main__":
scenes
=
file_extractor
(
folder_name
)
scenes
=
file_extractor
(
folder_name
)
images
=
image_extractor
(
scenes
)
images
=
image_extractor
(
scenes
)
newnamesforlater
=
[]
newnamesforlater
=
[]
#
list_dic, bins = make_dictionary(images, 4, False)
list_dic
,
bins
=
make_dictionary
(
images
,
4
,
False
)
file_sizes_new
=
[]
file_sizes_new
=
[]
file_sizes_old
=
[]
file_sizes_old
=
[]
# list_dic = np.load("first_dic.npy", allow_pickle="TRUE")
# np.save("first_dic.npy", list_dic)
bins
=
[
21
,
32
,
48
]
np
.
save
(
"first_dic.npy"
,
list_dic
)
for
i
in
range
(
len
(
images
)):
for
i
in
range
(
len
(
images
)):
image
,
new_error
,
diff
=
huffman
(
images
[
i
],
4
,
False
)
image
,
new_error
,
diff
=
huffman
(
images
[
i
],
4
,
False
)
encoded_string
=
encoder
(
new_error
,
list_dic
,
diff
,
bins
)
encoded_string
=
encoder
(
new_error
,
list_dic
,
diff
,
bins
)
...
@@ -525,16 +527,22 @@ if __name__ == "__main__":
...
@@ -525,16 +527,22 @@ if __name__ == "__main__":
f
.
write
(
inletters
)
f
.
write
(
inletters
)
file_sizes_new
.
append
((
os
.
path
.
getsize
(
newname
+
"_Compressed.txt"
)))
file_sizes_new
.
append
((
os
.
path
.
getsize
(
newname
+
"_Compressed.txt"
)))
file_sizes_old
.
append
((
os
.
path
.
getsize
(
images
[
i
])))
file_sizes_old
.
append
((
os
.
path
.
getsize
(
images
[
i
])))
sleep
(
5
)
if
i
%
50
==
0
:
print
(
i
)
sleep
(
20
)
file_sizes_new
.
append
(
os
.
path
.
getsize
(
"first_dic.npy"
))
file_sizes_new
.
append
(
os
.
path
.
getsize
(
"first_dic.npy"
))
print
(
np
.
sum
(
file_sizes_new
)
/
np
.
sum
(
file_sizes_old
))
print
(
np
.
sum
(
file_sizes_new
)
/
np
.
sum
(
file_sizes_old
))
#
list_dic = np.load("first_dic.npy", allow_pickle="TRUE")
list_dic
=
np
.
load
(
"first_dic.npy"
,
allow_pickle
=
"TRUE"
)
#
bins = [21,32,48]
bins
=
[
21
,
32
,
48
]
# starttime = time()
# starttime = time()
# for i,item in enumerate(newnamesforlater[0:6]):
for
i
,
item
in
enumerate
(
newnamesforlater
[
2
:
5
]):
# image, new_error, diff = huffman(images[i], 4, False)
print
(
item
)
# encoded_string2 = bytes_to_bitstring(read_from_file(item))
image
,
new_error
,
diff
=
huffman
(
images
[
i
],
4
,
False
)
# reconstruct_image = decoder(encoded_string2, list_dic, bins, False)
encoded_string2
=
bytes_to_bitstring
(
read_from_file
(
item
))
# print(np.allclose(image, reconstruct_image))
reconstruct_image
=
decoder
(
encoded_string2
,
list_dic
,
bins
,
False
)
print
(
np
.
allclose
(
image
,
reconstruct_image
))
# text_to_tiff("images/1626033496_437803/1626033496_437803_3._Compressed.txt", list_dic, bins)
# text_to_tiff("images/1626033496_437803/1626033496_437803_3._Compressed.txt", list_dic, bins)
# original_image = Image.open("images/1626033496_437803/1626033496_437803_3.tiff")
# original_image = Image.open("images/1626033496_437803/1626033496_437803_3.tiff")
# original_image = np.array(original_image)[1:]
# original_image = np.array(original_image)[1:]
...
...
first_dic.npy
View file @
625e9d15
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