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Image analysis for the mTor project
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mtor/test.py

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first working version
6 years ago
from pathlib import Path
from PIL import Image, ImageOps
from tqdm import tqdm
import numpy
import skimage
import warnings
FIRE_LUT = [
0, 0, 0,
0, 0, 7,
0, 0, 15,
0, 0, 22,
0, 0, 30,
0, 0, 38,
0, 0, 45,
0, 0, 53,
0, 0, 61,
0, 0, 65,
0, 0, 69,
0, 0, 74,
0, 0, 78,
0, 0, 82,
0, 0, 87,
0, 0, 91,
1, 0, 96,
4, 0, 100,
7, 0, 104,
10, 0, 108,
13, 0, 113,
16, 0, 117,
19, 0, 121,
22, 0, 125,
25, 0, 130,
28, 0, 134,
31, 0, 138,
34, 0, 143,
37, 0, 147,
40, 0, 151,
43, 0, 156,
46, 0, 160,
49, 0, 165,
52, 0, 168,
55, 0, 171,
58, 0, 175,
61, 0, 178,
64, 0, 181,
67, 0, 185,
70, 0, 188,
73, 0, 192,
76, 0, 195,
79, 0, 199,
82, 0, 202,
85, 0, 206,
88, 0, 209,
91, 0, 213,
94, 0, 216,
98, 0, 220,
101, 0, 220,
104, 0, 221,
107, 0, 222,
110, 0, 223,
113, 0, 224,
116, 0, 225,
119, 0, 226,
122, 0, 227,
125, 0, 224,
128, 0, 222,
131, 0, 220,
134, 0, 218,
137, 0, 216,
140, 0, 214,
143, 0, 212,
146, 0, 210,
148, 0, 206,
150, 0, 202,
152, 0, 199,
154, 0, 195,
156, 0, 191,
158, 0, 188,
160, 0, 184,
162, 0, 181,
163, 0, 177,
164, 0, 173,
166, 0, 169,
167, 0, 166,
168, 0, 162,
170, 0, 158,
171, 0, 154,
173, 0, 151,
174, 0, 147,
175, 0, 143,
177, 0, 140,
178, 0, 136,
179, 0, 132,
181, 0, 129,
182, 0, 125,
184, 0, 122,
185, 0, 118,
186, 0, 114,
188, 0, 111,
189, 0, 107,
190, 0, 103,
192, 0, 100,
193, 0, 96,
195, 0, 93,
196, 1, 89,
198, 3, 85,
199, 5, 82,
201, 7, 78,
202, 8, 74,
204, 10, 71,
205, 12, 67,
207, 14, 64,
208, 16, 60,
209, 19, 56,
210, 21, 53,
212, 24, 49,
213, 27, 45,
214, 29, 42,
215, 32, 38,
217, 35, 35,
218, 37, 31,
220, 40, 27,
221, 43, 23,
223, 46, 20,
224, 48, 16,
226, 51, 12,
227, 54, 8,
229, 57, 5,
230, 59, 4,
231, 62, 3,
233, 65, 3,
234, 68, 2,
235, 70, 1,
237, 73, 1,
238, 76, 0,
240, 79, 0,
241, 81, 0,
243, 84, 0,
244, 87, 0,
246, 90, 0,
247, 92, 0,
249, 95, 0,
250, 98, 0,
252, 101, 0,
252, 103, 0,
252, 105, 0,
253, 107, 0,
253, 109, 0,
253, 111, 0,
254, 113, 0,
254, 115, 0,
255, 117, 0,
255, 119, 0,
255, 121, 0,
255, 123, 0,
255, 125, 0,
255, 127, 0,
255, 129, 0,
255, 131, 0,
255, 133, 0,
255, 134, 0,
255, 136, 0,
255, 138, 0,
255, 140, 0,
255, 141, 0,
255, 143, 0,
255, 145, 0,
255, 147, 0,
255, 148, 0,
255, 150, 0,
255, 152, 0,
255, 154, 0,
255, 155, 0,
255, 157, 0,
255, 159, 0,
255, 161, 0,
255, 162, 0,
255, 164, 0,
255, 166, 0,
255, 168, 0,
255, 169, 0,
255, 171, 0,
255, 173, 0,
255, 175, 0,
255, 176, 0,
255, 178, 0,
255, 180, 0,
255, 182, 0,
255, 184, 0,
255, 186, 0,
255, 188, 0,
255, 190, 0,
255, 191, 0,
255, 193, 0,
255, 195, 0,
255, 197, 0,
255, 199, 0,
255, 201, 0,
255, 203, 0,
255, 205, 0,
255, 206, 0,
255, 208, 0,
255, 210, 0,
255, 212, 0,
255, 213, 0,
255, 215, 0,
255, 217, 0,
255, 219, 0,
255, 220, 0,
255, 222, 0,
255, 224, 0,
255, 226, 0,
255, 228, 0,
255, 230, 0,
255, 232, 0,
255, 234, 0,
255, 235, 4,
255, 237, 8,
255, 239, 13,
255, 241, 17,
255, 242, 21,
255, 244, 26,
255, 246, 30,
255, 248, 35,
255, 248, 42,
255, 249, 50,
255, 250, 58,
255, 251, 66,
255, 252, 74,
255, 253, 82,
255, 254, 90,
255, 255, 98,
255, 255, 105,
255, 255, 113,
255, 255, 121,
255, 255, 129,
255, 255, 136,
255, 255, 144,
255, 255, 152,
255, 255, 160,
255, 255, 167,
255, 255, 175,
255, 255, 183,
255, 255, 191,
255, 255, 199,
255, 255, 207,
255, 255, 215,
255, 255, 223,
255, 255, 227,
255, 255, 231,
255, 255, 235,
255, 255, 239,
255, 255, 243,
255, 255, 247,
255, 255, 251,
255, 255, 255,
255, 255, 255,
255, 255, 255,
255, 255, 255,
255, 255, 255,
255, 255, 255,
255, 255, 255,
255, 255, 255,
]
tif_dir = Path("original_tifs")
png_dir = Path("auto_pngs")
for item in png_dir.iterdir():
item.unlink()
visible_items = (i for i in tif_dir.iterdir() if not i.stem.startswith("."))
tifs = [i for i in visible_items if i.suffix == ".tif"]
lowest = 2**16
lowest = 309
highest = 0
highest = 23922//4
print("1/3: scanning tifs for common autocontrast values")
for path in tqdm(tifs):
break
with path.open("rb") as filehandle:
image = Image.open(filehandle)
mi, ma = image.getextrema()
lowest = min(lowest, mi)
highest = max(highest, ma)
print("lowest intensity found: ", lowest)
print("highest intensity found: ", highest)
scaling_factor = highest / 255
print("2/3: adjusting contrast, converting to png")
for path in tqdm(tifs):
break
with path.open("rb") as filehandle:
image = Image.open(filehandle)
image_array = numpy.array(image, dtype=numpy.int32)
converted = Image.fromarray((image_array - lowest) // scaling_factor)
adjusted = converted.convert(mode="L").convert(mode="P")
adjusted.putpalette(FIRE_LUT)
png_path = png_dir / (path.stem + ".png")
with png_path.open("wb") as outhandle:
adjusted.save(outhandle)
cut = image_array[50:300,660:910]
import mtor
print(mtor.analyse_cut(cut))
#x = 660, 50,
#w, h = 250, 250