𖣠⚪✤ИNᗱᗴⵙↀᗩᴥᕤᕦ𖤞ᙏᴥⓄꗳᔓᔕИNᗩᴥ✤𖥟ᗱᗴᑐᑕИNᗩ✤ᔓᔕⵙↀ𖡦ИNᗩᗱᗴↀⵙᙁᑐᑕᑎᗱᗴ𖥞⚪𔗢⚪🞋⚪𔗢⚪𖥞ᗱᗴᑎᑐᑕᙁⵙↀᗱᗴᗩИN𖡦ↀⵙᔓᔕ✤ᗩИNᑐᑕᗱᗴ𖥟✤ᴥᗩИNᔓᔕꗳⓄᴥᙏ𖤞ᕤᕦᴥᗩↀⵙᗱᗴИN✤⚪𖣠 

   
   
import cv2,OpenEXR,Imath
import numpy asߦᙏᑎИNⵙИNᑎᙏߦ
from edt import edt
ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ='ꓨИꟼ..𖣠⚪ᗱᗴᕤᕦᗩᙏⵙ𖣓✤ᔓᔕᗱᗴ✤⚪𔗢🞋𔗢⚪✤ᗱᗴᔓᔕ✤𖣓ⵙᙏᗩᕤᕦᗱᗴ⚪𖣠..PNG'
ⵙᗱᗴᕤᕦᗩᙏꖴ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꖴᙏᗩᕤᕦᗱᗴⵙ=cv2.imdecode(ߦᙏᑎИNⵙИNᑎᙏߦ.fromfile(ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ,ߦᙏᑎИNⵙИNᑎᙏߦⵙ.uint8),cv2.IMREAD_COLOR)
ⵙᗱᗴᙁᗩᑐᑕᔓᔕᗩᴥᕤᕦO𖧷ↀᗱᗴ𖧷ᗱᗴᐱИNOᑐᑕᗱᗴᕤᕦᗩᙏꖴ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꖴᙏᗩᕤᕦᗱᗴᑐᑕOИNᐱᗱᗴ𖧷ᗱᗴↀ𖧷Oᕤᕦᴥᗩᔓᔕᑐᑕᗩᙁᗱᗴⵙ=cv2.cvtColor(ⵙᗱᗴᕤᕦᗩᙏꖴ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꖴᙏᗩᕤᕦᗱᗴⵙ,cv2.COLOR_BGR2GRAY)
ⵙИNᴥᑎ𖧷ᗱᗴᴥⵙⵙᴥᗱᗴ𖧷ᑎᴥИN,ⵙↀᙁOᔓᔕᗱᗴᴥ𖧷𖧷ᴥᗱᗴᔓᔕOᙁↀⵙ=cv2.threshold(ⵙᗱᗴᙁᗩᑐᑕᔓᔕᗩᴥᕤᕦO𖧷ↀᗱᗴ𖧷ᗱᗴᐱИNOᑐᑕᗱᗴᕤᕦᗩᙏꖴ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꖴᙏᗩᕤᕦᗱᗴᑐᑕOИNᐱᗱᗴ𖧷ᗱᗴↀ𖧷Oᕤᕦᴥᗩᔓᔕᑐᑕᗩᙁᗱᗴⵙ,127,255,cv2.THRESH_BINARY)
ⵙᴥᗱᗴ8ᙏᑎИNᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁИNᑎᙏ8ᗱᗴᴥⵙ,ⵙᔓᔕᙁᗱᗴᑐᑕᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴᑐᑕᗱᗴᙁᔓᔕⵙ,ⵙᔓᔕᑐᑕꖴ𖧷ᔓᔕꖴ𖧷𖧷ᔓᔕᔓᔕᙁᗱᗴᑐᑕᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴᑐᑕᗱᗴᙁᔓᔕᔓᔕ𖧷𖧷ꖴᔓᔕ𖧷ꖴᑐᑕᔓᔕⵙ,ⵙᔓᔕↀꖴO𖧷ИNᗱᗴᑐᑕᔓᔕᙁᗱᗴᑐᑕᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴᑐᑕᗱᗴᙁᔓᔕᑐᑕᗱᗴИN𖧷Oꖴↀᔓᔕⵙ=cv2.connectedComponentsWithStats(ⵙↀᙁOᔓᔕᗱᗴᴥ𖧷𖧷ᴥᗱᗴᔓᔕOᙁↀⵙ)
ⵙᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴⵙ=ߦᙏᑎИNⵙИNᑎᙏߦ.zeros_like(ⵙᔓᔕᙁᗱᗴᑐᑕᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴᑐᑕᗱᗴᙁᔓᔕⵙ)
for i in range(1,ⵙᴥᗱᗴ8ᙏᑎИNᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁИNᑎᙏ8ᗱᗴᴥⵙ):ⵙᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴⵙ[ⵙᔓᔕᙁᗱᗴᑐᑕᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴᑐᑕᗱᗴᙁᔓᔕⵙ==i]=i
ⵙᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀИNᗩᗱᗴↀꖴᙁᑐᑕᑎᗱᗴⵙⵙᗱᗴᑎᑐᑕᙁꖴↀᗱᗴᗩИNↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏⵙ=edt(ⵙᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴⵙ.astype(ߦᙏᑎИNⵙИNᑎᙏߦⵙ.float32))
ⵙᔓᔕᗱᗴИNᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁИNᗱᗴᔓᔕⵙ='·'
ⵙᴥO𖧷ᑐᑕᗩꗳⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀⵙ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦⵙᙏᑎᙏꖴꕤᗩᙏⵙⵙᙏᗩꕤꖴᙏᑎᙏⵙᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ⵙↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙꗳᗩᑐᑕ𖧷Oᴥⵙ=2/4.793447 # 2/5.5625 # 1/27**1/ⵙߦᙏᑎИNⵙⵙИNᑎᙏߦⵙ.cbrt(2)
𖧷ᕤᕦꖴᗱᗴᗱᗴꖴᕤᕦ𖧷,𖧷ↀꖴᗯⵙⵙᗯꖴↀ𖧷=ⵙᗱᗴᕤᕦᗩᙏꖴ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꖴᙏᗩᕤᕦᗱᗴⵙ.shape[:2]
ⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀⵙ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦⵙᙏᑎᙏꖴꕤᗩᙏⵙⵙᙏᗩꕤꖴᙏᑎᙏⵙᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ⵙↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙ=int(max(𖧷ᕤᕦꖴᗱᗴᗱᗴꖴᕤᕦ𖧷,𖧷ↀꖴᗯⵙⵙᗯꖴↀ𖧷)*ⵙᴥO𖧷ᑐᑕᗩꗳⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀⵙ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦⵙᙏᑎᙏꖴꕤᗩᙏⵙⵙᙏᗩꕤꖴᙏᑎᙏⵙᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ⵙↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙꗳᗩᑐᑕ𖧷Oᴥⵙ)
ⵙↀᙁOᔓᔕᗱᗴᴥ𖧷𖧷ИNOᑐᑕⵙᙁᗱᗴꕤꖴߦⵙⵙߦꖴꕤᗱᗴᙁⵙᑐᑕOᑎИN𖧷𖧷ᴥᗱᗴᔓᔕOᙁↀⵙ=min(𖧷ᕤᕦꖴᗱᗴᗱᗴꖴᕤᕦ𖧷,𖧷ↀꖴᗯⵙⵙᗯꖴↀ𖧷)*64
ⵙᗱᗴᕤᕦᗩᙏꖴᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏꖴᙏᗩᕤᕦᗱᗴⵙ=ߦᙏᑎИNⵙИNᑎᙏߦ.zeros_like(ⵙᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴⵙ,dtype=ߦᙏᑎИNⵙИNᑎᙏߦⵙ.float32)
if ⵙᔓᔕᗱᗴИNᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁИNᗱᗴᔓᔕⵙ=='ⵔ':
for i in range(1,ⵙᴥᗱᗴ8ᙏᑎИNᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁИNᑎᙏ8ᗱᗴᴥⵙ):
𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌=(ⵙᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴⵙ==i)
ⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦᙁᗱᗴᑐᑕↀᗱᗴᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁᗱᗴↀᑐᑕᗱᗴᙁᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙ=ⵙᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀИNᗩᗱᗴↀꖴᙁᑐᑕᑎᗱᗴⵙⵙᗱᗴᑎᑐᑕᙁꖴↀᗱᗴᗩИNↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏⵙ[𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌]
ⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀᙏᑎᙏꖴꕤᗩᙏ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦᔓᔕᙁᗱᗴᑐᑕↀᗱᗴᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁᗱᗴↀᑐᑕᗱᗴᙁᔓᔕᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ᙏᗩꕤꖴᙏᑎᙏↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙ=ߦᙏᑎИNⵙИNᑎᙏߦ.max(ⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦᙁᗱᗴᑐᑕↀᗱᗴᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁᗱᗴↀᑐᑕᗱᗴᙁᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙ)
ⵙᗱᗴᕤᕦᗩᙏꖴᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏꖴᙏᗩᕤᕦᗱᗴⵙ[𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌]=ߦᙏᑎИNⵙИNᑎᙏߦ.clip(ⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦᙁᗱᗴᑐᑕↀᗱᗴᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁᗱᗴↀᑐᑕᗱᗴᙁᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙ,0,ⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀⵙ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦⵙᙏᑎᙏꖴꕤᗩᙏⵙⵙᙏᗩꕤꖴᙏᑎᙏⵙᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ⵙↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙ)/ⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀⵙ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦⵙᙏᑎᙏꖴꕤᗩᙏⵙⵙᙏᗩꕤꖴᙏᑎᙏⵙᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ⵙↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙ
elif ⵙᔓᔕᗱᗴИNᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁИNᗱᗴᔓᔕⵙ=="·":
for i in range(1,ⵙᴥᗱᗴ8ᙏᑎИNᙁᗱᗴ8ᗩᙁⵙⵙᙁᗩ8ᗱᗴᙁИNᑎᙏ8ᗱᗴᴥⵙ):
𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌=(ⵙᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴⵙ==i)
ifߦᙏᑎИNⵙИNᑎᙏߦ.sum(𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌)>ⵙↀᙁOᔓᔕᗱᗴᴥ𖧷𖧷ИNOᑐᑕⵙᙁᗱᗴꕤꖴߦⵙⵙߦꖴꕤᗱᗴᙁⵙᑐᑕOᑎИN𖧷𖧷ᴥᗱᗴᔓᔕOᙁↀⵙ:
ⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦↀᗱᗴߦꖴᙁᑐᑕⵙⵙᑐᑕᙁꖴߦᗱᗴↀᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙ=ߦᙏᑎИNⵙИNᑎᙏߦ.clip(ⵙᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀИNᗩᗱᗴↀꖴᙁᑐᑕᑎᗱᗴⵙⵙᗱᗴᑎᑐᑕᙁꖴↀᗱᗴᗩИNↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏⵙ[𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌]/ߦᙏᑎИNⵙИNᑎᙏߦ.max(ⵙᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀИNᗩᗱᗴↀꖴᙁᑐᑕᑎᗱᗴⵙⵙᗱᗴᑎᑐᑕᙁꖴↀᗱᗴᗩИNↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏⵙ[𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌]),0,ⵙᴥO𖧷ᑐᑕᗩꗳⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀⵙ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦⵙᙏᑎᙏꖴꕤᗩᙏⵙⵙᙏᗩꕤꖴᙏᑎᙏⵙᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ⵙↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙꗳᗩᑐᑕ𖧷Oᴥⵙ)
ⵙᗱᗴᕤᕦᗩᙏꖴᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏꖴᙏᗩᕤᕦᗱᗴⵙ[𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌]=cv2.normalize(ⵙᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀ𖧷ИNᗱᗴꖴↀᗩᴥᕤᕦↀᗱᗴߦꖴᙁᑐᑕⵙⵙᑐᑕᙁꖴߦᗱᗴↀᕤᕦᴥᗩↀꖴᗱᗴИN𖧷ↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴⵙ[:,ߦᙏᑎИNⵙИNᑎᙏߦ.newaxis],None,0,1,cv2.NORM_MINMAX).flatten()
else:
ⵙᗱᗴᕤᕦᗩᙏꖴᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏꖴᙏᗩᕤᕦᗱᗴⵙ[𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌]=ⵙᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀИNᗩᗱᗴↀꖴᙁᑐᑕᑎᗱᗴⵙⵙᗱᗴᑎᑐᑕᙁꖴↀᗱᗴᗩИNↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏⵙ[𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌]/ߦᙏᑎИNⵙИNᑎᙏߦ.max(ⵙᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀИNᗩᗱᗴↀꖴᙁᑐᑕᑎᗱᗴⵙⵙᗱᗴᑎᑐᑕᙁꖴↀᗱᗴᗩИNↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏⵙ[𐊌ᔓᔕᗩᙏⵙⵙᙏᗩᔓᔕ𐊌])
ⵙᗱᗴᕤᕦᗩᙏꖴᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏ𖧷8𓃎·ⵙⵙ·𓃎8𖧷ᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏꖴᙏᗩᕤᕦᗱᗴⵙ=(ⵙᗱᗴᕤᕦᗩᙏꖴᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏꖴᙏᗩᕤᕦᗱᗴⵙ*65535).astype(ߦᙏᑎИNⵙИNᑎᙏߦⵙ.uint16)
def ⵙᴥꕤᗱᗴᗱᗴ𖧷ᗩᴥᗱᗴИNᗱᗴᕤᕦⵙⵙᕤᕦᗱᗴИNᗱᗴᴥᗩ𖧷ᗱᗴᗱᗴꕤᴥⵙ(ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳⵙⵙꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ,ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ):
if ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ.ndim==2:
𖧷ᕤᕦꖴᗱᗴᗱᗴꖴᕤᕦ𖧷,𖧷ↀꖴᗯⵙⵙᗯꖴↀ𖧷=ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ.shape
ⵙᙁᗱᗴИNᑐᑕߦᙁᗩⵙⵙᗩᙁߦᑐᑕᗩИNᗱᗴᙁⵙ=ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ/ߦᙏᑎИNⵙИNᑎᙏߦ.max(ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ)
ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ=ߦᙏᑎИNⵙИNᑎᙏߦ.stack((ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ,)*3+(ⵙᙁᗱᗴИNᑐᑕߦᙁᗩⵙⵙᗩᙁߦᑐᑕᗩИNᗱᗴᙁⵙ,),axis=-1)
elif ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ.ndim==3 and ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ.shape[2]==4:
𖧷ᕤᕦꖴᗱᗴᗱᗴꖴᕤᕦ𖧷,𖧷ↀꖴᗯⵙⵙᗯꖴↀ𖧷,ⵙᔓᔕᙁᗱᗴИNᑐᑕⵙⵙᑐᑕᗩИNᗱᗴᙁᔓᔕⵙ=ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ.shape
else:
raise ValueError("")
ⵙᗱᗴߦ𖧷ᙁᗱᗴꕤꖴߦⵙⵙߦꖴꕤᗱᗴᙁ𖧷ߦᗱᗴⵙ=Imath.PixelType(Imath.PixelType.FLOAT)
ⵙᴥᗱᗴↀᗩᗱᗴᗱᗴᗩↀᗱᗴᴥⵙ=OpenEXR.Header(𖧷ↀꖴᗯⵙⵙᗯꖴↀ𖧷,𖧷ᕤᕦꖴᗱᗴᗱᗴꖴᕤᕦ𖧷)
ⵙᴥᗱᗴↀᗩᗱᗴᗱᗴᗩↀᗱᗴᴥⵙ['ⵙᔓᔕᙁᗱᗴИNᗩᑐᑕⵙⵙᑐᑕᗩИNᗱᗴᙁᔓᔕⵙ']={
'R':Imath.Channel(ⵙᗱᗴߦ𖧷ᙁᗱᗴꕤꖴߦⵙⵙߦꖴꕤᗱᗴᙁ𖧷ߦᗱᗴⵙ),
'G':Imath.Channel(ⵙᗱᗴߦ𖧷ᙁᗱᗴꕤꖴߦⵙⵙߦꖴꕤᗱᗴᙁ𖧷ߦᗱᗴⵙ),
'B':Imath.Channel(ⵙᗱᗴߦ𖧷ᙁᗱᗴꕤꖴߦⵙⵙߦꖴꕤᗱᗴᙁ𖧷ߦᗱᗴⵙ),
'A':Imath.Channel(ⵙᗱᗴߦ𖧷ᙁᗱᗴꕤꖴߦⵙⵙߦꖴꕤᗱᗴᙁ𖧷ߦᗱᗴⵙ)
}
ⵙᗱᗴᙁꖴꗳ𖧷ᑎߦ𖧷OO𖧷ߦᑎ𖧷ꗳꖴᙁᗱᗴⵙ=OpenEXR.OutputFile(ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳⵙⵙꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ.encode('utf-8'),ⵙᴥᗱᗴↀᗩᗱᗴᗱᗴᗩↀᗱᗴᴥⵙ)
ⵙᗩ𖧷ᗩↀ𖧷ᗩᙁꗳⵙⵙꗳᙁᗩ𖧷ↀᗩ𖧷ᗩⵙ=ⵙᗩ𖧷ᗩↀⵙⵙↀᗩ𖧷ᗩⵙ.reshape(𖧷ᕤᕦꖴᗱᗴᗱᗴꖴᕤᕦ𖧷*𖧷ↀꖴᗯⵙⵙᗯꖴↀ𖧷,4)
ⵙᗱᗴᙁꖴꗳ𖧷ᑎߦ𖧷OO𖧷ߦᑎ𖧷ꗳꖴᙁᗱᗴⵙ.writePixels({
'R':ⵙᗩ𖧷ᗩↀ𖧷ᗩᙁꗳⵙⵙꗳᙁᗩ𖧷ↀᗩ𖧷ᗩⵙ[:,0].tobytes(),
'G':ⵙᗩ𖧷ᗩↀ𖧷ᗩᙁꗳⵙⵙꗳᙁᗩ𖧷ↀᗩ𖧷ᗩⵙ[:,1].tobytes(),
'B':ⵙᗩ𖧷ᗩↀ𖧷ᗩᙁꗳⵙⵙꗳᙁᗩ𖧷ↀᗩ𖧷ᗩⵙ[:,2].tobytes(),
'A':ⵙᗩ𖧷ᗩↀ𖧷ᗩᙁꗳⵙⵙꗳᙁᗩ𖧷ↀᗩ𖧷ᗩⵙ[:,3].tobytes()
})
ⵙᴥꕤᗱᗴᗱᗴ𖧷ᗩᴥᗱᗴИNᗱᗴᕤᕦⵙⵙᕤᕦᗱᗴИNᗱᗴᴥᗩ𖧷ᗱᗴᗱᗴꕤᴥⵙ(f"ЯXƎ.𖣠⚪✤ИNᗱᗴⵙↀᗩᴥᕤᕦ𖣓✤ⵙ⚭𖣓꞉ⵈ⚪⊚⚪{ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ}⚪⊚⚪ⵈ꞉𖣓⚭ⵙ✤𖣓ᕤᕦᴥᗩↀⵙᗱᗴИN✤⚪𖣠.EXR",1-ⵙᗱᗴᕤᕦᗩᙏꖴᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏꖴᙏᗩᕤᕦᗱᗴⵙ)
ⵙᴥꕤᗱᗴᗱᗴ𖧷ᗩᴥᗱᗴИNᗱᗴᕤᕦⵙⵙᕤᕦᗱᗴИNᗱᗴᴥᗩ𖧷ᗱᗴᗱᗴꕤᴥⵙ(f"ЯXƎ.𖣠⚪ᔓᔕᙁᗱᗴᑐᑕ𖣓ↀᗱᗴᙁᗱᗴ⚭ᗩᙁ𖣓ᴥⓄᙁⓄᑐᑕ⚪⊚⚪{ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ}⚪⊚⚪ᑐᑕⓄᙁⓄᴥ𖣓ᙁᗩ⚭ᗱᗴᙁᗱᗴↀ𖣓ᑐᑕᗱᗴᙁᔓᔕ⚪𖣠.EXR",ߦᙏᑎИNⵙИNᑎᙏߦ.concatenate([(ⵙᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴⵙ/ߦᙏᑎИNⵙИNᑎᙏߦ.max(ⵙᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴⵙ)).astype(ߦᙏᑎИNⵙИNᑎᙏߦⵙ.float32)],axis=-1))
cv2.imencode('.png',cv2.normalize(ⵙↀᙁOᔓᔕᗱᗴᴥ𖧷𖧷ᴥᗱᗴᔓᔕOᙁↀⵙ,None,0,255,cv2.NORM_MINMAX))[1].tofile(f"ꓨИꟼ.𖣠⚪ↀᙁⓄᔓᔕᗱᗴᴥ✤⚪⊚⚪{ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ}⚪⊚⚪✤ᴥᗱᗴᔓᔕⓄᙁↀ⚪𖣠.PNG")
cv2.imencode('.png',cv2.normalize(255-ⵙᗱᗴᕤᕦᗩᙏꖴᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏꖴᙏᗩᕤᕦᗱᗴⵙ*255,None,0,255,cv2.NORM_MINMAX).astype(ߦᙏᑎИNⵙИNᑎᙏߦⵙ.uint8))[1].tofile(f"ꓨИꟼ.𖣠⚪✤ИNᗱᗴⵙↀᗩᴥᕤᕦ𖣓✤ⵙ⚭𖣓❋⚪⊚⚪{ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ}⚪⊚⚪❋𖣓⚭ⵙ✤𖣓ᕤᕦᴥᗩↀⵙᗱᗴИN✤⚪𖣠.PNG")
cv2.imencode('.png',65535-ⵙᗱᗴᕤᕦᗩᙏꖴᙏᴥOꗳᔓᔕИNᗩᴥ𖧷ᗱᗴᑐᑕИN𖧷ᔓᔕꖴↀↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏ𖧷8𓃎·ⵙⵙ·𓃎8𖧷ᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀↀꖴᔓᔕ𖧷ᗩИNᑐᑕᗱᗴ𖧷ᴥᗩИNᔓᔕꗳOᴥᙏꖴᙏᗩᕤᕦᗱᗴⵙ)[1].tofile(f"ꓨИꟼ.𖣠⚪✤ИNᗱᗴⵙↀᗩᴥᕤᕦ𖣓✤ⵙ⚭𖣓⠿·⚪⊚⚪{ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ}⚪⊚⚪·⠿𖣓⚭ⵙ✤𖣓ᕤᕦᴥᗩↀⵙᗱᗴИN✤⚪𖣠.PNG")
cv2.imencode('.png',cv2.normalize(ⵙᗱᗴᕤᕦᗩᙏꖴↀᗱᗴᙁᗱᗴ8ᗩᙁᗱᗴᙁߦꖴ𖧷ᙁᑎᙏⵙⵙᙏᑎᙁ𖧷ꖴߦᙁᗱᗴᙁᗩ8ᗱᗴᙁᗱᗴↀꖴᙏᗩᕤᕦᗱᗴⵙ,None,0,255,cv2.NORM_MINMAX).astype(ߦᙏᑎИNⵙИNᑎᙏߦⵙ.uint8))[1].tofile(f"ꓨИꟼ.𖣠⚪ᔓᔕᙁᗱᗴᑐᑕ𖣓ↀᗱᗴᙁᗱᗴ⚭ᗩᙁ𖣓ᴥⓄᙁⓄᑐᑕ⚪⊚⚪{ⵙᗱᗴᙏᗩИNᗱᗴᙁꖴꗳ𖧷ᑎߦИNꖴⵙⵙꖴИNߦᑎ𖧷ꗳꖴᙁᗱᗴИNᗩᙏᗱᗴⵙ}⚪⊚⚪ᑐᑕⓄᙁⓄᴥ𖣓ᙁᗩ⚭ᗱᗴᙁᗱᗴↀ𖣓ᑐᑕᗱᗴᙁᔓᔕ⚪𖣠.PNG")
exit()
 
הההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההההה
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Output:

Error: ENAMETOOLONG: name too long, open '/Yꟼ.𖣠⚪✤ИNᗱᗴⵙↀᗩᴥᕤᕦ𖤞ᙏᴥⓄꗳᔓᔕИNᗩᴥ✤𖥟ᗱᗴᑐᑕИNᗩ✤ᔓᔕⵙↀ𖡦ИNᗩᗱᗴↀⵙᙁᑐᑕᑎᗱᗴ𖥞⚪𔗢⚪🞋⚪𔗢⚪𖥞ᗱᗴᑎᑐᑕᙁⵙↀᗱᗴᗩИN𖡦ↀⵙᔓᔕ✤ᗩИNᑐᑕᗱᗴ𖥟✤ᴥᗩИNᔓᔕꗳⓄᴥᙏ𖤞ᕤᕦᴥᗩↀⵙᗱᗴИN✤⚪𖣠.PY'
by

Python Online Compiler

Write, Run & Share Python code online using OneCompiler's Python online compiler for free. It's one of the robust, feature-rich online compilers for python language, supporting both the versions which are Python 3 and Python 2.7. Getting started with the OneCompiler's Python editor is easy and fast. The editor shows sample boilerplate code when you choose language as Python or Python2 and start coding.

Taking inputs (stdin)

OneCompiler's python online editor supports stdin and users can give inputs to programs using the STDIN textbox under the I/O tab. Following is a sample python program which takes name as input and print your name with hello.

import sys
name = sys.stdin.readline()
print("Hello "+ name)

About Python

Python is a very popular general-purpose programming language which was created by Guido van Rossum, and released in 1991. It is very popular for web development and you can build almost anything like mobile apps, web apps, tools, data analytics, machine learning etc. It is designed to be simple and easy like english language. It's is highly productive and efficient making it a very popular language.

Tutorial & Syntax help

Loops

1. If-Else:

When ever you want to perform a set of operations based on a condition IF-ELSE is used.

if conditional-expression
    #code
elif conditional-expression
    #code
else:
    #code

Note:

Indentation is very important in Python, make sure the indentation is followed correctly

2. For:

For loop is used to iterate over arrays(list, tuple, set, dictionary) or strings.

Example:

mylist=("Iphone","Pixel","Samsung")
for i in mylist:
    print(i)

3. While:

While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.

while condition  
    #code 

Collections

There are four types of collections in Python.

1. List:

List is a collection which is ordered and can be changed. Lists are specified in square brackets.

Example:

mylist=["iPhone","Pixel","Samsung"]
print(mylist)

2. Tuple:

Tuple is a collection which is ordered and can not be changed. Tuples are specified in round brackets.

Example:

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)

Below throws an error if you assign another value to tuple again.

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
myTuple[1]="onePlus"
print(myTuple)

3. Set:

Set is a collection which is unordered and unindexed. Sets are specified in curly brackets.

Example:

myset{"iPhone","Pixel","Samsung"}
print{myset}

4. Dictionary:

Dictionary is a collection of key value pairs which is unordered, can be changed, and indexed. They are written in curly brackets with key - value pairs.

Example:

mydict = {
    "brand" :"iPhone",
    "model": "iPhone 11"
}
print(mydict)

Supported Libraries

Following are the libraries supported by OneCompiler's Python compiler

NameDescription
NumPyNumPy python library helps users to work on arrays with ease
SciPySciPy is a scientific computation library which depends on NumPy for convenient and fast N-dimensional array manipulation
SKLearn/Scikit-learnScikit-learn or Scikit-learn is the most useful library for machine learning in Python
PandasPandas is the most efficient Python library for data manipulation and analysis
MatplotlibMatplotlib is a cross-platform, data visualization and graphical plotting library for Python programming and it's numerical mathematics extension NumPy
DOcplexDOcplex is IBM Decision Optimization CPLEX Modeling for Python, is a library composed of Mathematical Programming Modeling and Constraint Programming Modeling


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