OneEye Changeset - c96bd773ec28

Changeset - c96bd773ec28

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Laman - 6 years ago 2019-05-03 18:09:55

random image transformations

3 files changed with 106 insertions and 20 deletions:

exp/keras/prepare_data.py

exp/keras/transformation_matrices.py

src/analyzer/corners.py

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exp/keras/prepare_data.py

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 import os
 import sys
 import re
 import random
 import numpy as np
 import cv2 as cv
 sys.path.append("../exp")
 from annotations import DataFile,computeBoundingBox
 from annotations import DataFile,computeBoundingBox,Corners
 from geometry import Line
 from keras.transformation_matrices import getIdentity,getRotation,getTranslation,getScale,getMirroring,getProjection
 random.seed(361)
 class Sample:
 	SIDE=256
 	def __init__(self,img,grid):
 		self.img=img
 		self.grid=grid
 	def transform(self):
 		center=self._getCenter()
 		m=getIdentity()
 		t1=getTranslation(-center.x,-center.y)
 		proj=getProjection()
 		rot=getRotation()
 		mir=getMirroring()
 		for mi in [t1,mir,proj,rot]:
 			m=np.matmul(mi,m)
 		m=np.matmul(self._computeCrop(m),m)
 		img=cv.warpPerspective(self.img,m,(self.SIDE,self.SIDE))
 		grid=Corners(c.transform(m) for c in self.grid)
 		Sample(img,grid).show()
 	def _getCenter(self):
 		(a,b,c,d)=self.grid
 		p=Line.fromPoints(a,c)
 		q=Line.fromPoints(b,d)
 		return p.intersect(q)
 	def _computeCrop(self,m):
 		grid=Corners(c.transform(m) for c in self.grid)
 		(x1,y1,x2,y2)=computeBoundingBox(grid)
 		(wg,hg)=(x2-x1,y2-y1)
 		(left,top,right,bottom)=[random.uniform(0.05,0.2) for i in range(4)]
 		t2=getTranslation(left*wg-x1, top*hg-y1)
 		scale=getScale(self.SIDE/(wg*(1+left+right)), self.SIDE/(hg*(1+top+bottom)))
 		return np.matmul(scale,t2)
 	def show(self):
 		img=np.copy(self.img)
 		for c in self.grid:
 			cv.circle(img,(int(c.x),int(c.y)),3,[0,255,0],-1)
 		show(img)
 def traverseDirs(root):
 	stack=[root]
 	while len(stack)>0:
 		d=stack.pop()
 		contents=sorted(os.scandir(d),key=lambda f: f.name,reverse=True)
 		if any(f.name=="annotations.json.gz" for f in contents):
 			print(d)
 			yield d
 		for f in contents:
 			if f.is_dir(): stack.append(f.path)
 def harvestDir(path):
 	annotations=DataFile(os.path.join(path,"annotations.json.gz"))
 	imgFilter=lambda f: f.is_file() and re.match(r".*\.(jpg|jpeg|png|gif)$", f.name.lower())
 	files=sorted(filter(imgFilter,os.scandir(path)),key=lambda f: f.name)
 	boards=annotations["."]
 	for f in files:
 		img=cv.imread(f.path)
 		for b in boards:
 			crop(img,b)
 def crop(img,board):
 	margin=0.2
 	(hi,wi)=img.shape[:2]
 	(x1,y1,x2,y2)=computeBoundingBox(board.board)
 	(wb,hb)=(x2-x1,y2-y1)
 	dx1=min(int(wb*margin),x1)
 	dx2=min(int(wb*margin),wi-x2)
 	dy1=min(int(hb*margin),y1)
 	dy2=min(int(hb*margin),hi-y2)
 	xa=x1-random.randint(0,dx1)
 	xb=x2+random.randint(0,dx2)
 	ya=y1-random.randint(0,dy1)
 	yb=y2+random.randint(0,dy2)
 	show(img[ya:yb,xa:xb])
 	return img[ya:yb,xa:xb]
 			sample=Sample(img,b.grid)
 			sample.transform()
 def show(img,filename="x"):
 	cv.imshow(filename,img)
 	cv.waitKey(0)
 	cv.destroyAllWindows()
 if __name__=="__main__":
 	root=sys.argv[1]
 	for d in traverseDirs(root):
 		harvestDir(d)

exp/keras/transformation_matrices.py

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@@ new file 100644 @@
 import math
 import random
 import numpy as np
 def getIdentity():
 	return np.float32([
 		[1,0,0],
 		[0,1,0],
 		[0,0,1]
 	])
 def getRotation():
 	alpha=random.random()*2*math.pi
 	return np.float32([
 		[math.cos(alpha),math.sin(alpha),0],
 		[-math.sin(alpha),math.cos(alpha),0],
 		[0,0,1]
 	])
 def getTranslation(dx,dy):
 	return np.float32([
 		[1,0,dx],
 		[0,1,dy],
 		[0,0,1]
 	])
 def getScale(kx,ky=0):
 	if not ky: ky=kx
 	return np.float32([
 		[kx,0,0],
 		[0,ky,0],
 		[0,0,1]
 	])
 def getMirroring():
 	return np.float32([
 		[random.choice((1,-1)),0,0],
 		[0,1,0],
 		[0,0,1]
 	])
 def getProjection():
 	dx=random.uniform(-0.001,0.001)
 	dy=random.uniform(-0.001,0.001)
 	return np.float32([
 		[1,0,0],
 		[0,1,0],
 		[dx,dy,1]
 	])

src/analyzer/corners.py

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 import logging
 from .epoint import EPoint
 log=logging.getLogger(__name__)
 class Corners:
 	def __init__(self,cornerList=[]):
-		self._corners=cornerList[:]
+		self._corners=list(cornerList)
 		self._is_canon=False
 		self._canonizeOrder()
 	## Adds a new corner if there are less than four, replaces the closest otherwise.
 	def add(self,x,y):
 		a=EPoint(x,y)
 		# for i,c in enumerate(self.corners): # move an improperly placed point
 			# if a.dist(c)<20:
 				# self.corners[i]=a
 				# return
 		if len(self._corners)<4: # add a new corner

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