def zadanie4():
cykl.beta = 1.0
baseForce=np.zeros(101)
for i in range(len(baseForce)):
baseForce[i]=exp(-100000*(i/100.0-0.5)**2.0)
cykl.baseForce=baseForce
u=np.zeros(101)
u = utils.methodGrid(cykl,u,10.0)
utils.saveMatrix("Zadanie4.txt", u)
def computeGlobalImageMask():
params = cu.loadParams('category imgsDir groundTruthsFile layer outputDir')
arch = loadArchitecture('cnn.arch')
A = projectCoordsToReceptiveField(arch,params['layer'])
boxes = listBoxes(A)
gt = loadBoxIndexFile(params['groundTruthsFile'])
for imName in gt.keys():
imgFile = params['imgsDir']+'/'+imName+'.jpg'
w,h = Image.open(imgFile).size
R = intersectWithGroundTruth(A,rescaleAllBoxes(gt[imName],227./w, 227./h))
cu.saveMatrix(R,params['outputDir']+'/'+imName+'.'+params['category'])
def computeGlobalImageMask():
params = cu.loadParams('category imgsDir groundTruthsFile layer outputDir')
arch = loadArchitecture('cnn.arch')
A = projectCoordsToReceptiveField(arch, params['layer'])
boxes = listBoxes(A)
gt = loadBoxIndexFile(params['groundTruthsFile'])
for imName in gt.keys():
imgFile = params['imgsDir'] + '/' + imName + '.jpg'
w, h = Image.open(imgFile).size
R = intersectWithGroundTruth(
A, rescaleAllBoxes(gt[imName], 227. / w, 227. / h))
cu.saveMatrix(
R, params['outputDir'] + '/' + imName + '.' + params['category'])
def multipleRegionMasks():
params = cu.loadParams('category imgsDir groundTruthsFile layer featuresDir outputDir')
arch = loadArchitecture('cnn.arch')
A = projectCoordsToReceptiveField(arch,params['layer'])
s = len(A)
gt = loadBoxIndexFile(params['groundTruthsFile'])
for imName in gt.keys():
imgFile = params['imgsDir']+'/'+imName+'.jpg'
w,h = Image.open(imgFile).size
idx = loadBoxIndexFile(params['featuresDir'] + '/' + imName + '.idx')
M = np.zeros((len(idx[imName]),s,s))
i = 0
for box in idx[imName]:
P = projectFeatureMapToImagePlane(box,A)
M[i,:,:] = intersectWithGroundTruth(P,gt[imName])
i += 1
cu.saveMatrix(M,params['outputDir']+'/'+imName+'.'+params['category'])
def selectRegions(imageList, featuresDir, groundTruths, outputDir, featExt, category, operator):
task = RegionSelector(groundTruths, operator)
result = processData(imageList, featuresDir, featExt, task)
nBoxes,nFeat = 0,0
for r in result:
nBoxes += r[0].shape[0]
nFeat = r[0].shape[1]
featureMatrix = np.zeros( (nBoxes,nFeat) )
i = 0
outputFile = open(outputDir + '/' + category + '.idx','w')
for r in result:
featureMatrix[i:i+r[0].shape[0]] = r[0]
for box in r[1]:
outputFile.write(box[0] + ' ' + ' '.join(map(str,map(int,box[1:]))) + '\n')
i += r[0].shape[0]
outputFile.close()
cu.saveMatrix(featureMatrix,outputDir + '/' + category + '.' + featExt)
print 'Total of',nBoxes,'positive examples collected for',category
def multipleRegionMasks():
params = cu.loadParams(
'category imgsDir groundTruthsFile layer featuresDir outputDir')
arch = loadArchitecture('cnn.arch')
A = projectCoordsToReceptiveField(arch, params['layer'])
s = len(A)
gt = loadBoxIndexFile(params['groundTruthsFile'])
for imName in gt.keys():
imgFile = params['imgsDir'] + '/' + imName + '.jpg'
w, h = Image.open(imgFile).size
idx = loadBoxIndexFile(params['featuresDir'] + '/' + imName + '.idx')
M = np.zeros((len(idx[imName]), s, s))
i = 0
for box in idx[imName]:
P = projectFeatureMapToImagePlane(box, A)
M[i, :, :] = intersectWithGroundTruth(P, gt[imName])
i += 1
cu.saveMatrix(
M, params['outputDir'] + '/' + imName + '.' + params['category'])
def selectRegions(imageList, featuresDir, groundTruths, outputDir, featExt,
category, operator):
task = RegionSelector(groundTruths, operator)
result = processData(imageList, featuresDir, featExt, task)
nBoxes, nFeat = 0, 0
for r in result:
nBoxes += r[0].shape[0]
nFeat = r[0].shape[1]
featureMatrix = np.zeros((nBoxes, nFeat))
i = 0
outputFile = open(outputDir + '/' + category + '.idx', 'w')
for r in result:
featureMatrix[i:i + r[0].shape[0]] = r[0]
for box in r[1]:
outputFile.write(box[0] + ' ' +
' '.join(map(str, map(int, box[1:]))) + '\n')
i += r[0].shape[0]
outputFile.close()
cu.saveMatrix(featureMatrix, outputDir + '/' + category + '.' + featExt)
print 'Total of', nBoxes, 'positive examples collected for', category
import os,sys
import utils as cu
import numpy as np
params = cu.loadParams('matrix1 matrix2 output')
Ma,Ia = cu.loadMatrixAndIndex(params['matrix1'])
Mb,Ib = cu.loadMatrixAndIndex(params['matrix2'])
extension = params['matrix1'].split('.')[-1]
cu.saveMatrix( np.concatenate( (Ma,Mb) ) , params['output']+'.'+extension)
out = open(params['output']+'.idx','w')
for r in Ia:
out.write(' '.join(r)+'\n')
for r in Ib:
out.write(' '.join(r)+'\n')
out.close()
def zadanie2():
u=np.zeros(101)
for i, x in enumerate(u):
u[i] = exp(-100.0*((i/100.0)-0.5)**2.0)
utils.saveMatrix("Zadanie2a.txt", utils.methodGrid(cykl1,np.copy(u)))
utils.saveMatrix("Zadanie2b.txt", utils.methodGrid(cykl2,np.copy(u)))
def run(self, img, features, bboxes):
print img
scores = self.model.sigmoidValues(features)
cu.saveMatrix(scores, self.outDir + '/' + img + '.sigmoid_scores')
return
import os, sys
import utils as cu
import numpy as np
params = cu.loadParams('matrix1 matrix2 output')
Ma, Ia = cu.loadMatrixAndIndex(params['matrix1'])
Mb, Ib = cu.loadMatrixAndIndex(params['matrix2'])
extension = params['matrix1'].split('.')[-1]
cu.saveMatrix(np.concatenate((Ma, Mb)), params['output'] + '.' + extension)
out = open(params['output'] + '.idx', 'w')
for r in Ia:
out.write(' '.join(r) + '\n')
for r in Ib:
out.write(' '.join(r) + '\n')
out.close()
def run(self,img,features,bboxes): print img scores = self.model.sigmoidValues(features) cu.saveMatrix(scores, self.outDir+'/'+img+'.sigmoid_scores') return
