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