#convert the coords to image before streching to 448*448
left = left/448.0 * W
right = right/448.0 * W
up = up/448.0 * H
down = down/448.0 * H
#drawable.rectangle([left,up,right,down],outline="red")
if(class_num == 4):
fbottle.write(img_name+' '+str(round(prob,6))+' '+str(round(left,6))+' '+str(round(up,6))+' '+str(round(right,6))+' '+str(round(down,6))+'\n')
elif(class_num == 6):
fcar.write(img_name+' '+str(round(prob,6))+' '+str(round(left,6))+' '+str(round(up,6))+' '+str(round(right,6))+' '+str(round(down,6))+'\n')
elif(class_num == 7):
fcat.write(img_name+' '+str(round(prob,6))+' '+str(round(left,6))+' '+str(round(up,6))+' '+str(round(right,6))+' '+str(round(down,6))+'\n')
elif(class_num == 18):
ftrain.write(img_name+' '+str(round(prob,6))+' '+str(round(left,6))+' '+str(round(up,6))+' '+str(round(right,6))+' '+str(round(down,6))+'\n')
#img.save(os.path.join(os.getcwd(),'results',img_name+'.jpg'))
return
model = model_from_json(open('Tiny_Yolo_Architecture.json').read(),custom_objects={'custom_loss':custom_loss})
model.load_weights('Tiny_Yolo_weights_07_12_33102_iter2.h5')
#Measure Test Accuracy
sample_number = 4952
vocPath= os.path.join(os.getcwd(),'dataset/VOCdevkit/VOC2007')
imageNameFile= os.path.join(vocPath,'ImageSets/Main/test.txt')
imageList = prepareBatch(0,sample_number,imageNameFile,vocPath)
Acc(imageList,model)
def MeasureAcc(model,sample_number,vocPath,imageNameFile):
imageList = prepareBatch(0,sample_number,imageNameFile,vocPath)
acc = Acc(imageList,model)
re = Recall(imageList,model)
return acc,re
def MeasureAcc(model, sample_number, vocPath, imageNameFile):
imageList = prepareBatch(0, sample_number, imageNameFile, vocPath)
acc = Acc(imageList, model)
re = Recall(imageList, model)
return acc, re
if (preds[24] > thresh):
predcit_class = np.argmax(preds[4:24])
if (predcit_class == true_class):
correct += 1
return correct * 1.0 / obj_num
def MeasureAcc(model, sample_number, vocPath, imageNameFile):
imageList = prepareBatch(0, sample_number, imageNameFile, vocPath)
acc = Acc(imageList, model)
re = Recall(imageList, model)
return acc, re
model = model_from_json(open('Tiny_Yolo_Architecture.json').read(),
custom_objects={'custom_loss': custom_loss})
model.load_weights('weights2.hdf5')
#Measure Test Accuracy
sample_number = 4952
vocPath = os.path.join(os.getcwd(), 'dataset/VOCdevkit/VOC2007')
imageNameFile = os.path.join(vocPath, 'ImageSets/Main/test.txt')
imageList = prepareBatch(0, sample_number, imageNameFile, vocPath)
acc = Acc(imageList, model)
#re = Recall(imageList,model)
#print "Accuracy and Recall are: ",acc,re
print "Accuracy is: ", acc
