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gui_main.py
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gui_main.py
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import os
import wx
from PIL import Image
import numpy as np
import cv2
from dataset import Dataset
import propagate_label
def propagate_label_gmm(previmage,objmask,nextimage):
rows = previmage.shape[0]
cols = previmage.shape[1]
gmm_mask = np.ones((rows,cols),np.uint8)
gmm_mask = gmm_mask * 0
#print np.sum(gmm_mask)
gmm_mask[objmask[0],objmask[1]] = 3
sure_fg = np.random.randint((objmask[0].shape[0]),size=100)
for x in np.nditer(sure_fg):
gmm_mask[objmask[0][x],objmask[1][x]] = 1
bgdModel = np.zeros((1,65),np.float64)
fgdModel = np.zeros((1,65),np.float64)
img = nextimage
print type(img[0][0])
tmp_mask = np.zeros((rows,cols),np.uint8)
m1,m2 = np.where(gmm_mask==1)
r_mask, bgdModel, fgdModel = cv2.grabCut(img,gmm_mask,None,bgdModel,fgdModel,5,cv2.GC_INIT_WITH_MASK)
r_mask, bgdModel, fgdModel = cv2.grabCut(img,tmp_mask,(0,199,120,120),bgdModel,fgdModel,5,cv2.GC_INIT_WITH_RECT| cv2.GC_INIT_WITH_MASK)
print sure_fg
print np.sum(gmm_mask)
print r_mask.shape
print objmask[1].shape
print img.shape,r_mask.shape
l_img = img* r_mask[:,:,np.newaxis]
cv2.imwrite('gmmm.png',l_img)
rgb_np = np.zeros((self.gtframe.width,self.gtframe.height,3))
rgb_np[np.where(r_mask)]=[0,255,0]
data = rgb_np
rescaled = (255.0 / data.max() * (data - data.min())).astype(np.uint8)
rgb_image = Image.fromarray(rescaled)
return rgb_image
def getmasks(np_label):
labels = {}
labels['green'] = np.where((np_label==7) | (np_label==8) | (np_label==9))
labels['sky'] = np.where(np_label == 1)
labels['road'] = np.where((np_label==2) | (np_label==4))
labels['lane'] = np.where(np_label == 5)
labels['building'] = np.where(np_label == 11)
labels['vehicle'] = np.where((np_label==17) | (np_label==18) | (np_label==19))
labels['cycle'] = np.where((np_label==23) | (np_label==24))
labels['cyclist'] = np.where((np_label==25) | (np_label==26))
return labels
class Labeller(wx.App):
def __init__(self, redirect=False, filename=None):
wx.App.__init__(self, redirect, filename)
self.frame = wx.Frame(None, title='Semi-Automatic Labeling ')
self.panel = wx.Panel(self.frame)
self.PhotoMaxSize = 240
self.dataSet = Dataset(images_dir="./data/kitti01/images/",labels_dir="./data/kitti01/labels")
self.labels = self.dataSet.labels.items()
self.images = self.dataSet.images.items()
labels_desc = self.dataSet.label_desc.values()
print labels_desc[0]
self.objects = [ label[0] for label in labels_desc]
self.labeldict = getmasks(self.labels[0][1])
print "Masks are ready"
print self.labeldict.values()
self.objects = list(set(self.objects))
print self.objects
self.current_frame = self.images[0][1]
self.next_frame = self.images[1][1]
rgb_label= self.dataSet.makeRGBLabelFromInt(self.labels[0][1])
ol = self.dataSet.overlayRGBonImage(rgb_label,self.images[0][1])
cv2.imwrite('ol.png',ol)
self.createWidgets()
self.frame.Show()
def onPropagate(self,event):
'''The workhorse function to experiement with. Replace propagate_label with propagate_label_xxx
where xxx is your experiment. '''
propagated_label = propagate_label.algo_gmm(self.current_frame,self.mask,self.next_frame)
cv2.imwrite('pimage.png',propagated_label)
def onComboSelect(self,event):
self.selected_obj = event.GetString()
print self.selected_obj
rgb_np = np.zeros((self.dataSet.rows,self.dataSet.cols,3))
self.mask = self.labeldict[self.selected_obj]
rgb_np[self.mask]=[0,255,0]
data = rgb_np
rescaled = (255.0 / data.max() * (data - data.min())).astype(np.uint8)
rgb_image = Image.fromarray(rescaled)
ol = self.dataSet.overlayRGBonImage(rescaled,self.images[0][1])
cv2.imwrite('ol.png',ol)
self.onView()
def createWidgets(self):
instructions = 'Select Data set directory'
img = wx.EmptyImage(self.dataSet.cols,self.dataSet.rows)
self.frame.Show()
self.wxCurrentFrame = wx.StaticBitmap(self.panel, wx.ID_ANY,wx.BitmapFromImage(img))
self.wxNextFrame = wx.StaticBitmap(self.panel, wx.ID_ANY,wx.BitmapFromImage(img))
#Creating holder to display labelled frame
#Browse button to select directory
#Currently the directories are hard-coded in dataset class
browseBtn = wx.Button(self.panel, label='Load')
browseBtn.Bind(wx.EVT_BUTTON, self.onBrowse)
#Propagate button to invoke labelling algorithm
labelBtn = wx.Button(self.panel, label='Propagate')
labelBtn.Bind(wx.EVT_BUTTON, self.onPropagate)
distros = ["12","3432"]
#Combo Box to select the object to be propagated
cb = wx.ComboBox(self.panel, pos=(50, 30), choices=self.objects)
cb.Bind(wx.EVT_COMBOBOX,self.onComboSelect)
print "Creating sizers.."
self.mainSizer = wx.BoxSizer(wx.VERTICAL)
self.cf_sizer = wx.BoxSizer(wx.HORIZONTAL)
self.nf_sizer = wx.BoxSizer(wx.HORIZONTAL)
self.buttonsizer = wx.BoxSizer(wx.HORIZONTAL)
self.cf_sizer.Add(self.wxCurrentFrame, 0, wx.ALL, 5)
self.nf_sizer.Add(self.wxNextFrame, 0, wx.ALL, 5)
self.buttonsizer.Add(browseBtn, 0, wx.ALL, 5)
self.buttonsizer.Add(cb,0,wx.ALL,5)
self.buttonsizer.Add(labelBtn,0,wx.ALL,5)
self.mainSizer.Add(self.cf_sizer, 0, wx.ALL, 5)
self.mainSizer.Add(self.buttonsizer, 0, wx.ALL| wx.EXPAND, 5)
self.mainSizer.Add(self.nf_sizer, 0, wx.ALL, 5)
self.panel.SetSizer(self.mainSizer)
self.mainSizer.Fit(self.frame)
self.panel.Layout()
print "Layout done"
def onBrowse(self, event):
"""
Browse for file
"""
self.onView()
def onView(self):
img = wx.Image('ol.png', wx.BITMAP_TYPE_ANY)
self.wxCurrentFrame.SetBitmap(wx.BitmapFromImage(img))
next_file= os.path.join(self.dataSet.images_dir,self.images[1][0])
next_image = wx.Image(next_file, wx.BITMAP_TYPE_ANY)
self.wxNextFrame.SetBitmap(wx.BitmapFromImage(next_image))
self.panel.Refresh()
if __name__ == '__main__':
app = Labeller()
app.MainLoop()