Exemple #1
0
    def build_dataset(self, datadir, spec, dset_name):

      print(dset_name)
      img = read_file(os.path.join(datadir, dset_name + "_img.h5"))
      mit0 = read_file(os.path.join(datadir, dset_name + "_mit.h5")).astype("float32")
      mit1 = read_file(os.path.join(datadir, dset_name + "_1eroded_mit.h5")).astype("float32")
      mit2 = read_file(os.path.join(datadir, dset_name + "_2eroded_mit.h5")).astype("float32")
      mit3 = read_file(os.path.join(datadir, dset_name + "_3eroded_mit.h5")).astype("float32")
#      seg = read_file(os.path.join(datadir, dset_name + "_seg.h5"))

      img = dp.transform.divideby(img, val=255.0, dtype="float32")
    
      mit0[mit0 != 0] = 1 #Binarizing psds
      mit1[mit1 != 0] = 1 #Binarizing psds
      mit2[mit2 != 0] = 1 #Binarizing psds
      mit3[mit3 != 0] = 1 #Binarizing psds

      vd = dp.VolumeDataset()
      vd.add_raw_data(key="input",      data=img)
      vd.add_raw_data(key="mit0_label",       data=mit0)
      vd.add_raw_data(key="mit1_label",       data=mit1)
      vd.add_raw_data(key="mit2_label",       data=mit2)
      vd.add_raw_data(key="mit3_label",       data=mit3)
      # vd.add_raw_data(key="psd_mask",   data=msk)

      vd.set_spec(spec)
      return vd
Exemple #2
0
def make_forward_scanner(data_name, opt):
    # Read an EM image.
    if opt.dummy:
        img = np.random.rand(*opt.input_size[-3:]).astype('float32')
    else:
        img = emio.imread(os.path.join(opt.data_dir, data_name + '_img.h5'))
        img = (img / 255.).astype('float32')
    # Build Dataset.
    vd = dp.VolumeDataset()
    vd.add_raw_data(key='input', data=img)
    vd.set_spec(opt.in_spec)
    return dp.ForwardScanner(vd, opt.scan_spec, params=opt.scan_params)
Exemple #3
0
 def build_dataset(self):
     # Image.
     img = self.data['img']
     # Segmentation.
     seg = self.data['seg']
     # Mask.
     msk = self.data['msk_' + self.mode]
     # Build dataset.
     vd = dp.VolumeDataset()
     vd.add_raw_data(key='input',         data=img)
     vd.add_raw_data(key='affinity',      data=seg)
     vd.add_raw_mask(key='affinity_mask', data=msk, loc=True)
     vd.set_spec(self.spec)
     return vd
Exemple #4
0
def make_forward_scanner(dset_name, data_dir, input_spec,
                         scan_spec, scan_params, **params):
    """ Creates a DataProvider ForwardScanner from a dset name """

    # Reading EM image
#    img = utils.read_h5(dset_name)
    print("image path", os.path.join(data_dir, dset_name + "_img.h5"))
    img = utils.read_h5(os.path.join(data_dir, dset_name + "_img.h5"))
    img = (img / 255.).astype("float32")

    # Creating DataProvider Dataset
    vd = dp.VolumeDataset()

    vd.add_raw_data(key="input", data=img)
    vd.set_spec(input_spec)

    # Returning DataProvider ForwardScanner
    return dp.ForwardScanner(vd, scan_spec, params=scan_params)
Exemple #5
0
    def build_dataset(self, datadir, spec, dset_name):

        print(dset_name)
        img = read_file(os.path.join(datadir, dset_name + "_img.h5"))
        psd = read_file(os.path.join(datadir,
                                     dset_name + "_mit.h5")).astype("float32")
        #      seg = read_file(os.path.join(datadir, dset_name + "_seg.h5"))

        img = dp.transform.divideby(img, val=255.0, dtype="float32")
        psd[psd != 0] = 1  #Binarizing psds
        #     msk = (seg == 0).astype("float32") #Boundary mask

        vd = dp.VolumeDataset()
        vd.add_raw_data(key="input", data=img)
        vd.add_raw_data(key="psd_label", data=psd)
        #    vd.add_raw_data(key="psd_mask",   data=msk)

        vd.set_spec(spec)
        return vd
Exemple #6
0
    def build_dataset(self, datadir, spec, dset_name, erode):
      
      print(dset_name)
      img = read_file(os.path.join(datadir, dset_name + "_img.h5"))
      mit_str = "_mit.h5"
      if erode:
        mit_str = "_"+str(erode)+"erode"+"_mit.h5"
      mit = read_file(os.path.join(datadir, dset_name + mit_str)).astype("float32")
#       print(img.shape)
#       print(mit.shape)
#      seg = read_file(os.path.join(datadir, dset_name + "_seg.h5"))

      img = dp.transform.divideby(img, val=255.0, dtype="float32")
    
      mit[mit != 0] = 1 #Binarizing psds
      vd = dp.VolumeDataset()
      vd.add_raw_data(key="input",      data=img)
      vd.add_raw_data(key="psd_label",  data=mit)
      # vd.add_raw_data(key="psd_mask", data=msk)

      vd.set_spec(spec)
      return vd
Exemple #7
0
    def build_dataset(self, datadir, spec, dset_name, resize):

      print(dset_name)
      img = read_file(os.path.join(datadir, dset_name + "_resized4_img.h5"))
      psd = read_file(os.path.join(datadir, dset_name + "_resized4_blood.h5")).astype("float32")
#      seg = read_file(os.path.join(datadir, dset_name + "_seg.h5"))

      img = dp.transform.divideby(img, val=255.0, dtype="float32")
      
      psd[psd != 0] = 1 #Binarizing psds
      #if (resize != 1):
      #     img = utils.resize_image(img, resize)
      #     psd = scipy.misc.imresize(psd, 1.0/resize, interp="bilinear")
      #     msk = (seg == 0).astype("float32") #Boundary mask

      vd = dp.VolumeDataset()
      vd.add_raw_data(key="input",      data=img)
      vd.add_raw_data(key="psd_label",  data=psd)
      # vd.add_raw_data(key="psd_mask",   data=msk)

      vd.set_spec(spec)
      return vd