I am getting error with caffe.io.array_to_datum() for single channel images, how to solve?

Question

I am trying to convert a set of grayscale images and ground truth images to LMDB for segmentation task. I have created 4 text files (train.txt, train_label.txt, val.txt, val_label.txt) indicating path to each image in each folder. For many days, it is taking my time and still I am not successful. I am a beginner in python and caffe I will be thankful if somebody helps me here. I tried the following code:

import os
import numpy as np
from scipy import io
import lmdb
import caffe
from PIL import Image

NUM_IDX_DIGITS = 10
IDX_FMT = '{:0>%d' % NUM_IDX_DIGITS + 'd}'


# src
def img_to_lmdb(paths_src_file, path_dst):
    """
    paths_src: src img paths 
    path_dst: src img lmdb file
    """
    print("Creating Training Data LMDB File ..... ")

    paths_src = []
    with open(paths_src_file) as f: 
        for line in f.readlines():
            #print line 
            line = line.strip('\n')
            paths_src.append(line)

    #path_dst = 'train-lmdb'
    in_db = lmdb.open(path_dst, map_size=int(1e12))
    with in_db.begin(write=True) as in_txn:
        for in_idx, in_ in enumerate(paths_src):
            print in_idx, in_
            # load image:
            # - as np.uint8 {0, ..., 255}
            # - in BGR (switch from RGB)
            # - in Channel x Height x Width order (switch from H x W x C)
            im = np.array(Image.open(in_)) # or load whatever ndarray you need
            ###############
            print im.shape
            im = np.expand_dims(im, axis=0)
            print im.shape
            ###################
            im = im[:,:,::-1]
            #im = im[:,:]

            im = im.transpose((2,0,1)) # convert to CxHxW
            im_dat = caffe.io.array_to_datum(im)
            in_txn.put('{:0>10d}'.format(in_idx), im_dat.SerializeToString())
    in_db.close()
    print 'end.'

# label 
def label_to_lmdb(paths_label_file, path_dst):
    """
    paths_src: label img paths 
    path_dst: label lmdb file
    """
    print("Creating Training Label LMDB File ..... ")
    paths_src = []
    with open(paths_label_file) as f: 
        for line in f.readlines():
            line = line.strip('\n')
            paths_src.append(line)

    in_db = lmdb.open(path_dst, map_size=int(1e12))
    with in_db.begin(write=True) as in_txn:
        for in_idx, in_ in enumerate(paths_src):
            print in_idx, in_
            # load image:
            # - as np.uint8 {0, ..., 255}
            # - in BGR (switch from RGB)
            # - in Channel x Height x Width order (switch from H x W x C)
            im = np.array(Image.open(in_)) # or load whatever ndarray you need

            # 
            im = im.reshape(im.shape[0], im.shape[1], 1)
            im = im.transpose((2,0,1))
            ##

            ##im = np.expand_dims(im, axis=0)
                ##print im.shape


            #im = np.expand_dims(im, axis=0)    

            # create the dataset
            im_dat = caffe.io.array_to_datum(im)
            in_txn.put('{:0>10d}'.format(in_idx), im_dat.SerializeToString())
    in_db.close()
    print 'end.'

# train
train_img_paths = 'train.txt'
train_img_lmdb = 'train_img_lmdb'

train_label_paths = 'train_label.txt'
train_label_lmdb = 'train_label_lmdb'

img_to_lmdb(train_img_paths, train_img_lmdb)
label_to_lmdb(train_label_paths, train_label_lmdb)


# val
val_img_paths = 'val.txt'
val_img_lmdb = 'val_img_lmdb'


val_label_paths = 'val_label.txt'
val_label_lmdb = 'val_label_lmdb1'

img_to_lmdb(val_img_paths, val_img_lmdb)
label_to_lmdb(val_label_paths, val_label_lmdb)

I was getting an error:

im = im[:,:,::-1]
IndexError: too many indices for array

And:

im = im.transpose((2,0,1)) # convert to CxHxW
ValueError: axes don't match array

Since my images and labels are in grayscale (i.e., only one channel), I added im = np.expand_dims(im, axis=0), and now I am getting the following error:

Creating Training Data LMDB File ..... 
0 /home/user2/caffe-pascalcontext-fcn32s/dataset/Train/PNG/image-001-001.png
(281, 389)
(1, 281, 389)
Traceback (most recent call last):
  File "lmdb_data.py", line 104, in <module>
    img_to_lmdb(train_img_paths, train_img_lmdb)
  File "lmdb_data.py", line 46, in img_to_lmdb
    im_dat = caffe.io.array_to_datum(im)
  File "/home/user2/caffe-master/python/caffe/io.py", line 78, in array_to_datum
    datum.float_data.extend(arr.flat)
  File "/home/user2/anaconda2/envs/caffeenv/lib/python2.7/site-packages/google/protobuf/internal/containers.py", line 275, in extend
    new_values = [self._type_checker.CheckValue(elem) for elem in elem_seq_iter]
  File "/home/user2/anaconda2/envs/caffeenv/lib/python2.7/site-packages/google/protobuf/internal/type_checkers.py", line 108, in CheckValue
    raise TypeError(message)
TypeError: 66 has type <type 'numpy.int32'>, but expected one of: ((<type 'float'>, <type 'int'>, <type 'long'>),)

1. How can I fix this error?
2. How can I convert these four image sets into LMDB?
3. Is it possible I use convert_imageset (Caffe built-in converter) for this task? If yes, please let me know how can I do that?

Your help is really appreciated.