F0707 15:46:19.091634 13341 io.cpp:325] Check failed: 'anno' Must be non NULL

[Mrsherlock1996]

Hello, I successfully compiled your caffe-ssd, but it prompted me the error during create lmdb file by cread_data.sh:

sherlock@Y50-70:~/Downloads/myproject$ ./create_data.sh
root directory ok
list_file OK
img_file,anno,have been read
text_format has been used
anno_type is detection
/home/sherlock/Documents/caffe/build/tools/convert_annoset --anno_type=detection --label_type=xml --label_map_file=/home/sherlock/Downloads/myproject/labelmap_voc.prototxt --check_label=True --min_dim=0 --max_dim=0 --resize_height=256 --resize_width=256 --backend=lmdb --shuffle=False --check_size=False --encode_type=jpg --encoded=True --gray=False /home/sherlock/Downloads/myproject/ /home/sherlock/Downloads/myproject/trainval.txt /home/sherlock/Downloads/myproject/wider_face_LMDB/lmdb/wider_face_LMDB_trainval_lmdb
I0707 15:46:19.063556 13341 convert_annoset.cpp:122] A total of 12876 images.
I0707 15:46:19.063902 13341 db_lmdb.cpp:35] Opened lmdb /home/sherlock/Downloads/myproject/wider_face_LMDB/lmdb/wider_face_LMDB_trainval_lmdb
F0707 15:46:19.091634 13341 io.cpp:325] Check failed: 'anno' Must be non NULL
*** Check f

ailure stack trace: ***
@ 0x7f4ff26160cd google::LogMessage::Fail()
@ 0x7f4ff2617f33 google::LogMessage::SendToLog()
@ 0x7f4ff2615c28 google::LogMessage::Flush()
@ 0x7f4ff2618999 google::LogMessageFatal::~LogMessageFatal()
@ 0x7f4ff2a6ad45 google::CheckNotNull<>()
@ 0x7f4ff2a653cf caffe::ReadXMLToAnnotatedDatum()
@ 0x7f4ff2a6715e caffe::ReadRichImageToAnnotatedDatum()
@ 0x55c155bb1341 (unknown)
@ 0x7f4ff1416b97 __libc_start_main
@ 0x55c155bb1dfa (unknown)

could you help me solve this problem, thanks!!

[Mrsherlock1996]

this is create_data.sh

cur_dir=$(cd $( dirname ${BASH_SOURCE[0]} ) && pwd )
root_dir=$cur_dir

cd $root_dir

redo=1
data_root_dir="$root_dir"
dataset_name="wider_face_LMDB"
mapfile="$root_dir/labelmap_voc.prototxt"
anno_type="detection"
db="lmdb"
min_dim=0
max_dim=0
width=256
height=256

extra_cmd="--encode-type=jpg --encoded"
if [ $redo ]
then
extra_cmd="$extra_cmd --redo"
fi
for subset in trainval
do
python3 $root_dir/create_annoset.py --anno-type=$anno_type --label-map-file=$mapfile --min-dim=$min_dim --max-dim=$max_dim --resize-width=$width --resize-height=$height --check-label $extra_cmd $data_root_dir /home/sherlock/Downloads/myproject/trainval.txt $data_root_dir/$dataset_name/$db/$dataset_name""$subset""$db examples/$dataset_name
done

[Mrsherlock1996]

this is create_annoset.py

import argparse
import os
import shutil
import subprocess
import sys

from caffe.proto import caffe_pb2
from google.protobuf import text_format

if name == "main":
parser = argparse.ArgumentParser(description="Create AnnotatedDatum database")
parser.add_argument("root",
help="The root directory which contains the images and annotations.")
parser.add_argument("listfile",
help="The file which contains image paths and annotation info.")
parser.add_argument("outdir",
help="The output directory which stores the database file.")
parser.add_argument("exampledir",
help="The directory to store the link of the database files.")
parser.add_argument("--redo", default = False, action = "store_true",
help="Recreate the database.")
parser.add_argument("--anno-type", default = "classification",
help="The type of annotation {classification, detection}.")
parser.add_argument("--label-type", default = "xml",
help="The type of label file format for detection {xml, json, txt}.")
parser.add_argument("--backend", default = "lmdb",
help="The backend {lmdb, leveldb} for storing the result")
parser.add_argument("--check-size", default = False, action = "store_true",
help="Check that all the datum have the same size.")
parser.add_argument("--encode-type", default = "",
help="What type should we encode the image as ('png','jpg',...).")
parser.add_argument("--encoded", default = False, action = "store_true",
help="The encoded image will be save in datum.")
parser.add_argument("--gray", default = False, action = "store_true",
help="Treat images as grayscale ones.")
parser.add_argument("--label-map-file", default = "",
help="A file with LabelMap protobuf message.")
parser.add_argument("--min-dim", default = 0, type = int,
help="Minimum dimension images are resized to.")
parser.add_argument("--max-dim", default = 0, type = int,
help="Maximum dimension images are resized to.")
parser.add_argument("--resize-height", default = 0, type = int,
help="Height images are resized to.")
parser.add_argument("--resize-width", default = 0, type = int,
help="Width images are resized to.")
parser.add_argument("--shuffle", default = False, action = "store_true",
help="Randomly shuffle the order of images and their labels.")
parser.add_argument("--check-label", default = False, action = "store_true",
help="Check that there is no duplicated name/label.")

args = parser.parse_args()
root_dir = args.root
list_file = args.listfile
out_dir = args.outdir
example_dir = args.exampledir

redo = args.redo
anno_type = args.anno_type
label_type = args.label_type
backend = args.backend
check_size = args.check_size
encode_type = args.encode_type
encoded = args.encoded
gray = args.gray
label_map_file = args.label_map_file
min_dim = args.min_dim
max_dim = args.max_dim
resize_height = args.resize_height
resize_width = args.resize_width
shuffle = args.shuffle
check_label = args.check_label

check if root directory exists

if not os.path.exists(root_dir):
print("root directory: {} does not exist".format(root_dir))
sys.exit()
print("root directory ok")

add "/" to root directory if needed

if root_dir[-1] != "/":
root_dir += "/"

check if list file exists

if not os.path.exists(list_file):
print("list file: {} does not exist".format(list_file))
sys.exit()
print("list_file OK")

check list file format is correct

with open(list_file, "r") as lf:
for line in lf.readlines():
img_file, anno = line.strip("\n").split(" ")
if not os.path.exists(root_dir + img_file):
print("image file: {} does not exist".format(root_dir + img_file))
if anno_type == "classification":
if not anno.isdigit():
print("annotation: {} is not an integer".format(anno))
elif anno_type == "detection":
if not os.path.exists(root_dir + anno):
print("annofation file: {} does not exist".format(root_dir + anno))
sys.exit()
print("img_file,anno,have been read")
break

check if label map file exist

if anno_type == "detection":
if not os.path.exists(label_map_file):
print("label map file: {} does not exist".format(label_map_file))
sys.exit()
label_map = caffe_pb2.LabelMap()
lmf = open(label_map_file, "r")
try:
text_format.Merge(str(lmf.read()), label_map)
print("text_format has been used")
except:
print("Cannot parse label map file: {}".format(label_map_file))
sys.exit()
print("anno_type is detection")
out_parent_dir = os.path.dirname(out_dir)
if not os.path.exists(out_parent_dir):
os.makedirs(out_parent_dir)
if os.path.exists(out_dir) and not redo:
print("{} already exists and I do not hear redo".format(out_dir))
sys.exit()
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
print("finished shutil")

get caffe root directory

caffe_root = "/home/sherlock/Documents/caffe"
if anno_type == "detection":
cmd = "{}/build/tools/convert_annoset"
" --anno_type={}"
" --label_type={}"
" --label_map_file={}"
" --check_label={}"
" --min_dim={}"
" --max_dim={}"
" --resize_height={}"
" --resize_width={}"
" --backend={}"
" --shuffle={}"
" --check_size={}"
" --encode_type={}"
" --encoded={}"
" --gray={}"
" {} {} {}"
.format(caffe_root, anno_type, label_type, label_map_file, check_label,
min_dim, max_dim, resize_height, resize_width, backend, shuffle,
check_size, encode_type, encoded, gray, root_dir, list_file, out_dir)
elif anno_type == "classification":
cmd = "{}/build/tools/convert_annoset"
" --anno_type={}"
" --min_dim={}"
" --max_dim={}"
" --resize_height={}"
" --resize_width={}"
" --backend={}"
" --shuffle={}"
" --check_size={}"
" --encode_type={}"
" --encoded={}"
" --gray={}"
" {} {} {}"
.format(caffe_root, anno_type, min_dim, max_dim, resize_height,
resize_width, backend, shuffle, check_size, encode_type, encoded,
gray, root_dir, list_file, out_dir)
print(cmd)
process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE)
output = process.communicate()[0]

if not os.path.exists(example_dir):
os.makedirs(example_dir)
link_dir = os.path.join(example_dir, os.path.basename(out_dir))
if os.path.exists(link_dir):
os.unlink(link_dir)
os.symlink(out_dir, link_dir)