Hello, I'm a high school student who is running the code due to school assignments.
https://github.com/Bengemon825/TF_Object_Detection2020
I received an example from the link above and changed the data from 1 class to 2 classes, but I get an error like the title.
I think you're telling me to run xml_to_csv.py
first and then run generate_tfrecord.py
. The former runs well and the csv is well made, but the latter is troublesome.
Below is the full text of generate_tfrecord.py
. Please help me just once.
"""
Usage:
# # From tensorflow/models/
# # Create train data:
python generate_tfrecord.py --csv_input=data/train_labels.csv --output_path=train.record
python generate_tfrecord.py --csv_input=data/all_labels.csv --output_path=train.record
# # Create test data:
python generate_tfrecord.py --csv_input=data/test_labels.csv --output_path=test.record
python generate_tfrecord.py --csv_input=data/test_labels.csv --output_path=data/test.record --image_dir=images/
"""
# # taken from https://github.com/datitran/raccoon_dataset
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
import os
import io
import pandas as pd
import tensorflow as tf
from PIL import Image
from object_detection.utils import dataset_util
from collections import namedtuple, OrderedDict
flags = tf.compat.v1.app.flags
flags.DEFINE_string('csv_input', '', 'Path to the CSV input')
flags.DEFINE_string('output_path', '', 'Path to output TFRecord')
flags.DEFINE_string('image_dir', '', 'Path to images')
FLAGS = flags.FLAGS
# # replace row_label with the name you annotated your images as
def class_text_to_int(row_label):
if row_label == 'Masked':
return 1
elif row_label == 'No_Masked':
return 2
else :
None
def split(df, group):
data = namedtuple('data', ['filename', 'object'])
gb = df.groupby(group)
return [data(filename, gb.get_group(x)) for filename, x in zip(gb.groups.keys(), gb.groups)]
def create_tf_example(group, path):
with tf.io.gfile.GFile(os.path.join(path, '{}'.format(group.filename)), 'rb') as fid:
encoded_jpg = fid.read()
encoded_jpg_io = io.BytesIO(encoded_jpg)
image = Image.open(encoded_jpg_io)
width, height = image.size
filename = group.filename.encode('utf8')
image_format = b'jpg'
xmins = []
xmaxs = []
ymins = []
ymaxs = []
classes_text = []
classes = []
for index, row in group.object.iterrows():
xmins.append(row['xmin'] / width)
xmaxs.append(row['xmax'] / width)
ymins.append(row['ymin'] / height)
ymaxs.append(row['ymax'] / height)
classes_text.append(row['class'].encode('utf8'))
classes.append(class_text_to_int(row['class']))
tf_example = tf.train.Example(features=tf.train.Features(feature={
'image/height': dataset_util.int64_feature(height),
'image/width': dataset_util.int64_feature(width),
'image/filename': dataset_util.bytes_feature(filename),
'image/source_id': dataset_util.bytes_feature(filename),
'image/encoded': dataset_util.bytes_feature(encoded_jpg),
'image/format': dataset_util.bytes_feature(image_format),
'image/object/bbox/xmin': dataset_util.float_list_feature(xmins),
'image/object/bbox/xmax': dataset_util.float_list_feature(xmaxs),
'image/object/bbox/ymin': dataset_util.float_list_feature(ymins),
'image/object/bbox/ymax': dataset_util.float_list_feature(ymaxs),
'image/object/class/text': dataset_util.bytes_list_feature(classes_text),
'image/object/class/label': dataset_util.int64_list_feature(classes),
}))
return tf_example
def main(_):
writer = tf.io.TFRecordWriter(FLAGS.output_path)
path = os.path.join(FLAGS.image_dir)
examples = pd.read_csv(FLAGS.csv_input)
grouped = split(examples, 'filename')
for group in grouped:
tf_example = create_tf_example(group, path)
writer.write(tf_example.SerializeToString())
writer.close()
output_path = os.path.join(os.getcwd(), FLAGS.output_path)
print('Successfully created the TFRecords: {}'.format(output_path))
if __name__ == '__main__':
tf.compat.v1.app.run()
Below is an error that occurs when you run this as python.\generate_tfrecord.py
PS C:\Users\Sumin\TF_Object_Detection2020-master\masks> python generate_tfrecord.py
2020-09-18 09:16:50.716966: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2020-09-18 09:16:50.760112: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Traceback (most recent call last):
File "generate_tfrecord.py", line 109, in <module>
tf.compat.v1.app.run()
File "C:\Users\Sumin\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\platform\app.py", line 40, in run
_run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
File "C:\Users\Sumin\AppData\Roaming\Python\Python38\site-packages\absl\app.py", line 300, in run
_run_main(main, args)
File "C:\Users\Sumin\AppData\Roaming\Python\Python38\site-packages\absl\app.py", line 251, in _run_main
sys.exit(main(argv))
File "generate_tfrecord.py", line 95, in main
writer = tf.io.TFRecordWriter(FLAGS.output_path)
File "C:\Users\Sumin\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\lib\io\tf_record.py", line 298, in __init__
super(TFRecordWriter, self).__init__(
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xc1 in position 40: invalid start byte
2020-09-18 09:16:50.716966: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found 2020-09-18 09:16:50.760112: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine
If you look at the error above, there may be a problem with installing TensorFlow.
Google "cudart64_101.dll"; dlerror: cudart64_101.dll not found".
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