I'm trying to generate tfrecords the same way FSNS was generated?
when running that script:
def _int64_feature(value):
return tf.train.Feature(int64_list=tf.train.Int64List(value=value))
for j in range(0,int(len(addrs_image))):
print('Train data: {}/{}'.format(j,int(len(addrs_image))))
sys.stdout.flush()
img = Image.open(addrs_image[j])
img = img.resize((600, 150), Image.ANTIALIAS)
np_data = np.array(img)
image_data = img.tobytes()
for text in open(addrs_label[j], encoding="utf-8"):
char_ids_padded, char_ids_unpadded = encode_utf8_string(
text=text,
dic=dict,
length=7,
null_char_id=26)
example = tf.train.Example(features=tf.train.Features(
feature={
'image/encoded': _bytes_feature(image_data),
'image/format': _bytes_feature(b"raw"),
'image/width':
_int64_feature([np_data.shape[1]]),
'image/orig_width':
_int64_feature([np_data.shape[1]]),
'image/class': _int64_feature(char_ids_padded),
'image/unpadded_class':
_int64_feature(char_ids_unpadded),
'image/text': _bytes_feature(bytes(text, 'utf-8')),
# 'height': _int64_feature([crop_data.shape[0]]),
}
))
I got an error that says:
type error:'image/class': _int64_feature(char_ids_padded),r: none has type nonetype and the output expected to be int
'image/unpadded_class': _int64_feature(char_ids_unpadded),
and dic.txt file contain
enter image description here
So, any one has idea on how to solve that problem?
any suggestion is very appreciated and thank you all in advance
tfrecord
asked Nov 27 '18 at 17:36
Hamada FathyHamada Fathy
11
add a comment |
when running that script:
def _int64_feature(value):
return tf.train.Feature(int64_list=tf.train.Int64List(value=value))
for j in range(0,int(len(addrs_image))):
print('Train data: {}/{}'.format(j,int(len(addrs_image))))
sys.stdout.flush()
img = Image.open(addrs_image[j])
img = img.resize((600, 150), Image.ANTIALIAS)
np_data = np.array(img)
image_data = img.tobytes()
for text in open(addrs_label[j], encoding="utf-8"):
char_ids_padded, char_ids_unpadded = encode_utf8_string(
text=text,
dic=dict,
length=7,
null_char_id=26)
example = tf.train.Example(features=tf.train.Features(
feature={
'image/encoded': _bytes_feature(image_data),
'image/format': _bytes_feature(b"raw"),
'image/width':
_int64_feature([np_data.shape[1]]),
'image/orig_width':
_int64_feature([np_data.shape[1]]),
'image/class': _int64_feature(char_ids_padded),
'image/unpadded_class':
_int64_feature(char_ids_unpadded),
'image/text': _bytes_feature(bytes(text, 'utf-8')),
# 'height': _int64_feature([crop_data.shape[0]]),
}
))
I got an error that says:
type error:'image/class': _int64_feature(char_ids_padded),r: none has type nonetype and the output expected to be int
'image/unpadded_class': _int64_feature(char_ids_unpadded),
and dic.txt file contain
enter image description here
So, any one has idea on how to solve that problem?
any suggestion is very appreciated and thank you all in advance
tfrecord
asked Nov 27 '18 at 17:36
Hamada FathyHamada Fathy
11
add a comment |
when running that script:
def _int64_feature(value):
return tf.train.Feature(int64_list=tf.train.Int64List(value=value))
for j in range(0,int(len(addrs_image))):
print('Train data: {}/{}'.format(j,int(len(addrs_image))))
sys.stdout.flush()
img = Image.open(addrs_image[j])
img = img.resize((600, 150), Image.ANTIALIAS)
np_data = np.array(img)
image_data = img.tobytes()
for text in open(addrs_label[j], encoding="utf-8"):
char_ids_padded, char_ids_unpadded = encode_utf8_string(
text=text,
dic=dict,
length=7,
null_char_id=26)
example = tf.train.Example(features=tf.train.Features(
feature={
'image/encoded': _bytes_feature(image_data),
'image/format': _bytes_feature(b"raw"),
'image/width':
_int64_feature([np_data.shape[1]]),
'image/orig_width':
_int64_feature([np_data.shape[1]]),
'image/class': _int64_feature(char_ids_padded),
'image/unpadded_class':
_int64_feature(char_ids_unpadded),
'image/text': _bytes_feature(bytes(text, 'utf-8')),
# 'height': _int64_feature([crop_data.shape[0]]),
}
))
I got an error that says:
type error:'image/class': _int64_feature(char_ids_padded),r: none has type nonetype and the output expected to be int
'image/unpadded_class': _int64_feature(char_ids_unpadded),
and dic.txt file contain
enter image description here
So, any one has idea on how to solve that problem?
any suggestion is very appreciated and thank you all in advance
tfrecord
asked Nov 27 '18 at 17:36
Hamada FathyHamada Fathy
11
when running that script:
def _int64_feature(value):
return tf.train.Feature(int64_list=tf.train.Int64List(value=value))
for j in range(0,int(len(addrs_image))):
print('Train data: {}/{}'.format(j,int(len(addrs_image))))
sys.stdout.flush()
img = Image.open(addrs_image[j])
img = img.resize((600, 150), Image.ANTIALIAS)
np_data = np.array(img)
image_data = img.tobytes()
for text in open(addrs_label[j], encoding="utf-8"):
char_ids_padded, char_ids_unpadded = encode_utf8_string(
text=text,
dic=dict,
length=7,
null_char_id=26)
example = tf.train.Example(features=tf.train.Features(
feature={
'image/encoded': _bytes_feature(image_data),
'image/format': _bytes_feature(b"raw"),
'image/width':
_int64_feature([np_data.shape[1]]),
'image/orig_width':
_int64_feature([np_data.shape[1]]),
'image/class': _int64_feature(char_ids_padded),
'image/unpadded_class':
_int64_feature(char_ids_unpadded),
'image/text': _bytes_feature(bytes(text, 'utf-8')),
# 'height': _int64_feature([crop_data.shape[0]]),
}
))
I got an error that says:
type error:'image/class': _int64_feature(char_ids_padded),r: none has type nonetype and the output expected to be int
'image/unpadded_class': _int64_feature(char_ids_unpadded),
and dic.txt file contain
enter image description here
So, any one has idea on how to solve that problem?
any suggestion is very appreciated and thank you all in advance
tfrecord
tfrecord
asked Nov 27 '18 at 17:36
Hamada FathyHamada Fathy
11
asked Nov 27 '18 at 17:36
Hamada FathyHamada Fathy
11
asked Nov 27 '18 at 17:36
Hamada FathyHamada Fathy
11
asked Nov 27 '18 at 17:36
Hamada FathyHamada Fathy
11
asked Nov 27 '18 at 17:36
Hamada FathyHamada Fathy
11
11
add a comment |
add a comment |
0
active
oldest
votes
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53505190%2fim-trying-to-generate-tfrecords-the-same-way-fsns-was-generated%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
0
active
oldest
votes
0
active
oldest
votes
active
oldest
votes
active
oldest
votes
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53505190%2fim-trying-to-generate-tfrecords-the-same-way-fsns-was-generated%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
