tensorflow-im2txt | 谷歌图像叙事功能测试。

by ndscigdata Python Version: Current License: No License

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kandi X-RAY | tensorflow-im2txt Summary

tensorflow-im2txt is a Python library. tensorflow-im2txt has no bugs, it has no vulnerabilities and it has low support. However tensorflow-im2txt build file is not available. You can download it from GitHub.

谷歌图像叙事功能测试。

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Support

tensorflow-im2txt has a low active ecosystem.

It has 22 star(s) with 12 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 1041 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tensorflow-im2txt is current.

Quality

tensorflow-im2txt has no bugs reported.

Security

tensorflow-im2txt has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

tensorflow-im2txt does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

tensorflow-im2txt releases are not available. You will need to build from source code and install.

tensorflow-im2txt has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed tensorflow-im2txt and discovered the below as its top functions. This is intended to give you an instant insight into tensorflow-im2txt implemented functionality, and help decide if they suit your requirements.

Generate the caption file
Builds the graph from the given model configuration
Build model
Creates a function that returns a restore function
Build the model
Builds inputs
Builds the image embeddings
Process an image
Process image files
Decode a JPEG image
Create a sequence example
Run beam search
Push an item onto the heap
Extract data
Builds and returns a model
Build the graph
Logs image summary
Distort the image
Load and process captions
Process captions
Builds the graph from the given config
Builds a graph from a proto file
Create the vocabulary
Process images
Fetch data from a file

Get all kandi verified functions for this library.

tensorflow-im2txt Key Features

No Key Features are available at this moment for tensorflow-im2txt.

tensorflow-im2txt Examples and Code Snippets

No Code Snippets are available at this moment for tensorflow-im2txt.

Community Discussions

Trending Discussions on tensorflow-im2txt

regarding using the pre trained im2txt model

QUESTION

regarding using the pre trained im2txt model

Asked 2018-Oct-12 at 00:44

I have followed every step from here https://edouardfouche.com/Fun-with-Tensorflow-im2txt/ but i get the following error

NotFoundError (see above for traceback): Tensor name "lstm/basic_lstm_cell/bias" not found in checkpoint files /home/asadmahmood72/Image_to_text/models/im2txt/model.ckpt-3000000 [[Node: save/RestoreV2_380 = RestoreV2[dtypes=[DT_FLOAT], _device="/job:localhost/replica:0/task:0/cpu:0"](_arg_save/Const_0_0, save/RestoreV2_380/tensor_names, save/RestoreV2_380/shape_and_slices)]]

My os is UBUNTU 16.04 my tensorflow version is 1.2.0

...

ANSWER

Answered 2017-Jun-25 at 16:20

it looks like the tensorflow API changed again, which makes it incompatible with the checkpoint model. I was using tensorflow 0.12.1 in the article. Can you try with tensorflow 0.12.1 if it works? Otherwise you will have to train the model yourself (expensive) or find a checkpoint file that was generated with a more recent version of tensorflow...

Source https://stackoverflow.com/questions/44735794

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install tensorflow-im2txt

You can download it from GitHub.
You can use tensorflow-im2txt like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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