image-captioning | repository contains PyTorch implementations of Show | Machine Learning library
kandi X-RAY | image-captioning Summary
kandi X-RAY | image-captioning Summary
This repository contains PyTorch implementations of Show and Tell: A Neural Image Caption Generator and Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. These models were among the first neural approaches to image captioning and remain useful benchmarks against newer models.
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Top functions reviewed by kandi - BETA
- Generate the model
- Reorder an incremental state
- Decode the model
- Generate training sentences
- Create binary dataset
- Add a word
- Binarize a string
- Get the value for a specific key
- Return the full increment state key for a module
- Collate features
- String representation of a tensor
- Plot image caption
- Plot a long caption
- Load a dictionary from a file
- Read lines from file
- Builds a dictionary from the annotations
- Calculate the final score
- Read lines from a file
- Save the corpus to a file
- Return a string representation of a tensor
- Extract features from image dataset
- Validate a training dataset
- Set the value of the given key to the given value
- Get command line arguments
image-captioning Key Features
image-captioning Examples and Code Snippets
Community Discussions
Trending Discussions on image-captioning
QUESTION
I have been trying to solve this error to complete my project but I dont get to know what I should do. Help me fixing this.
Code:
...ANSWER
Answered 2021-Mar-08 at 05:32resnet = ResNet50(include_top=False,weights='imagenet',input_shape=224,224,3),pooling='avg')
resnet = load_model('resnet50_weights_tf_dim_ordering_tf_kernels.h5')
print("="*150)
print("RESNET MODEL LOADED")
QUESTION
I got the following error when trying to load a ResNet50 model. Where should I download the resnet50.h5 file?
ANSWER
Answered 2021-Mar-05 at 18:16If you are looking for pre-trained weights of ResNet-50, you can find it here
QUESTION
I wanted to use this model but we cannot use merge anymore.
...ANSWER
Answered 2020-Aug-14 at 09:16you should define the caption_in as 2D: Input(shape=(max_len,)). in your case, the concatenation must be operated on the last axis: axis=-1. the rest seems ok
QUESTION
I'm generating my image captioning model's training data through a data generator which is added below. This model is based on the model provided here. How can I generate and set validation data in a similar fashion during the training? I do have the features of the validation images and their captions.
Data Generator:
...ANSWER
Answered 2020-Apr-07 at 14:41You need another generator.
One for training, one for validation. Just create two generators, one using training data, the other using validation data.
QUESTION
I'm trying to develop an image captioning model. I'm referring to this Github repository. I have three methods, and they perform the following:
- Generates the image model
- Generates the caption model
- Concatenates the image and caption model together
Since the code is long, I've created a Gist to show the methods.
Here is a summary of my image model and caption model.
But then I run the code, I am getting this error:
...ANSWER
Answered 2018-Sep-29 at 10:40You need the get the outputs of the models, using output attribute, and then use Keras functional API to be able to concatenate them (by either of Concatenate layer or its equivalent functional interface concatenate) and create the final model:
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