Image-Caption-Generator
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A simple implementation of neural image caption generator
Image-Caption-Generator
A simple implementation of neural image caption generator
Please note that the code in this repo is for use in talks/workshops. There is a lot of room for improvement (in terms of both accuracy and efficiency) so that these aspects can be discussed during the sessions.
You may refer to Tensorflow's im2text Model for a stable and accurate implementation.
Setup
Create Directories
- Run
./scripts/mkdir.sh
Downloading Datasets
- Run
./scripts/download_images.sh - This downloads Flick8K dataset
Downloading Models
- The VGG16 model would be downloaded automatically when the model is trained for the first time and would be cached on the disk.
- Alternatively, run
python3 vgg16.py. It would download the VGG16 model, produce the embeddings for a test image and compare with a pre-computed embedding.
Processing Images
- Update
data_dirincode/preprocess.pyand setmode_list=["train", "test", "debug"] - Run
python3 preprocess.py
Train
- Run
python3 train.py