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Image_Captioning

The neural network architecture which automatically generate captions from images.

Project Instructions:

The project is structured as a series of Jupyter notebooks that are designed to be completed in sequential order: sequential order:

0_Dataset:
Step 1: Initialize the COCO API 
Step 2: Plot a sample image

1_Preliminaries:
Step 1: Explore the Data Loader
Step 2: Use the Data Loader to Obtain Batches
Step 3: Experiment with the CNN Encoder
Step 4: Implement the RNN Decoder

2_Training:
Step 1: Training Setup
Step 2: Train your Model

3_Inference:
Step 1: Get Data Loader for Test Dataset
Step 2: Load Trained Models
Step 3: Finish the Sampler
Step 4: Clean up Captions
Step 5: Generate Predictions!

You MUST enable GPU mode for this project.

Please note, a completely trained model is expected to take between 5-12 hours to train well on a GPU.



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