Image-Captioning-Project

Instructions

1. Please ensure you install coco api

cd cocoapi/PythonAPI
make

or

python setup.py install

2. Make sure your cocoapi folder in following tree struct (images/ at least with train and val)

cocoapi
├─annotations
│  └─.idea
├─common
├─images
│  ├─test2014
│  ├─train2014
│  └─val2014
├─MatlabAPI
│  └─private
├─PythonAPI
│  ├─build
│  │  ├─lib.win-amd64-3.6
│  │  │  └─pycocotools
│  │  └─temp.win-amd64-3.6
│  │      ├─common
│  │      ├─MatlabAPI
│  │      │  └─private
│  │      └─Release
│  │          └─pycocotools
│  ├─demos
│  └─pycocotools
│      └─__pycache__
└─results

3. Play with the app

• Move to working dir

cd img_caption

• Run the app

python TinkerUI.py

• Click Browse and we do provide some test images for you:

img_caption/user_uploaded

• Boom! You should have see some good stuff!

4. Model Applied

Our models is in:

img_caption\models\legit_model

(PS: Dont ask how many times failed in training and just take a look in the jupyter notebook log - img_caption\2_Training.ipynb)

5. Jupyter Notebook Workflow

• Vocab generation -- img_caption\1_Preliminaries.ipynb
• Training (with Val BLEU score at the bottom of the notebook) -- img_caption\2_Training.ipynb
• Demo -- img_caption\3_Demo.ipynb

6. Legit and Funny Outputs

• Perfect captioning:

• Weird sentence format or not fully captioning

• These are some really funny outcome

(PS: I can be a giraffe as well!!!)

7. Group Member

1001603 ZHOU XUEXUAN
1001427 WENG YUNFAN
1001417 ZHANG CHENG
1001426 SHANG XIAOSHENG (Play less PUBG plz)