instances/15_Image_Captioning_ShowAndTell_Flickr8k_DL.json

{
    "name": "15_Image_Captioning_ShowAndTell_Flickr8k_DL",
    "query": "This is my current PyTorch project: Develop an automatic image captioning system using the Show and Tell model. Here I found a repo can guide you: https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Image-Captioning. Use the dataset Flickr8k dataset, downloading it from [this link](https://huggingface.co/datasets/jxie/flickr8k) and load it in `src/data_loader.py`. The system should generate descriptions of sample images and save them to `results/metrics/generated_descriptions.txt`. An attention mechanism must be implemented in `src/model.py`. Save the pre-trained model as `models/saved_models/show_and_tell_model.pt`. Visualize the attention weights and save it to `results/figures/attention_weights.png`. The dataset should load smoothly, with proper error handling if any issues arise. Ideally, the attention mechanism should clearly highlight the image regions that are most influential in generating captions.",
    "tags": [
        "Computer Vision",
        "Natural Language Processing"
    ],
    "requirements": [
        {
            "requirement_id": 0,
            "prerequisites": [],
            "criteria": "The pre-trained \"Show and Tell\" model is used.",
            "category": "Machine Learning Method",
            "satisfied": null
        },
        {
            "requirement_id": 1,
            "prerequisites": [],
            "criteria": "The \"Flickr8k\" dataset, potentially downloaded from [this link](https://huggingface.co/datasets/jxie/flickr8k), is loaded in `src/data_loader.py`.",
            "category": "Dataset or Environment",
            "satisfied": null
        },
        {
            "requirement_id": 2,
            "prerequisites": [
                0,
                1
            ],
            "criteria": "The attention mechanism is implemented in `src/model.py`.",
            "category": "Machine Learning Method",
            "satisfied": null
        },
        {
            "requirement_id": 3,
            "prerequisites": [
                0,
                1,
                2
            ],
            "criteria": "Generated descriptions of sample images are saved in `results/metrics/generated_descriptions.txt`.",
            "category": "Other",
            "satisfied": null
        },
        {
            "requirement_id": 4,
            "prerequisites": [
                0,
                1,
                2
            ],
            "criteria": "The trained model is saved as `models/saved_models/show_and_tell_model.pt`.",
            "category": "Save Trained Model",
            "satisfied": null
        },
        {
            "requirement_id": 5,
            "prerequisites": [
                0,
                1,
                2
            ],
            "criteria": "A visualization of attention weights is saved as `results/figures/attention_weights.png`.",
            "category": "Visualization",
            "satisfied": null
        }
    ],
    "preferences": [
        {
            "preference_id": 0,
            "criteria": "The dataset should load smoothly, with clear error handling if any issues arise during download.",
            "satisfied": null
        },
        {
            "preference_id": 1,
            "criteria": "The attention mechanism should clearly highlight the image regions that contribute most to the generated captions.",
            "satisfied": null
        }
    ],
    "is_kaggle_api_needed": false,
    "is_training_needed": true,
    "is_web_navigation_needed": true
}