Datasets:
ArXiv:
License:
{ | |
"name": "18_Image_Enhancement_SRGAN_DIV2K_DL", | |
"query": "I need to create a system for image enhancement using an SRGAN model (you can obtain a pre-trained SRGAN [here](https://github.com/tensorlayer/srgan)) with the DIV2K dataset, which can be downloaded from [this link](https://data.vision.ee.ethz.ch/cvl/DIV2K/). The dataset should be loaded in the `src/data_loader.py` file. The system should preprocess the images, including resizing and normalization, in `src/data_loader.py`. Use a pre-trained model saved under `models/saved_models/` to save time, and save the enhanced images to the `results/figures/` directory. Additionally, the system should visualize and save the comparison between the original and enhanced images to `results/figures/enhanced_comparison.png`. Finally, create a Markdown report with results and visualizations on a diverse set of samples to showcase the model's performance on various types of images, and save it as `results/report.md`. The report should include a detailed comparison of the model's performance on these selected samples, highlighting where the model excels or struggles.", | |
"tags": [ | |
"Computer Vision", | |
"Generative Models" | |
], | |
"requirements": [ | |
{ | |
"requirement_id": 0, | |
"prerequisites": [], | |
"criteria": "The \"DIV2K\" dataset is loaded in the `src/data_loader.py` file.", | |
"category": "Dataset or Environment", | |
"satisfied": null | |
}, | |
{ | |
"requirement_id": 1, | |
"prerequisites": [], | |
"criteria": "A pre-trained \"SRGAN\" model is saved under `models/saved_models/`.", | |
"category": "Save Trained Model", | |
"satisfied": null | |
}, | |
{ | |
"requirement_id": 2, | |
"prerequisites": [ | |
0 | |
], | |
"criteria": "Image preprocessing, including resizing and normalization, is implemented in `src/data_loader.py`.", | |
"category": "Data preprocessing and postprocessing", | |
"satisfied": null | |
}, | |
{ | |
"requirement_id": 3, | |
"prerequisites": [ | |
0, | |
1, | |
2 | |
], | |
"criteria": "Enhanced images are saved to the specified folder `results/figures/`.", | |
"category": "Data preprocessing and postprocessing", | |
"satisfied": null | |
}, | |
{ | |
"requirement_id": 4, | |
"prerequisites": [ | |
0, | |
1, | |
2, | |
3 | |
], | |
"criteria": "The comparison of original and enhanced images is visualized and saved as `results/figures/enhanced_comparison.png`.", | |
"category": "Visualization", | |
"satisfied": null | |
}, | |
{ | |
"requirement_id": 5, | |
"prerequisites": [ | |
1, | |
2, | |
3, | |
4 | |
], | |
"criteria": "A Markdown file containing results and visualizations is generated and saved as `results/report.md`.", | |
"category": "Visualization", | |
"satisfied": null | |
} | |
], | |
"preferences": [ | |
{ | |
"preference_id": 0, | |
"criteria": "A diverse set of samples should be selected to showcase the model's performance across different types of images.", | |
"satisfied": null | |
}, | |
{ | |
"preference_id": 1, | |
"criteria": "The Markdown report should include a detailed comparison of the model's performance on these selected samples, highlighting where the model excels or struggles.", | |
"satisfied": null | |
} | |
], | |
"is_kaggle_api_needed": false, | |
"is_training_needed": false, | |
"is_web_navigation_needed": true | |
} |