File size: 1,654 Bytes
cd1be53 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 | # Manual Prompt-Aligned AI Image Dataset
## Description
This dataset contains manually generated AI images created from a fixed, predefined set of prompts. Each image is directly aligned to its corresponding prompt file and generated across multiple image generation models.
## Prompt Alignment
Each image is generated directly from a corresponding prompt file found in ./prompts.
## Directory Structure
```
images/
├── dalle/
│ ├── p001.png
│ ├── p002.png
│ └── ...
├── midjourney/
│ ├── p001.png
│ └── ...
├── bing/
│ ├── p001.jpg
│ └── ...
├── stable_diffusion/
│ ├── p001.png
│ └── ...
├── ideogram/
│ ├── p001.png
│ └── ...
└── nanobanana/
├── p001.png
└── ...
prompts/
├── p001.txt
└── ...
```
## Generators Used
- DALL-E
- Midjourney (In Progress)
- Bing (MAI-Image-1 Model)
- Stable Diffusion (In Progress)
- Ideogram (In Progress)
- FLUX (skipped due to required paid credits)
- Nano Banana
## Metadata Inference
Metadata is derived implicitly from file paths:
- `generator` → parent directory name under `images/`
- `prompt_id` → filename (e.g., `p042`)
- `prompt_text` → contents of `prompts/p042.txt`
Example derived record:
```python
{
"image_path": ".../images/dalle/p042.png", # note that all images in bing folder are jpg
"generator": "dalle",
"prompt_id": "p042",
"prompt_text": "...contents of prompts/p042.txt..."
}
```
## Limitations
This dataset was manually generated and is therefore limited in scale and generator coverage.
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