---
configs:
- config_name: split_20250821_120925
  data_files:
  - split: train
    path: data/split_20250821_120925.parquet
- config_name: split_20250821_122924
  data_files:
  - split: train
    path: data/split_20250821_122924.parquet
- config_name: split_20250821_123925
  data_files:
  - split: train
    path: data/split_20250821_123925.parquet
- config_name: split_20250821_124926
  data_files:
  - split: train
    path: data/split_20250821_124926.parquet
- config_name: split_20250821_130425
  data_files:
  - split: train
    path: data/split_20250821_130425.parquet
- config_name: split_20250821_131426
  data_files:
  - split: train
    path: data/split_20250821_131426.parquet
- config_name: split_20250821_133425
  data_files:
  - split: train
    path: data/split_20250821_133425.parquet
- config_name: split_20250821_134425
  data_files:
  - split: train
    path: data/split_20250821_134425.parquet
- config_name: split_20250821_140445
  data_files:
  - split: train
    path: data/split_20250821_140445.parquet
- config_name: split_20250821_141427
  data_files:
  - split: train
    path: data/split_20250821_141427.parquet
- config_name: split_20250821_142925
  data_files:
  - split: train
    path: data/split_20250821_142925.parquet
- config_name: split_20250821_143429
  data_files:
  - split: train
    path: data/split_20250821_143429.parquet
- config_name: split_20250821_145425
  data_files:
  - split: train
    path: data/split_20250821_145425.parquet
- config_name: split_20250821_150928
  data_files:
  - split: train
    path: data/split_20250821_150928.parquet
- config_name: split_20250821_152925
  data_files:
  - split: train
    path: data/split_20250821_152925.parquet
- config_name: split_20250821_155424
  data_files:
  - split: train
    path: data/split_20250821_155424.parquet
- config_name: split_20250821_161924
  data_files:
  - split: train
    path: data/split_20250821_161924.parquet
- config_name: split_20250821_163927
  data_files:
  - split: train
    path: data/split_20250821_163927.parquet
- config_name: split_20250821_170937
  data_files:
  - split: train
    path: data/split_20250821_170937.parquet
- config_name: split_20250821_173926
  data_files:
  - split: train
    path: data/split_20250821_173926.parquet
- config_name: split_20250821_180425
  data_files:
  - split: train
    path: data/split_20250821_180425.parquet
- config_name: split_20250821_182427
  data_files:
  - split: train
    path: data/split_20250821_182427.parquet
- config_name: split_20250821_184448
  data_files:
  - split: train
    path: data/split_20250821_184448.parquet
- config_name: split_20250821_185537
  data_files:
  - split: train
    path: data/split_20250821_185537.parquet
- config_name: split_20250821_191036
  data_files:
  - split: train
    path: data/split_20250821_191036.parquet
- config_name: split_20250821_192503
  data_files:
  - split: train
    path: data/split_20250821_192503.parquet
- config_name: split_20250821_194436
  data_files:
  - split: train
    path: data/split_20250821_194436.parquet
- config_name: split_20250821_195938
  data_files:
  - split: train
    path: data/split_20250821_195938.parquet
- config_name: split_20250821_200935
  data_files:
  - split: train
    path: data/split_20250821_200935.parquet
- config_name: split_20250821_201430
  data_files:
  - split: train
    path: data/split_20250821_201430.parquet
- config_name: split_20250821_203929
  data_files:
  - split: train
    path: data/split_20250821_203929.parquet
- config_name: split_20250822_081634
  data_files:
  - split: train
    path: data/split_20250822_081634.parquet
- config_name: split_20250823_101844
  data_files:
  - split: train
    path: data/split_20250823_101844.parquet
- config_name: split_20250823_212018
  data_files:
  - split: train
    path: data/split_20250823_212018.parquet
- config_name: split_20250824_091637
  data_files:
  - split: train
    path: data/split_20250824_091637.parquet
- config_name: split_20250825_011818
  data_files:
  - split: train
    path: data/split_20250825_011818.parquet
- config_name: split_20250826_011735
  data_files:
  - split: train
    path: data/split_20250826_011735.parquet
- config_name: split_20250826_201630
  data_files:
  - split: train
    path: data/split_20250826_201630.parquet
- config_name: split_20250827_171634
  data_files:
  - split: train
    path: data/split_20250827_171634.parquet
- config_name: split_20250828_171741
  data_files:
  - split: train
    path: data/split_20250828_171741.parquet
- config_name: split_20250829_152007
  data_files:
  - split: train
    path: data/split_20250829_152007.parquet
- config_name: split_20250830_121729
  data_files:
  - split: train
    path: data/split_20250830_121729.parquet
- config_name: split_20250831_101744
  data_files:
  - split: train
    path: data/split_20250831_101744.parquet
- config_name: split_20250901_051630
  data_files:
  - split: train
    path: data/split_20250901_051630.parquet
- config_name: split_20250901_221746
  data_files:
  - split: train
    path: data/split_20250901_221746.parquet
- config_name: split_20250902_181639
  data_files:
  - split: train
    path: data/split_20250902_181639.parquet
- config_name: split_20250903_171626
  data_files:
  - split: train
    path: data/split_20250903_171626.parquet
- config_name: split_20250904_141819
  data_files:
  - split: train
    path: data/split_20250904_141819.parquet
- config_name: split_20250905_112051
  data_files:
  - split: train
    path: data/split_20250905_112051.parquet
- config_name: split_20250906_101618
  data_files:
  - split: train
    path: data/split_20250906_101618.parquet
- config_name: split_20250907_061726
  data_files:
  - split: train
    path: data/split_20250907_061726.parquet
- config_name: split_20250908_031640
  data_files:
  - split: train
    path: data/split_20250908_031640.parquet
- config_name: split_20250908_231634
  data_files:
  - split: train
    path: data/split_20250908_231634.parquet
- config_name: split_20250909_231638
  data_files:
  - split: train
    path: data/split_20250909_231638.parquet
- config_name: split_20250910_211645
  data_files:
  - split: train
    path: data/split_20250910_211645.parquet
- config_name: split_20250911_191641
  data_files:
  - split: train
    path: data/split_20250911_191641.parquet
- config_name: split_20250912_171724
  data_files:
  - split: train
    path: data/split_20250912_171724.parquet
- config_name: split_20250913_201617
  data_files:
  - split: train
    path: data/split_20250913_201617.parquet
- config_name: split_20250914_181635
  data_files:
  - split: train
    path: data/split_20250914_181635.parquet
- config_name: split_20250915_141646
  data_files:
  - split: train
    path: data/split_20250915_141646.parquet
dataset_info:
  features:
  - name: media_hash
    dtype: string
  - name: model_name
    dtype: string
  - name: label
    dtype: int64
  - name: timestamp
    dtype: int64
  - name: file_age_hours
    dtype: float32
  - name: media_image
    dtype: image
---

# BitMind Image Benchmarks

This dataset contains AI-generated image samples.

## Dataset Structure

Each config represents a batch upload with:
- Parquet files in `data/` containing image data and metadata

## Loading the Dataset

```python
from datasets import load_dataset

# List available configs (timestamps)
configs = ['split_20250821_110436', 'split_20250821_112432', ...]

# Load specific config
dataset = load_dataset('bitmind/bm-image-benchmarks', 'split_20250821_110436')

# Access data
for sample in dataset['train']:
    print(f"Model: {sample['model_name']}")
    print(f"Label: {sample['label']}")
    # sample['media_image'] contains the PIL Image
    image = sample['media_image']
    image.show()  # Display the image
```

## Processing Images

```python
from datasets import load_dataset
from PIL import Image

# Load dataset (images and metadata)
config = 'split_20250821_110436'  # Use your desired config
dataset = load_dataset('bitmind/bm-image-benchmarks', config)

# Process images with metadata
for sample in dataset['train']:
    image = sample['media_image']  # PIL Image object
    print(f"Model: {sample['model_name']}")
    print(f"Label: {sample['label']}")
    print(f"Hash: {sample['media_hash']}")
    
    # Your image processing code here
    # image.save(f"{sample['media_hash']}.png")
```