---
license: mit
dataset_info:
  features:
  - name: id
    dtype: string
  - name: control_images
    list: image
  - name: control_mask
    dtype: image
  - name: target_image
    dtype: image
  - name: prompt
    dtype: string
  splits:
  - name: train
    num_bytes: 8458819
    num_examples: 20
  - name: test
    num_bytes: 2807087
    num_examples: 2
  download_size: 11241583
  dataset_size: 11265906
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
task_categories:
- image-to-image
language:
- en
tags:
- face_seg
pretty_name: tsien
size_categories:
- n<1K
---
This is the dataset used for FluxKontext or Qwen-Image-Edit training with the task image-text2image.
This is a good adtaset that can very fine the effect of finetuning, where the base model is not good at

Refer this for the lora finetune model [**qwen-image-edit-lora-face-segmentation**](https://huggingface.co/TsienDragon/qwen-image-edit-lora-face-segmentation)

Usage of the dataset
```
dd = load_editing_dataset("TsienDragon/face_segmentation_20")
sample = dd["test"][0]
```

Example of the data structure
```bash
DATASET_ROOT/train
├── control_images
│   ├── 060002_4_028450_FEMALE_30.png
│   ├── 060002_4_028450_FEMALE_30_1.png
│   ├── 060002_4_028450_FEMALE_30_2.jpg
│   ├── 060002_4_028450_FEMALE_30_mask.png
│   ├── 060003_4_028451_FEMALE_65.png
│   ├── 060003_4_028451_FEMALE_65_1.png
│   └── 060003_4_028451_FEMALE_65_mask.png
└── training_images
    ├── 060002_4_028450_FEMALE_30.txt
    ├── 060002_4_028450_FEMALE_30.png
    ├── 060003_4_028451_FEMALE_65.txt
    └── 060003_4_028451_FEMALE_65.png
```