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aigc-apps-EasyAnimate/scripts/README_t2i.md
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2024-05-26 21:05:24 +08:00

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## EN、Training text to image model
### i、Base on diffusers format
The format of dataset can be set as diffuser format.
If using the diffusers format dataset for training.
```
📦 project/
├── 📂 datasets/
│ ├── 📂 diffusers_datasets/
│ ├── 📂 train/
│ │ ├── 📄 00000001.jpg
│ │ ├── 📄 00000002.jpg
│ │ └── 📄 .....
│ └── 📄 metadata.jsonl
```
Then, set scripts/train_t2i.sh.
```
export DATASET_NAME="datasets/diffusers_datasets/"
...
train_data_format="diffusers"
```
Then, we run scripts/train_t2i.sh.
```sh
sh scripts/train_t2i.sh
```
### ii、Base on internal dataset
If using the internal dataset for training, you need to format the dataset firstly.
You need to arrange the dataset in this format.
```
📦 project/
├── 📂 datasets/
│ ├── 📂 internal_datasets/
│ ├── 📂 train/
│ │ ├── 📄 00000001.jpg
│ │ ├── 📄 00000002.jpg
│ │ └── 📄 .....
│ └── 📄 json_of_internal_datasets.json
```
The json_of_internal_datasets.json is a standard JSON file, as shown in below:
```json
[
{
"file_path": "train/00000001.jpg",
"text": "A group of young men in suits and sunglasses are walking down a city street.",
"type": "image"
},
{
"file_path": "train/00000002.jpg",
"text": "A notepad with a drawing of a woman on it.",
"type": "image"
}
.....
]
```
The file_path in the json needs to be set as relative path.
Then, set scripts/train_t2i.sh.
```
export DATASET_NAME="datasets/internal_datasets/"
export DATASET_META_NAME="datasets/internal_datasets/json_of_internal_datasets.json"
...
train_data_format="normal"
```
Then, we run scripts/train_t2i.sh.
```sh
sh scripts/train_t2i.sh
```
## CN、训练基础文生图模型
### i、基于diffusers格式
数据集的格式可以设置为diffusers格式。
```
📦 project/
├── 📂 datasets/
│ ├── 📂 diffusers_datasets/
│ ├── 📂 train/
│ │ ├── 📄 00000001.jpg
│ │ ├── 📄 00000002.jpg
│ │ └── 📄 .....
│ └── 📄 metadata.jsonl
```
然后,进入scripts/train_t2i.sh进行设置。
```
export DATASET_NAME="datasets/diffusers_datasets/"
...
train_data_format="diffusers"
```
最后运行scripts/train_t2i.sh。
```sh
sh scripts/train_t2i.sh
```
### ii、基于自建数据集
如果使用自建数据集进行训练,则需要首先格式化数据集。
您需要以这种格式排列数据集。
```
📦 project/
├── 📂 datasets/
│ ├── 📂 internal_datasets/
│ ├── 📂 train/
│ │ ├── 📄 00000001.jpg
│ │ ├── 📄 00000002.jpg
│ │ └── 📄 .....
│ └── 📄 json_of_internal_datasets.json
```
json_of_internal_datasets.json是一个标准的json文件,如下所示:
```json
[
{
"file_path": "train/00000001.jpg",
"text": "A group of young men in suits and sunglasses are walking down a city street.",
"type": "image"
},
{
"file_path": "train/00000002.jpg",
"text": "A notepad with a drawing of a woman on it.",
"type": "image"
}
.....
]
```
json中的file_path需要设置为相对路径。
然后,进入scripts/train_t2i.sh进行设置。
```
export DATASET_NAME="datasets/internal_datasets/"
export DATASET_META_NAME="datasets/internal_datasets/json_of_internal_datasets.json"
...
train_data_format="normal"
```
最后运行scripts/train_t2i.sh。
```sh
sh scripts/train_t2i.sh
```