Qwen Image

https://huggingface.co/Qwen/Qwen-Image
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Qwen Image is an image generation foundation model excelling in complex text rendering and precise...
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### Install Diffusers Dependencies

Source: https://huggingface.co/Qwen/Qwen-Image-Edit/blob/418bcab18188842e18720b4092510b5d1abc63a8/README.md

Install the necessary libraries to run the Qwen-Image-Edit model.

```bash
pip install -U diffusers transformers accelerate
```

```bash
pip install -U diffusers
```

--------------------------------

### Configure Model and Generation Parameters

Source: https://huggingface.co/Qwen/Qwen-Image/discussions/32/files

Examples of setting up the pipeline, defining prompt magic, and managing aspect ratios.

```python
pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
pipe = pipe.to(device)

positive_magic = {
"en": "Ultra HD, 4K, cinematic composition." # for english prompt,
"zh": "超清，4K，电影级构图" # for chinese prompt,
}

# Generate image
prompt = '''A coffee shop entrance features a chalkboard sign reading "Qwen Coffee 😊 $2 per cup," with a neon light beside it displaying "通义千问". Next to it hangs a poster showing a beautiful Chinese woman, and beneath the poster is written "π≈3.1415926-53589793-23846264-33832795-02384197". Ultra HD, 4K, cinematic composition'''

negative_prompt = " " # using an empty string if you do not have specific concept to remove

# Generate with different aspect ratios
aspect_ratios = {
"16:9": (1664, 928),
"9:16": (928, 1664),
"4:3": (1472, 1140),
"3:4": (1140, 1472)
}

width, height = aspect_ratios["16:9"]
```

--------------------------------

### Install and Use Qwen-Image-Edit with Diffusers

Source: https://huggingface.co/Qwen/Qwen-Image-Edit/discussions/1/files

Install the necessary dependencies and initialize the pipeline to perform image editing tasks.

```bash
pip install -U diffusers transformers accelerate
```

```python
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit", dtype=torch.bfloat16, device_map="cuda")

prompt = "Turn this cat into a dog"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")

image = pipe(image=input_image, prompt=prompt).images[0]
```

--------------------------------

### Install Diffusers Library

Source: https://huggingface.co/Qwen/Qwen-Image/colab

Install the diffusers library to enable model pipeline functionality.

```bash
!pip install -U diffusers
```

--------------------------------

### Attempt Multi-Image Input Configuration

Source: https://huggingface.co/Qwen/Qwen-Image/discussions/69

Example of an unsuccessful attempt to pass a list of images directly into the pipeline input dictionary.

```python
image1 = Image.open("./1.png").convert("RGB").resize((512, 512))  
image2 = Image.open("./2.png").convert("RGB").resize((512, 512))  
inputs = {  
"image": [image1, image2],  
"prompt": prompt,  
"generator": torch.manual_seed(0),  
"true_cfg_scale": 4.0,  
"negative_prompt": "",  
"num_inference_steps": 8,  
}
```

--------------------------------

### Define local model path

Source: https://huggingface.co/Qwen/Qwen-Image/discussions/27

Example of setting the model identifier to a local directory path.

```python
model_id = "Qwen/Qwen-Image"
```

```python
model_id = "./models/qwen-image"
```

--------------------------------

### Table Code Examples

Source: https://huggingface.co/Qwen/Qwen-Image/blame/b0d9cbe58a813c316e7107e15310a4347b223020/transformer/diffusion_pytorch_model.safetensors.index.json

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### Initialize and Run Qwen-Image Pipeline

Source: https://huggingface.co/Qwen/Qwen-Image/blame/80a84a33c628044c1a720c5b22b318cd25d9c20d/transformer/diffusion_pytorch_model.safetensors.index.json

This snippet demonstrates how to install the necessary dependencies, initialize the DiffusionPipeline with the Qwen-Image model, and generate an image from a text prompt.

```APIDOC
## Initialize and Run Qwen-Image Pipeline

### Description
This operation initializes the Qwen-Image model using the Hugging Face Diffusers library and generates an image based on a provided text prompt.

### Installation
```bash
pip install -U diffusers transformers accelerate
```

### Usage Example
```python
import torch
from diffusers import DiffusionPipeline

# Initialize the pipeline
# Use device_map="cuda" for GPU or "mps" for Apple Silicon
pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda")

# Define prompt and generate image
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]
```
```

--------------------------------

### Install Diffusers Dependencies

Source: https://huggingface.co/Qwen/Qwen-Image-Edit/blame/main/processor/tokenizer.json

Install the necessary libraries to run the model.

```bash
pip install -U diffusers transformers accelerate
```
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