| import torch |
| from diffsynth import ModelManager, FluxImagePipeline, download_models |
| from diffsynth.controlnets.processors import Annotator |
| import numpy as np |
| from PIL import Image |
|
|
|
|
| download_models(["FLUX.1-dev"]) |
| model_manager = ModelManager(torch_dtype=torch.bfloat16, device="cuda") |
| model_manager.load_models([ |
| "models/FLUX/FLUX.1-dev/text_encoder/model.safetensors", |
| "models/FLUX/FLUX.1-dev/text_encoder_2", |
| "models/FLUX/FLUX.1-dev/ae.safetensors", |
| "models/ostris/Flex.2-preview/Flex.2-preview.safetensors" |
| ]) |
| pipe = FluxImagePipeline.from_model_manager(model_manager) |
|
|
| image = pipe( |
| prompt="portrait of a beautiful Asian girl, long hair, red t-shirt, sunshine, beach", |
| num_inference_steps=50, embedded_guidance=3.5, |
| seed=0 |
| ) |
| image.save("image_1.jpg") |
|
|
| mask = np.zeros((1024, 1024, 3), dtype=np.uint8) |
| mask[200:400, 400:700] = 255 |
| mask = Image.fromarray(mask) |
| mask.save("image_mask.jpg") |
|
|
| inpaint_image = image |
|
|
| image = pipe( |
| prompt="portrait of a beautiful Asian girl with sunglasses, long hair, red t-shirt, sunshine, beach", |
| num_inference_steps=50, embedded_guidance=3.5, |
| flex_inpaint_image=inpaint_image, flex_inpaint_mask=mask, |
| seed=4 |
| ) |
| image.save("image_2.jpg") |
|
|
| control_image = Annotator("canny")(image) |
| control_image.save("image_control.jpg") |
|
|
| image = pipe( |
| prompt="portrait of a beautiful Asian girl with sunglasses, long hair, yellow t-shirt, sunshine, beach", |
| num_inference_steps=50, embedded_guidance=3.5, |
| flex_control_image=control_image, |
| seed=4 |
| ) |
| image.save("image_3.jpg") |
|
|
