update_example entity control

examples/EntityControl/entity_control_ipadapter.py

@@ -0,0 +1,51 @@
+import torch
+from diffsynth import ModelManager, FluxImagePipeline, download_customized_models
+from examples.EntityControl.utils import visualize_masks
+from PIL import Image
+import requests
+from io import BytesIO
+
+lora_path = download_customized_models(
+    model_id="DiffSynth-Studio/Eligen",
+    origin_file_path="model_bf16.safetensors",
+    local_dir="models/lora/entity_control"
+)[0]
+model_manager = ModelManager(torch_dtype=torch.bfloat16, device="cuda", model_id_list=["FLUX.1-dev", "InstantX/FLUX.1-dev-IP-Adapter"])
+model_manager.load_lora(lora_path, lora_alpha=1.)
+pipe = FluxImagePipeline.from_model_manager(model_manager)
+
+# prepare inputs
+image_shape = 1024
+seed = 4
+# set True to apply regional attention in negative prompt prediction for better results with more time
+use_seperated_negtive_prompt = False
+mask_urls = [
+    'https://github.com/user-attachments/assets/e6745b3f-ab2b-4612-9bb5-b7235474a9a4',
+    'https://github.com/user-attachments/assets/5ddf9a89-32fa-4540-89ad-e956130942b3',
+    'https://github.com/user-attachments/assets/9d8a0bb0-6817-497e-af85-44f2512afe79'
+]
+# prepare entity masks, entity prompts, global prompt and negative prompt
+masks = []
+for url in mask_urls:
+    response = requests.get(url)
+    mask = Image.open(BytesIO(response.content)).resize((image_shape, image_shape), resample=Image.NEAREST)
+    masks.append(mask)
+entity_prompts = ['A girl', 'hat', 'sunset']
+global_prompt = "A girl wearing a hat, looking at the sunset"
+negative_prompt = "worst quality, low quality, monochrome, zombie, interlocked fingers, Aissist, cleavage, nsfw"
+
+response = requests.get('https://github.com/user-attachments/assets/019bbfaa-04b3-4de6-badb-32b67c29a1bc')
+reference_img = Image.open(BytesIO(response.content)).convert('RGB').resize((image_shape, image_shape))
+
+torch.manual_seed(seed)
+image = pipe(
+    prompt=global_prompt,
+    cfg_scale=3.0,
+    negative_prompt=negative_prompt,
+    num_inference_steps=50, embedded_guidance=3.5, height=image_shape, width=image_shape,
+    entity_prompts=entity_prompts, entity_masks=masks,
+    use_seperated_negtive_prompt=use_seperated_negtive_prompt,
+    ipadapter_images=[reference_img], ipadapter_scale=0.7
+)
+image.save(f"styled_entity_control.png")
+visualize_masks(image, masks, entity_prompts, f"styled_entity_control_with_mask.png")