File size: 3,414 Bytes
46e91d6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | import torch
from PIL import Image
import gradio as gr
import spaces
from diffusers import QwenImageEditPipeline
# نحدد هل فيه GPU
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
DTYPE = torch.bfloat16 if DEVICE == "cuda" else torch.float32
# نحمل المودل الأساسي Qwen Image Edit
print("Loading Qwen/Qwen-Image-Edit pipeline...")
pipe = QwenImageEditPipeline.from_pretrained(
"Qwen/Qwen-Image-Edit",
torch_dtype=DTYPE
).to(DEVICE)
pipe.set_progress_bar_config(disable=None)
# اسم ملف اللورا داخل الريبو حق FoxBaze
LORA_REPO = "FoxBaze/Try_On_Qwen_Edit_Lora_Alpha"
LORA_WEIGHT_NAME = "Try_On_Qwen_Edit_Lora.safetensors"
PROMPT_WOMAN = (
"Style the woman in the top of the image, with every article of clothing on the bottom"
)
PROMPT_MAN = (
"Style the man in the top of the image, with every article of clothing on the bottom"
)
@spaces.GPU()
def try_on(model_image, garments_image, gender):
"""
model_image: صورة الشخص (فوق)
garments_image: صورة فيها الملابس (تحت)
gender: 'woman' أو 'man'
"""
if model_image is None or garments_image is None:
raise gr.Error("Please upload both a model image and a garments image.")
# نحول من numpy array إلى PIL
model_pil = Image.fromarray(model_image).convert("RGB")
garments_pil = Image.fromarray(garments_image).convert("RGB")
# نفعّل لورا التجربة
pipe.load_lora_weights(
LORA_REPO,
weight_names=LORA_WEIGHT_NAME,
adapter_names="tryon"
)
prompt = PROMPT_WOMAN if gender == "woman" else PROMPT_MAN
inputs = {
"image": [model_pil, garments_pil], # top = الشخص, bottom = الملابس
"prompt": prompt,
"generator": torch.manual_seed(0),
"true_cfg_scale": 4.0,
"negative_prompt": " ",
"num_inference_steps": 30,
}
with torch.inference_mode():
result = pipe(**inputs)
# نشيل اللورا عشان ما تتراكم في الذاكرة بين الطلبات
pipe.delete_adapters("tryon")
output_image = result.images[0]
return output_image
with gr.Blocks() as demo:
gr.Markdown(
"""
# 👗 Qwen Try-On (FoxBaze LoRA Alpha)
Upload a **model photo** on the top, and a **garments image** on the bottom
(one subject on top row, multiple clothing items on bottom row).
The app will style the subject with all garments.
"""
)
with gr.Row():
with gr.Column():
model_image = gr.Image(
label="Top image: Model (full body preferred)",
type="numpy"
)
garments_image = gr.Image(
label="Bottom image: Garments (multiple pieces)",
type="numpy"
)
gender = gr.Radio(
["woman", "man"],
value="woman",
label="Subject gender (for prompt tuning)",
)
run_btn = gr.Button("Generate Try-On")
with gr.Column():
output_image = gr.Image(
label="Result",
interactive=False
)
run_btn.click(
fn=try_on,
inputs=[model_image, garments_image, gender],
outputs=[output_image],
)
if __name__ == "__main__":
demo.launch() |