Create app.py

app.py

@@ -0,0 +1,60 @@
+import gradio as gr
+import torch
+from PIL import Image
+from diffusers import QwenImageEditPlusPipeline
+
+MODEL_ID = "Qwen/Qwen-Image-Edit-2509"
+LORA_REPO = "lovis93/next-scene-qwen-image-lora-2509"
+LORA_FILE = "next-scene_lora_v1-3000.safetensors"
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+dtype = torch.bfloat16 if torch.cuda.is_available() else torch.float32
+
+pipe = QwenImageEditPlusPipeline.from_pretrained(MODEL_ID, torch_dtype=dtype).to(device)
+pipe.load_lora_weights(LORA_REPO, weight_name=LORA_FILE)
+
+def next_scene(image, prompt, steps, true_cfg_scale, lora_strength, seed):
+    gen = None
+    if seed and int(seed) != 0:
+        gen = torch.Generator(device=device).manual_seed(int(seed))
+    try:
+        pipe.set_adapters(["default"], adapter_weights=[float(lora_strength)])
+    except Exception:
+        pass
+
+    kwargs = dict(
+        image=[image],
+        prompt=prompt,
+        num_inference_steps=int(steps),
+        guidance_scale=1.0,
+        generator=gen,
+    )
+    try:
+        kwargs["true_cfg_scale"] = float(true_cfg_scale)
+    except Exception:
+        pass
+
+    out = pipe(**kwargs)
+    return out.images[0]
+
+with gr.Blocks() as demo:
+    gr.Markdown("## Next Scene — Qwen-Image-Edit-2509 + LoRA")
+    with gr.Row():
+        with gr.Column():
+            inp_img = gr.Image(type="pil", label="Входной кадр (старт сцены)")
+            prompt = gr.Textbox(
+                label='Промпт (начинайте с "Next Scene: ...")',
+                value='Next Scene: camera pulls back revealing the riverside at sunset, soft rim light, subtle lens flare.'
+            )
+            steps = gr.Slider(4, 60, value=40, step=1, label="Steps")
+            true_cfg = gr.Slider(1.0, 6.0, value=3.0, step=0.5, label="true_cfg_scale")
+            lora_strength = gr.Slider(0.0, 1.2, value=0.75, step=0.05, label="LoRA strength")
+            seed = gr.Number(value=0, label="Seed (0 = random)")
+            btn = gr.Button("Сгенерировать следующий кадр")
+        with gr.Column():
+            out_img = gr.Image(label="Результат")
+
+    btn.click(next_scene, [inp_img, prompt, steps, true_cfg, lora_strength, seed], [out_img])
+
+if __name__ == "__main__":
+    demo.launch()