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requirements.py

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+import gradio as gr
+import numpy as np
+import random
+import torch
+import spaces
+
+from PIL import Image
+from diffusers import FlowMatchEulerDiscreteScheduler
+from optimization import optimize_pipeline_
+from qwenimage.pipeline_qwenimage_edit_plus import QwenImageEditPlusPipeline
+from qwenimage.transformer_qwenimage import QwenImageTransformer2DModel
+from qwenimage.qwen_fa3_processor import QwenDoubleStreamAttnProcessorFA3
+
+import math
+from huggingface_hub import hf_hub_download
+from safetensors.torch import load_file
+
+from PIL import Image
+import os
+import gradio as gr
+from gradio_client import Client, handle_file
+import tempfile
+from typing import Optional, Tuple, Any
+
+
+# --- Model Loading ---
+dtype = torch.bfloat16
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+pipe = QwenImageEditPlusPipeline.from_pretrained(
+    "Qwen/Qwen-Image-Edit-2509",
+    transformer=QwenImageTransformer2DModel.from_pretrained(
+        "linoyts/Qwen-Image-Edit-Rapid-AIO",
+        subfolder='transformer',
+        torch_dtype=dtype,
+        device_map='cuda'
+    ),
+    torch_dtype=dtype
+).to(device)
+
+pipe.load_lora_weights(
+    "dx8152/Qwen-Edit-2509-Multiple-angles",
+    weight_name="镜头转换.safetensors",
+    adapter_name="angles"
+)
+
+
+pipe.set_adapters(["angles"], adapter_weights=[1.])
+pipe.fuse_lora(adapter_names=["angles"], lora_scale=1.25)
+pipe.unload_lora_weights()
+
+pipe.transformer.__class__ = QwenImageTransformer2DModel
+pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
+
+optimize_pipeline_(
+    pipe,
+    image=[Image.new("RGB", (1024, 1024)), Image.new("RGB", (1024, 1024))],
+    prompt="prompt"
+)
+
+MAX_SEED = np.iinfo(np.int32).max
+
+
+def _generate_video_segment(
+    input_image_path: str,
+    output_image_path: str,
+    prompt: str,
+    request: gr.Request
+) -> str:
+    """
+    Generate a single video segment between two frames by calling an external
+    Wan 2.2 image-to-video service hosted on Hugging Face Spaces.
+
+    This helper function is used internally when the user asks to create
+    a video between the input and output images.
+
+    Args:
+        input_image_path (str):
+            Path to the starting frame image on disk.
+        output_image_path (str):
+            Path to the ending frame image on disk.
+        prompt (str):
+            Text prompt describing the camera movement / transition.
+        request (gr.Request):
+            Gradio request object, used here to forward the `x-ip-token`
+            header to the downstream Space for authentication/rate limiting.
+
+    Returns:
+        str:
+            A string returned by the external service, usually a URL or path
+            to the generated video.
+    """
+    x_ip_token = request.headers['x-ip-token']
+    video_client = Client(
+        "multimodalart/wan-2-2-first-last-frame",
+        headers={"x-ip-token": x_ip_token}
+    )
+    result = video_client.predict(
+        start_image_pil=handle_file(input_image_path),
+        end_image_pil=handle_file(output_image_path),
+        prompt=prompt,
+        api_name="/generate_video",
+    )
+    return result[0]["video"]
+
+
+def build_camera_prompt(
+    rotate_deg: float = 0.0,
+    move_forward: float = 0.0,
+    vertical_tilt: float = 0.0,
+    wideangle: bool = False
+) -> str:
+    """
+    Build a camera movement prompt based on the chosen controls.
+
+    This converts the provided control values into a prompt instruction with the corresponding trigger words for the multiple-angles LoRA.
+
+    Args:
+        rotate_deg (float, optional):
+            Horizontal rotation in degrees. Positive values rotate left,
+            negative values rotate right. Defaults to 0.0.
+        move_forward (float, optional):
+            Forward movement / zoom factor. Larger values imply moving the
+            camera closer or into a close-up. Defaults to 0.0.
+        vertical_tilt (float, optional):
+            Vertical angle of the camera:
+            - Negative ≈ bird's-eye view
+            - Positive ≈ worm's-eye view
+            Defaults to 0.0.
+        wideangle (bool, optional):
+            Whether to switch to a wide-angle lens style. Defaults to False.
+
+    Returns:
+        str:
+            A text prompt describing the camera motion. If no controls are
+            active, returns `"no camera movement"`.
+    """
+    prompt_parts = []
+
+    # Rotation
+    if rotate_deg != 0:
+        direction = "left" if rotate_deg > 0 else "right"
+        if direction == "left":
+            prompt_parts.append(
+                f"将镜头向左旋转{abs(rotate_deg)}度 Rotate the camera {abs(rotate_deg)} degrees to the left."
+            )
+        else:
+            prompt_parts.append(
+                f"将镜头向右旋转{abs(rotate_deg)}度 Rotate the camera {abs(rotate_deg)} degrees to the right."
+            )
+
+    # Move forward / close-up
+    if move_forward > 5:
+        prompt_parts.append("将镜头转为特写镜头 Turn the camera to a close-up.")
+    elif move_forward >= 1:
+        prompt_parts.append("将镜头向前移动 Move the camera forward.")
+
+    # Vertical tilt
+    if vertical_tilt <= -1:
+        prompt_parts.append("将相机转向鸟瞰视角 Turn the camera to a bird's-eye view.")
+    elif vertical_tilt >= 1:
+        prompt_parts.append("将相机切换到仰视视角 Turn the camera to a worm's-eye view.")
+
+    # Lens option
+    if wideangle:
+        prompt_parts.append(" 将镜头转为广角镜头 Turn the camera to a wide-angle lens.")
+
+    final_prompt = " ".join(prompt_parts).strip()
+    return final_prompt if final_prompt else "no camera movement"
+
+
+@spaces.GPU
+def infer_camera_edit(
+    image: Optional[Image.Image] = None,
+    rotate_deg: float = 0.0,
+    move_forward: float = 0.0,
+    vertical_tilt: float = 0.0,
+    wideangle: bool = False,
+    seed: int = 0,
+    randomize_seed: bool = True,
+    true_guidance_scale: float = 1.0,
+    num_inference_steps: int = 4,
+    height: Optional[int] = None,
+    width: Optional[int] = None,
+    prev_output: Optional[Image.Image] = None,
+) -> Tuple[Image.Image, int, str]:
+    """
+    Edit the camera angles/view of an image with Qwen Image Edit 2509 and dx8152's Qwen-Edit-2509-Multiple-angles LoRA.
+
+    Applies a camera-style transformation (rotation, zoom, tilt, lens)
+    to an input image.
+
+    Args:
+        image (PIL.Image.Image | None, optional):
+            Input image to edit. If `None`, the function will instead try to
+            use `prev_output`. At least one of `image` or `prev_output` must
+            be available. Defaults to None.
+        rotate_deg (float, optional):
+            Horizontal rotation in degrees (-90, -45, 0, 45, 90). Positive values rotate
+            to the left, negative to the right. Defaults to 0.0.
+        move_forward (float, optional):
+            Forward movement / zoom factor (0, 5, 10). Higher values move the
+            camera closer; values >5 switch to a close-up style. Defaults to 0.0.
+        vertical_tilt (float, optional):
+            Vertical tilt (-1 to 1). -1 ≈ bird's-eye view, +1 ≈ worm's-eye view.
+            Defaults to 0.0.
+        wideangle (bool, optional):
+            Whether to use a wide-angle lens style. Defaults to False.
+        seed (int, optional):
+            Random seed for the generation. Ignored if `randomize_seed=True`.
+            Defaults to 0.
+        randomize_seed (bool, optional):
+            If True, a random seed (0..MAX_SEED) is chosen per call.
+            Defaults to True.
+        true_guidance_scale (float, optional):
+            CFG / guidance scale controlling prompt adherence.
+            Defaults to 1.0 since the demo is using a distilled transformer for faster inference.
+        num_inference_steps (int, optional):
+            Number of inference steps. Defaults to 4.
+        height (int, optional):
+            Output image height. Must typically be a multiple of 8.
+            If set to 0, the model will infer a size. Defaults to 1024 if none is provided.
+        width (int, optional):
+            Output image width. Must typically be a multiple of 8.
+            If set to 0, the model will infer a size. Defaults to 1024 if none is provided.
+        prev_output (PIL.Image.Image | None, optional):
+            Previous output image to use as input when no new image is uploaded.
+            Defaults to None.
+
+    Returns:
+        Tuple[PIL.Image.Image, int, str]:
+            - The edited output image.
+            - The actual seed used for generation.
+            - The constructed camera prompt string.
+    """
+    progress = gr.Progress(track_tqdm=True)
+    
+    prompt = build_camera_prompt(rotate_deg, move_forward, vertical_tilt, wideangle)
+    print(f"Generated Prompt: {prompt}")
+
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    generator = torch.Generator(device=device).manual_seed(seed)
+
+    # Choose input image (prefer uploaded, else last output)
+    pil_images = []
+    if image is not None:
+        if isinstance(image, Image.Image):
+            pil_images.append(image.convert("RGB"))
+        elif hasattr(image, "name"):
+            pil_images.append(Image.open(image.name).convert("RGB"))
+    elif prev_output:
+        pil_images.append(prev_output.convert("RGB"))
+
+    if len(pil_images) == 0:
+        raise gr.Error("Please upload an image first.")
+
+    if prompt == "no camera movement":
+        return image, seed, prompt
+
+    result = pipe(
+        image=pil_images,
+        prompt=prompt,
+        height=height if height != 0 else None,
+        width=width if width != 0 else None,
+        num_inference_steps=num_inference_steps,
+        generator=generator,
+        true_cfg_scale=true_guidance_scale,
+        num_images_per_prompt=1,
+    ).images[0]
+
+    return result, seed, prompt
+
+
+def create_video_between_images(
+    input_image: Optional[Image.Image],
+    output_image: Optional[np.ndarray],
+    prompt: str,
+    request: gr.Request
+) -> str:
+    """
+    Create a short transition video between the input and output images via the 
+    Wan 2.2 first-last-frame Space.
+
+    Args:
+        input_image (PIL.Image.Image | None):
+            Starting frame image (the original / previous view).
+        output_image (numpy.ndarray | None):
+            Ending frame image - the output image with the the edited camera angles.
+        prompt (str):
+            The camera movement prompt used to describe the transition.
+        request (gr.Request):
+            Gradio request object, used to forward the `x-ip-token` header
+            to the video generation app.
+
+    Returns:
+        str:
+            a path pointing to the generated video.
+
+    Raises:
+        gr.Error:
+            If either image is missing or if the video generation fails.
+    """
+    if input_image is None or output_image is None:
+        raise gr.Error("Both input and output images are required to create a video.")
+
+    try:
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as tmp:
+            input_image.save(tmp.name)
+            input_image_path = tmp.name
+
+        output_pil = Image.fromarray(output_image.astype('uint8'))
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as tmp:
+            output_pil.save(tmp.name)
+            output_image_path = tmp.name
+
+        video_path = _generate_video_segment(
+            input_image_path,
+            output_image_path,
+            prompt if prompt else "Camera movement transformation",
+            request
+        )
+        return video_path
+    except Exception as e:
+        raise gr.Error(f"Video generation failed: {e}")
+
+
+# --- UI ---
+css = '''#col-container { max-width: 800px; margin: 0 auto; }
+.dark .progress-text{color: white !important}
+#examples{max-width: 800px; margin: 0 auto; }'''
+
+
+def reset_all() -> list:
+    """
+    Reset all camera control knobs and flags to their default values.
+
+    This is used by the "Reset" button to set:
+    - rotate_deg = 0
+    - move_forward = 0
+    - vertical_tilt = 0
+    - wideangle = False
+    - is_reset = True
+
+    Returns:
+        list:
+            A list of values matching the order of the reset outputs:
+            [rotate_deg, move_forward, vertical_tilt, wideangle, is_reset, True]
+    """
+    return [0, 0, 0, 0, False, True]
+
+
+def end_reset() -> bool:
+    """
+    Mark the end of a reset cycle.
+
+    This helper is chained after `reset_all` to set the internal
+    `is_reset` flag back to False, so that live inference can resume.
+
+    Returns:
+        bool:
+            Always returns False.
+    """
+    return False
+
+
+def update_dimensions_on_upload(
+    image: Optional[Image.Image]
+) -> Tuple[int, int]:
+    """
+    Compute recommended (width, height) for the output resolution when an
+    image is uploaded while preserveing the aspect ratio.
+
+    Args:
+        image (PIL.Image.Image | None):
+            The uploaded image. If `None`, defaults to (1024, 1024).
+
+    Returns:
+        Tuple[int, int]:
+            The new (width, height).
+    """
+    if image is None:
+        return 1024, 1024
+
+    original_width, original_height = image.size
+
+    if original_width > original_height:
+        new_width = 1024
+        aspect_ratio = original_height / original_width
+        new_height = int(new_width * aspect_ratio)
+    else:
+        new_height = 1024
+        aspect_ratio = original_width / original_height
+        new_width = int(new_height * aspect_ratio)
+
+    # Ensure dimensions are multiples of 8
+    new_width = (new_width // 8) * 8
+    new_height = (new_height // 8) * 8
+
+    return new_width, new_height
+
+
+with gr.Blocks(theme=gr.themes.Citrus(), css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown("## 🎬 Qwen Image Edit — Camera Angle Control")
+        gr.Markdown("""
+            Qwen Image Edit 2509 for Camera Control ✨ 
+            Using [dx8152's Qwen-Edit-2509-Multiple-angles LoRA](https://huggingface.co/dx8152/Qwen-Edit-2509-Multiple-angles) and [Phr00t/Qwen-Image-Edit-Rapid-AIO](https://huggingface.co/Phr00t/Qwen-Image-Edit-Rapid-AIO/tree/main) for 4-step inference 💨
+            """
+        )
+
+        with gr.Row():
+            with gr.Column():
+                image = gr.Image(label="Input Image", type="pil")
+                prev_output = gr.Image(value=None, visible=False)
+                is_reset = gr.Checkbox(value=False, visible=False)
+
+                with gr.Tab("Camera Controls"):
+                    rotate_deg = gr.Slider(
+                        label="Rotate Right-Left (degrees °)",
+                        minimum=-90,
+                        maximum=90,
+                        step=45,
+                        value=0
+                    )
+                    move_forward = gr.Slider(
+                        label="Move Forward → Close-Up",
+                        minimum=0,
+                        maximum=10,
+                        step=5,
+                        value=0
+                    )
+                    vertical_tilt = gr.Slider(
+                        label="Vertical Angle (Bird ↔ Worm)",
+                        minimum=-1,
+                        maximum=1,
+                        step=1,
+                        value=0
+                    )
+                    wideangle = gr.Checkbox(label="Wide-Angle Lens", value=False)
+                with gr.Row():
+                    reset_btn = gr.Button("Reset")
+                    run_btn = gr.Button("Generate", variant="primary")
+
+                with gr.Accordion("Advanced Settings", open=False):
+                    seed = gr.Slider(
+                        label="Seed",
+                        minimum=0,
+                        maximum=MAX_SEED,
+                        step=1,
+                        value=0
+                    )
+                    randomize_seed = gr.Checkbox(
+                        label="Randomize Seed",
+                        value=True
+                    )
+                    true_guidance_scale = gr.Slider(
+                        label="True Guidance Scale",
+                        minimum=1.0,
+                        maximum=10.0,
+                        step=0.1,
+                        value=1.0
+                    )
+                    num_inference_steps = gr.Slider(
+                        label="Inference Steps",
+                        minimum=1,
+                        maximum=40,
+                        step=1,
+                        value=4
+                    )
+                    height = gr.Slider(
+                        label="Height",
+                        minimum=256,
+                        maximum=2048,
+                        step=8,
+                        value=1024
+                    )
+                    width = gr.Slider(
+                        label="Width",
+                        minimum=256,
+                        maximum=2048,
+                        step=8,
+                        value=1024
+                    )
+
+            with gr.Column():
+                result = gr.Image(label="Output Image", interactive=False)
+                prompt_preview = gr.Textbox(label="Processed Prompt", interactive=False)
+                create_video_button = gr.Button(
+                    "🎥 Create Video Between Images",
+                    variant="secondary",
+                    visible=False
+                )
+                with gr.Group(visible=False) as video_group:
+                    video_output = gr.Video(
+                        label="Generated Video",
+                        show_download_button=True,
+                        autoplay=True
+                    )
+
+    inputs = [
+        image, rotate_deg, move_forward,
+        vertical_tilt, wideangle,
+        seed, randomize_seed, true_guidance_scale, num_inference_steps, height, width, prev_output
+    ]
+    outputs = [result, seed, prompt_preview]
+
+    # Reset behavior
+    reset_btn.click(
+        fn=reset_all,
+        inputs=None,
+        outputs=[rotate_deg, move_forward, vertical_tilt, wideangle, is_reset],
+        queue=False
+    ).then(fn=end_reset, inputs=None, outputs=[is_reset], queue=False)
+
+    # Manual generation with video button visibility control
+    def infer_and_show_video_button(*args: Any):
+        """
+        Wrapper around `infer_camera_edit` that also controls the visibility
+        of the 'Create Video Between Images' button.
+
+        The first argument in `args` is expected to be the input image; if both
+        input and output images are present, the video button is shown.
+
+        Args:
+            *args:
+                Positional arguments forwarded directly to `infer_camera_edit`.
+
+        Returns:
+            tuple:
+                (output_image, seed, prompt, video_button_visibility_update)
+        """
+        result_img, result_seed, result_prompt = infer_camera_edit(*args)
+        # Show video button if we have both input and output images
+        show_button = args[0] is not None and result_img is not None
+        return result_img, result_seed, result_prompt, gr.update(visible=show_button)
+
+    run_event = run_btn.click(
+        fn=infer_and_show_video_button,
+        inputs=inputs,
+        outputs=outputs + [create_video_button]
+    )
+
+    # Video creation
+    create_video_button.click(
+        fn=lambda: gr.update(visible=True),
+        outputs=[video_group],
+        api_name=False
+    ).then(
+        fn=create_video_between_images,
+        inputs=[image, result, prompt_preview],
+        outputs=[video_output],
+        api_name=False
+    )
+
+    # Examples
+    gr.Examples(
+        examples=[
+            ["tool_of_the_sea.png", 90, 0, 0, False, 0, True, 1.0, 4, 568, 1024],
+            ["monkey.jpg", -90, 0, 0, False, 0, True, 1.0, 4, 704, 1024],
+            ["metropolis.jpg", 0, 0, -1, False, 0, True, 1.0, 4, 816, 1024],
+            ["disaster_girl.jpg", -45, 0, 1, False, 0, True, 1.0, 4, 768, 1024],
+            ["grumpy.png", 90, 0, 1, False, 0, True, 1.0, 4, 576, 1024]
+        ],
+        inputs=[
+            image, rotate_deg, move_forward,
+            vertical_tilt, wideangle,
+            seed, randomize_seed, true_guidance_scale, num_inference_steps, height, width
+        ],
+        outputs=outputs,
+        fn=infer_camera_edit,
+        cache_examples="lazy",
+        elem_id="examples"
+    )
+
+    # Image upload triggers dimension update and control reset
+    image.upload(
+        fn=update_dimensions_on_upload,
+        inputs=[image],
+        outputs=[width, height]
+    ).then(
+        fn=reset_all,
+        inputs=None,
+        outputs=[rotate_deg, move_forward, vertical_tilt, wideangle, is_reset],
+        queue=False
+    ).then(
+        fn=end_reset,
+        inputs=None,
+        outputs=[is_reset],
+        queue=False
+    )
+
+    # Live updates
+    def maybe_infer(
+        is_reset: bool,
+        progress: gr.Progress = gr.Progress(track_tqdm=True),
+        *args: Any
+    ):
+        if is_reset:
+            return gr.update(), gr.update(), gr.update(), gr.update()
+        else:
+            result_img, result_seed, result_prompt = infer_camera_edit(*args)
+            # Show video button if we have both input and output
+            show_button = args[0] is not None and result_img is not None
+            return result_img, result_seed, result_prompt, gr.update(visible=show_button)
+
+    control_inputs = [
+        image, rotate_deg, move_forward,
+        vertical_tilt, wideangle,
+        seed, randomize_seed, true_guidance_scale, num_inference_steps, height, width, prev_output
+    ]
+    control_inputs_with_flag = [is_reset] + control_inputs
+
+    for control in [rotate_deg, move_forward, vertical_tilt]:
+        control.release(
+            fn=maybe_infer,
+            inputs=control_inputs_with_flag,
+            outputs=outputs + [create_video_button]
+        )
+
+    wideangle.input(
+        fn=maybe_infer,
+        inputs=control_inputs_with_flag,
+        outputs=outputs + [create_video_button]
+    )
+
+    run_event.then(lambda img, *_: img, inputs=[result], outputs=[prev_output])
+
+    gr.api(infer_camera_edit, api_name="infer_edit_camera_angles")
+    gr.api(create_video_between_images, api_name="create_video_between_images")
+
+demo.launch(mcp_server=True, show_api=True)

requirements.txt

@@ -0,0 +1,13 @@
+git+https://github.com/huggingface/diffusers.git
+
+
+
+transformers
+accelerate
+safetensors
+sentencepiece
+dashscope
+kernels
+torchvision
+peft
+torchao==0.11.0