Spaces:
Running
on
Zero
Running
on
Zero
update multiimages api
Browse files
app.py
CHANGED
@@ -1,4 +1,5 @@
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import gradio as gr
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import spaces
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from gradio_litmodel3d import LitModel3D
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import json
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@@ -20,6 +21,54 @@ MAX_SEED = np.iinfo(np.int32).max
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TMP_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'tmp')
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os.makedirs(TMP_DIR, exist_ok=True)
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def start_session(req: gr.Request):
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user_dir = os.path.join(TMP_DIR, str(req.session_hash))
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@@ -160,8 +209,9 @@ def image_to_3d(
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},
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else:
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outputs = pipeline.run_multi_image(
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-
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seed=seed,
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formats=["gaussian", "mesh"],
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preprocess_image=False,
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@@ -335,9 +385,8 @@ def test_for_api_gen(image: Image.Image) -> Image.Image:
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"""
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return image
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def update_is_multiimage(
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return "true" if
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with gr.Blocks(delete_cache=(600, 600)) as demo:
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@@ -378,8 +427,17 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
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*NOTE: this is an experimental algorithm without training a specialized model. It may not produce the best results for all images, especially those having different poses or inconsistent details.*
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""")
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is_multiimage = gr.Radio(
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-
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with gr.Accordion(label="Generation Settings", open=False):
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seed = gr.Slider(0, MAX_SEED, label="Seed", value=0, step=1)
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import gradio as gr
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from gradio.events import SelectData
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import spaces
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from gradio_litmodel3d import LitModel3D
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import json
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TMP_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'tmp')
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os.makedirs(TMP_DIR, exist_ok=True)
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def to_pil_list(
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multiimages: List[
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Union[
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Image.Image,
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Tuple[Image.Image, str],
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gr.File,
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Tuple[gr.File, str],
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str, # fallback: plain path
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Path
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]
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]
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) -> List[Image.Image]:
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"""
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Convert a heterogeneous `multiimages` list into a homogeneous
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`List[Image.Image]`.
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Accepts elements in any of the following forms:
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• PIL.Image
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• (PIL.Image, caption)
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• gr.File (gr.File.name is the temp‑file path)
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• (gr.File, caption)
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• str / pathlib.Path (direct file path)
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Returns:
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List[Image.Image] -- guaranteed PIL images
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"""
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pil_imgs: List[Image.Image] = []
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for item in multiimages:
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# Unpack tuple/list, keep first element
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if isinstance(item, (tuple, list)):
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item = item[0]
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if isinstance(item, Image.Image): # already PIL
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pil_imgs.append(item)
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elif hasattr(item, "name"): # gr.File
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pil_imgs.append(Image.open(item.name))
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elif isinstance(item, (str, Path)): # file path
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pil_imgs.append(Image.open(item))
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else:
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raise TypeError(
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f"Unsupported element in multiimages: {type(item)}"
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)
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return pil_imgs
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def start_session(req: gr.Request):
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user_dir = os.path.join(TMP_DIR, str(req.session_hash))
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},
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else:
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pil_images = to_pil_list(multiimages)
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outputs = pipeline.run_multi_image(
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pil_images,
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seed=seed,
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formats=["gaussian", "mesh"],
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preprocess_image=False,
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"""
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return image
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def update_is_multiimage(event: SelectData):
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return "true" if event.index == 1 else "false"
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with gr.Blocks(delete_cache=(600, 600)) as demo:
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*NOTE: this is an experimental algorithm without training a specialized model. It may not produce the best results for all images, especially those having different poses or inconsistent details.*
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""")
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is_multiimage = gr.Radio(
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choices=["true", "false"],
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value="false",
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label="Use multi-image mode",
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visible=True
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)
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input_tabs.select(
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fn=update_is_multiimage,
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outputs=is_multiimage
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)
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with gr.Accordion(label="Generation Settings", open=False):
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seed = gr.Slider(0, MAX_SEED, label="Seed", value=0, step=1)
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