Spaces:
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β’
9f38f01
1
Parent(s):
304e045
move spaces.GPU
Browse files
app.py
CHANGED
@@ -162,12 +162,14 @@ def pipeline_callback(output_queue: SimpleQueue, pipe: Any, step_index: int, tim
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image = pipe.vae.decode(latents / pipe.vae.config.scaling_factor, return_dict=False)[0] # type: ignore[attr-defined]
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image = pipe.image_processor.postprocess(image, output_type="np").squeeze() # type: ignore[attr-defined]
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output_queue.put(("log", "mvs/image", rr.Image(image)))
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output_queue.put(("log", "mvs/latents", rr.Tensor(latents.squeeze())))
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return callback_kwargs
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@spaces.GPU
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def generate_mvs(input_image, sample_steps, sample_seed):
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seed_everything(sample_seed)
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@@ -200,7 +202,6 @@ def generate_mvs(input_image, sample_steps, sample_seed):
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z123_thread.join()
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@spaces.GPU
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def make3d(images: Image.Image):
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output_queue = SimpleQueue()
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handle = threading.Thread(target=_make3d, args=[output_queue, images])
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@@ -314,6 +315,8 @@ def _make3d(output_queue: SimpleQueue, images: Image.Image):
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output_queue.put(("mesh", mesh_out))
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@rr.thread_local_stream("InstantMesh")
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def log_to_rr(input_image, do_remove_background, sample_steps, sample_seed):
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preprocessed_image = preprocess(input_image, do_remove_background)
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@@ -341,6 +344,10 @@ def log_to_rr(input_image, do_remove_background, sample_steps, sample_seed):
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if msg[0] == "log":
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rr.log(msg[1], msg[2])
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yield stream.read()
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_HEADER_ = '''
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<h2><b>Official π€ Gradio Demo</b></h2><h2><a href='https://github.com/TencentARC/InstantMesh' target='_blank'><b>InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models</b></a></h2>
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image = pipe.vae.decode(latents / pipe.vae.config.scaling_factor, return_dict=False)[0] # type: ignore[attr-defined]
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image = pipe.image_processor.postprocess(image, output_type="np").squeeze() # type: ignore[attr-defined]
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# rr.log("mvs/image", rr.Image(image))
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# rr.log("mvs/latents", rr.Tensor(latents.squeeze()))
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output_queue.put(("log", "mvs/image", rr.Image(image)))
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output_queue.put(("log", "mvs/latents", rr.Tensor(latents.squeeze())))
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return callback_kwargs
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def generate_mvs(input_image, sample_steps, sample_seed):
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seed_everything(sample_seed)
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z123_thread.join()
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def make3d(images: Image.Image):
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output_queue = SimpleQueue()
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handle = threading.Thread(target=_make3d, args=[output_queue, images])
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output_queue.put(("mesh", mesh_out))
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@spaces.GPU
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@rr.thread_local_stream("InstantMesh")
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def log_to_rr(input_image, do_remove_background, sample_steps, sample_seed):
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preprocessed_image = preprocess(input_image, do_remove_background)
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if msg[0] == "log":
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rr.log(msg[1], msg[2])
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yield stream.read()
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if msg[0] == "mesh":
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mesh = msg[1]
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# return mesh
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_HEADER_ = '''
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<h2><b>Official π€ Gradio Demo</b></h2><h2><a href='https://github.com/TencentARC/InstantMesh' target='_blank'><b>InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models</b></a></h2>
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