Spaces:
Sleeping
Sleeping
Yaron Koresh
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -28,7 +28,7 @@ from diffusers import DiffusionPipeline, AnimateDiffPipeline, MotionAdapter, Eul
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#import jax
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#import jax.numpy as jnp
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from numba import cuda, njit as cpu, void, int64 as int, float64 as float, boolean as bool, uint8 as rgb
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from numba.cuda import jit as gpu, grid
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from numba.types import unicode_type as string
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from PIL.Image import fromarray as array2image
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import numpy as np
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@@ -119,6 +119,23 @@ function custom(){
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}
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"""
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# functionality
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def run(cmd):
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@@ -174,6 +191,7 @@ def generate_random_string(length):
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def calc(img,p1,p2,motion):
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global out_pipe
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global last_motion
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x = grid(1)
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@@ -295,23 +313,6 @@ def ui():
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result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=False, type='filepath', show_share_button=False))
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demo.queue().launch()
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@gpu(void())
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def pre():
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global pipe
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pipe = AnimateDiffPipeline.from_pretrained(base, vae=vae, motion_adapter=adapter, torch_dtype=dtype).to(device)
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pipe.scheduler = DDIMScheduler(
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clip_sample=False,
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beta_start=0.00085,
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beta_end=0.012,
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beta_schedule="linear",
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timestep_spacing="trailing",
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steps_offset=1
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)
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pipe.unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device=device), strict=False)
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pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin")
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pipe.enable_vae_slicing()
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pipe.enable_free_init(method="butterworth", use_fast_sampling=fast)
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@gpu(void())
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def events():
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gr.on(
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@@ -327,7 +328,7 @@ def events():
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def entry():
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os.chdir(os.path.abspath(os.path.dirname(__file__)))
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ui()
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events[1,32]()
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#import jax
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#import jax.numpy as jnp
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from numba import cuda, njit as cpu, void, int64 as int, float64 as float, boolean as bool, uint8 as rgb
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from numba.cuda import jit as gpu, grid, as_cuda_array as tensor2array
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from numba.types import unicode_type as string
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from PIL.Image import fromarray as array2image
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import numpy as np
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}
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"""
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# torch pipe
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pipe = AnimateDiffPipeline.from_pretrained(base, vae=vae, motion_adapter=adapter, torch_dtype=dtype).to(device)
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pipe.scheduler = DDIMScheduler(
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clip_sample=False,
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beta_start=0.00085,
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beta_end=0.012,
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beta_schedule="linear",
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timestep_spacing="trailing",
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steps_offset=1
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)
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pipe.unet.load_state_dict(load_file(hf_hub_download(repo, ckpt), device=device), strict=False)
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pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin")
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pipe.enable_vae_slicing()
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pipe.enable_free_init(method="butterworth", use_fast_sampling=fast)
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# functionality
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def run(cmd):
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def calc(img,p1,p2,motion):
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global out_pipe
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global last_motion
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global pipe
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x = grid(1)
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result.append(gr.Image(interactive=False,elem_classes="image-container", label="Result", show_label=False, type='filepath', show_share_button=False))
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demo.queue().launch()
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@gpu(void())
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def events():
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gr.on(
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def entry():
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os.chdir(os.path.abspath(os.path.dirname(__file__)))
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ui()
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events[1,32]()
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