from diffusers import StableDiffusionControlNetInpaintPipeline
controlnet = [
ControlNetModel.from_pretrained(
"diffusers/controlnet-zoe-depth-sdxl-1.0" ,
torch_dtype=torch.float16
)
]
pipe = StableDiffusionControlNetInpaintPipeline.from_pretrained(
"diffusers/stable-diffusion-xl-1.0-inpainting-0.1" ,
controlnet=controlnet,
torch_dtype=torch.float16
)
pipe.to( "cuda" )
pipe.enable_xformers_memory_efficient_attention()
init_image = load_image( "https://media.vogue.fr/photos/62bf04b69a57673c725432f3/3:2/w_1793,h_1195,c_limit/rev-1-Barbie-InstaVert_High_Res_JPEG.jpeg" )
zoe_image = load_image( "/workspace/zoe_depth.png" )
mask_image = load_image( "/workspace/mask.png" )
prompt = "beautiful japanese woman with smile, long hair, 8k, RAW photo, best quality, masterpiece, photo-realistic, focus, professional lighting"
negative_prompt = "worst quality, low quality"
strength= 0.95
controlnet_conditioning_scale = 0.45
import os
os.makedirs( "results" , exist_ok= True )
for i in range (4):
seed = 10000 * (i + 1 )
generator = torch.manual_seed(seed)
image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
image=init_image,
mask_image=mask_image,
control_image=[zoe_image],
controlnet_conditioning_scale=controlnet_conditioning_scale,
strength=strength,
generator=generator
).images[ 0 ]
image.save(os.path.join( "results" ,f"/workspace/outputs/{seed}.png" ))
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
Cell In[9], line 13
3 from diffusers import ControlNetModel, StableDiffusionControlNetInpaintPipeline
6 controlnet = [
7 ControlNetModel.from_pretrained(
8 "diffusers/controlnet-zoe-depth-sdxl-1.0" ,
9 torch_dtype=torch.float16
10 )
11 ]
---> 13 pipe = StableDiffusionControlNetInpaintPipeline.from_pretrained(
14 "diffusers/stable-diffusion-xl-1.0-inpainting-0.1" ,
15 controlnet=controlnet,
16 torch_dtype=torch.float16
17 )
19 pipe.to( "cuda" )
20 pipe.enable_xformers_memory_efficient_attention()
File /usr/local/lib/python3.10/dist-packages/diffusers/pipelines/pipeline_utils.py:932, in DiffusionPipeline.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
929 # 1. Download the checkpoints and configs
930 # use snapshot download here to get it working from from_pretrained
931 if not os.path.isdir(pretrained_model_name_or_path):
--> 932 cached_folder = cls.download(
933 pretrained_model_name_or_path,
934 cache_dir=cache_dir,
935 resume_download=resume_download,
936 force_download=force_download,
937 proxies=proxies,
938 local_files_only=local_files_only,
939 use_auth_token=use_auth_token,
940 revision=revision,
941 from_flax=from_flax,
942 use_safetensors=use_safetensors,
943 custom_pipeline=custom_pipeline,
944 custom_revision=custom_revision,
945 variant=variant,
946 load_connected_pipeline=load_connected_pipeline,
947 **kwargs,
948 )
949 else:
950 cached_folder = pretrained_model_name_or_path
File /usr/local/lib/python3.10/dist-packages/diffusers/pipelines/pipeline_utils.py:1507, in DiffusionPipeline.download(cls, pretrained_model_name, **kwargs)
1505 # download all allow_patterns - ignore_patterns
1506 try:
-> 1507 cached_folder = snapshot_download(
1508 pretrained_model_name,
1509 cache_dir=cache_dir,
1510 resume_download=resume_download,
1511 proxies=proxies,
1512 local_files_only=local_files_only,
1513 use_auth_token=use_auth_token,
1514 revision=revision,
1515 allow_patterns=allow_patterns,
1516 ignore_patterns=ignore_patterns,
1517 user_agent=user_agent,
1518 )
1520 # retrieve pipeline class from local file
1521 cls_name = cls.load_config(os.path.join(cached_folder, "model_index.json")).get("_class_name", None)
File /usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py:118, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
115 if check_use_auth_token:
116 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 118 return fn(*args, **kwargs)
File /usr/local/lib/python3.10/dist-packages/huggingface_hub/_snapshot_download.py:235, in snapshot_download(repo_id, revision, repo_type, cache_dir, local_dir, local_dir_use_symlinks, library_name, library_version, user_agent, proxies, etag_timeout, resume_download, force_download, token, local_files_only, allow_patterns, ignore_patterns, max_workers, tqdm_class)
233 _inner_hf_hub_download(file)
234 else:
--> 235 thread_map(
236 _inner_hf_hub_download,
237 filtered_repo_files,
238 desc=f"Fetching {len(filtered_repo_files)} files",
239 max_workers=max_workers,
240 # User can use its own tqdm class or the default one from `huggingface_hub.utils`
241 tqdm_class=tqdm_class or hf_tqdm,
242 )
244 if local_dir is not None:
245 return str(os.path.realpath(local_dir))
File /usr/local/lib/python3.10/dist-packages/tqdm/contrib/concurrent.py:69, in thread_map(fn, *iterables, **tqdm_kwargs)
55 """
56 Equivalent of `list(map(fn, *iterables))`
57 driven by `concurrent.futures.ThreadPoolExecutor`.
(...)
66 [default: max(32, cpu_count() + 4)].
67 """
68 from concurrent.futures import ThreadPoolExecutor
---> 69 return _executor_map(ThreadPoolExecutor, fn, *iterables, **tqdm_kwargs)
File /usr/local/lib/python3.10/dist-packages/tqdm/contrib/concurrent.py:51, in _executor_map(PoolExecutor, fn, *iterables, **tqdm_kwargs)
47 with ensure_lock(tqdm_class, lock_name=lock_name) as lk:
48 # share lock in case workers are already using `tqdm`
49 with PoolExecutor(max_workers=max_workers, initializer=tqdm_class.set_lock,
50 initargs=(lk,)) as ex:
---> 51 return list(tqdm_class(ex.map(fn, *iterables, chunksize=chunksize), **kwargs))
File /usr/local/lib/python3.10/dist-packages/tqdm/notebook.py:254, in tqdm_notebook.__iter__(self)
252 try:
253 it = super(tqdm_notebook, self).__iter__()
--> 254 for obj in it:
255 # return super(tqdm...) will not catch exception
256 yield obj
257 # NB: except ... [ as ...] breaks IPython async KeyboardInterrupt
File /usr/local/lib/python3.10/dist-packages/tqdm/std.py:1178, in tqdm.__iter__(self)
1175 time = self._time
1177 try:
-> 1178 for obj in iterable:
1179 yield obj
1180 # Update and possibly print the progressbar.
1181 # Note: does not call self.update(1) for speed optimisation.
File /usr/lib/python3.10/concurrent/futures/_base.py:621, in Executor.map.<locals>.result_iterator()
618 while fs:
619 # Careful not to keep a reference to the popped future
620 if timeout is None:
--> 621 yield _result_or_cancel(fs.pop())
622 else:
623 yield _result_or_cancel(fs.pop(), end_time - time.monotonic())
File /usr/lib/python3.10/concurrent/futures/_base.py:319, in _result_or_cancel(***failed resolving arguments***)
317 try:
318 try:
--> 319 return fut.result(timeout)
320 finally:
321 fut.cancel()
File /usr/lib/python3.10/concurrent/futures/_base.py:458, in Future.result(self, timeout)
456 raise CancelledError()
457 elif self._state == FINISHED:
--> 458 return self.__get_result()
459 else:
460 raise TimeoutError()
File /usr/lib/python3.10/concurrent/futures/_base.py:403, in Future.__get_result(self)
401 if self._exception:
402 try:
--> 403 raise self._exception
404 finally:
405 # Break a reference cycle with the exception in self._exception
406 self = None
File /usr/lib/python3.10/concurrent/futures/thread.py:58, in _WorkItem.run(self)
55 return
57 try:
---> 58 result = self.fn(*self.args, **self.kwargs)
59 except BaseException as exc:
60 self.future.set_exception(exc)
File /usr/local/lib/python3.10/dist-packages/huggingface_hub/_snapshot_download.py:211, in snapshot_download.<locals>._inner_hf_hub_download(repo_file)
210 def _inner_hf_hub_download(repo_file: str):
--> 211 return hf_hub_download(
212 repo_id,
213 filename=repo_file,
214 repo_type=repo_type,
215 revision=commit_hash,
216 cache_dir=cache_dir,
217 local_dir=local_dir,
218 local_dir_use_symlinks=local_dir_use_symlinks,
219 library_name=library_name,
220 library_version=library_version,
221 user_agent=user_agent,
222 proxies=proxies,
223 etag_timeout=etag_timeout,
224 resume_download=resume_download,
225 force_download=force_download,
226 token=token,
227 )
File /usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_validators.py:118, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
115 if check_use_auth_token:
116 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 118 return fn(*args, **kwargs)
File /usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:1364, in hf_hub_download(repo_id, filename, subfolder, repo_type, revision, library_name, library_version, cache_dir, local_dir, local_dir_use_symlinks, user_agent, force_download, force_filename, proxies, etag_timeout, resume_download, token, local_files_only, legacy_cache_layout)
1361 with temp_file_manager() as temp_file:
1362 logger.info("downloading %s to %s", url, temp_file.name)
-> 1364 http_get(
1365 url_to_download,
1366 temp_file,
1367 proxies=proxies,
1368 resume_size=resume_size,
1369 headers=headers,
1370 expected_size=expected_size,
1371 )
1373 if local_dir is None:
1374 logger.info(f"Storing {url} in cache at {blob_path}")
File /usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:544, in http_get(url, temp_file, proxies, resume_size, headers, timeout, max_retries, expected_size)
542 if chunk: # filter out keep-alive new chunks
543 progress.update(len(chunk))
--> 544 temp_file.write(chunk)
546 if expected_size is not None and expected_size != temp_file.tell():
547 raise EnvironmentError(
548 f"Consistency check failed: file should be of size {expected_size} but has size"
549 f" {temp_file.tell()} ({displayed_name}).\nWe are sorry for the inconvenience. Please retry download and"
550 " pass `force_download=True, resume_download=False` as argument.\nIf the issue persists, please let us"
551 " know by opening an issue on https://github.com/huggingface/huggingface_hub."
552 )
File /usr/lib/python3.10/tempfile.py:622, in _TemporaryFileWrapper.__getattr__.<locals>.func_wrapper(*args, **kwargs)
620 @_functools.wraps(func)
621 def func_wrapper(*args, **kwargs):
--> 622 return func(*args, **kwargs)
OSError: [Errno 28] No space left on device
