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"""
Source url: https://github.com/OPHoperHPO/image-background-remove-tool
Author: Nikita Selin (OPHoperHPO)[https://github.com/OPHoperHPO].
License: Apache License 2.0
"""
import hashlib
import os
import warnings
from abc import ABCMeta, abstractmethod, ABC
from pathlib import Path
from typing import Optional
import carvekit
from carvekit.ml.files import checkpoints_dir
import requests
import tqdm
requests = requests.Session()
requests.headers.update({"User-Agent": f"Carvekit/{carvekit.version}"})
MODELS_URLS = {
"basnet.pth": {
"repository": "Carve/basnet-universal",
"revision": "870becbdb364fda6d8fdb2c10b072542f8d08701",
"filename": "basnet.pth",
},
"deeplab.pth": {
"repository": "Carve/deeplabv3-resnet101",
"revision": "d504005392fc877565afdf58aad0cd524682d2b0",
"filename": "deeplab.pth",
},
"fba_matting.pth": {
"repository": "Carve/fba",
"revision": "a5d3457df0fb9c88ea19ed700d409756ca2069d1",
"filename": "fba_matting.pth",
},
"u2net.pth": {
"repository": "Carve/u2net-universal",
"revision": "10305d785481cf4b2eee1d447c39cd6e5f43d74b",
"filename": "full_weights.pth",
},
"tracer_b7.pth": {
"repository": "Carve/tracer_b7",
"revision": "d8a8fd9e7b3fa0d2f1506fe7242966b34381e9c5",
"filename": "tracer_b7.pth",
},
"tracer_hair.pth": {
"repository": "Carve/tracer_b7",
"revision": "d8a8fd9e7b3fa0d2f1506fe7242966b34381e9c5",
"filename": "tracer_b7.pth", # TODO don't forget change this link!!
},
}
MODELS_CHECKSUMS = {
"basnet.pth": "e409cb709f4abca87cb11bd44a9ad3f909044a917977ab65244b4c94dd33"
"8b1a37755c4253d7cb54526b7763622a094d7b676d34b5e6886689256754e5a5e6ad",
"deeplab.pth": "9c5a1795bc8baa267200a44b49ac544a1ba2687d210f63777e4bd715387324469a59b072f8a28"
"9cc471c637b367932177e5b312e8ea6351c1763d9ff44b4857c",
"fba_matting.pth": "890906ec94c1bfd2ad08707a63e4ccb0955d7f5d25e32853950c24c78"
"4cbad2e59be277999defc3754905d0f15aa75702cdead3cfe669ff72f08811c52971613",
"u2net.pth": "16f8125e2fedd8c85db0e001ee15338b4aa2fda77bab8ba70c25e"
"bea1533fda5ee70a909b934a9bd495b432cef89d629f00a07858a517742476fa8b346de24f7",
"tracer_b7.pth": "c439c5c12d4d43d5f9be9ec61e68b2e54658a541bccac2577ef5a54fb252b6e8415d41f7e"
"c2487033d0c02b4dd08367958e4e62091318111c519f93e2632be7b",
"tracer_hair.pth": "5c2fb9973fc42fa6208920ffa9ac233cc2ea9f770b24b4a96969d3449aed7ac89e6d37e"
"e486a13e63be5499f2df6ccef1109e9e8797d1326207ac89b2f39a7cf",
}
def sha512_checksum_calc(file: Path) -> str:
"""
Calculates the SHA512 hash digest of a file on fs
Args:
file: Path to the file
Returns:
SHA512 hash digest of a file.
"""
dd = hashlib.sha512()
with file.open("rb") as f:
for chunk in iter(lambda: f.read(4096), b""):
dd.update(chunk)
return dd.hexdigest()
class CachedDownloader:
__metaclass__ = ABCMeta
@property
@abstractmethod
def name(self) -> str:
return self.__class__.__name__
@property
@abstractmethod
def fallback_downloader(self) -> Optional["CachedDownloader"]:
pass
def download_model(self, file_name: str) -> Path:
try:
return self.download_model_base(file_name)
except BaseException as e:
if self.fallback_downloader is not None:
warnings.warn(
f"Failed to download model from {self.name} downloader."
f" Trying to download from {self.fallback_downloader.name} downloader."
)
return self.fallback_downloader.download_model(file_name)
else:
warnings.warn(
f"Failed to download model from {self.name} downloader."
f" No fallback downloader available."
)
raise e
@abstractmethod
def download_model_base(self, file_name: str) -> Path:
"""Download model from any source if not cached. Returns path if cached"""
def __call__(self, file_name: str):
return self.download_model(file_name)
class HuggingFaceCompatibleDownloader(CachedDownloader, ABC):
def __init__(
self,
name: str = "Huggingface.co",
base_url: str = "https://huggingface.co",
fb_downloader: Optional["CachedDownloader"] = None,
):
self.cache_dir = checkpoints_dir
self.base_url = base_url
self._name = name
self._fallback_downloader = fb_downloader
@property
def fallback_downloader(self) -> Optional["CachedDownloader"]:
return self._fallback_downloader
@property
def name(self):
return self._name
def check_for_existence(self, file_name: str) -> Optional[Path]:
if file_name not in MODELS_URLS.keys():
raise FileNotFoundError("Unknown model!")
path = (
self.cache_dir
/ MODELS_URLS[file_name]["repository"].split("/")[1]
/ file_name
)
if not path.exists():
return None
if MODELS_CHECKSUMS[path.name] != sha512_checksum_calc(path):
warnings.warn(
f"Invalid checksum for model {path.name}. Downloading correct model!"
)
os.remove(path)
return None
return path
def download_model_base(self, file_name: str) -> Path:
cached_path = self.check_for_existence(file_name)
if cached_path is not None:
return cached_path
else:
cached_path = (
self.cache_dir
/ MODELS_URLS[file_name]["repository"].split("/")[1]
/ file_name
)
cached_path.parent.mkdir(parents=True, exist_ok=True)
url = MODELS_URLS[file_name]
hugging_face_url = f"{self.base_url}/{url['repository']}/resolve/{url['revision']}/{url['filename']}"
try:
r = requests.get(hugging_face_url, stream=True, timeout=10)
if r.status_code < 400:
with open(cached_path, "wb") as f:
r.raw.decode_content = True
for chunk in tqdm.tqdm(
r,
desc="Downloading " + cached_path.name + " model",
colour="blue",
):
f.write(chunk)
else:
if r.status_code == 404:
raise FileNotFoundError(f"Model {file_name} not found!")
else:
raise ConnectionError(
f"Error {r.status_code} while downloading model {file_name}!"
)
except BaseException as e:
if cached_path.exists():
os.remove(cached_path)
raise ConnectionError(
f"Exception caught when downloading model! "
f"Model name: {cached_path.name}. Exception: {str(e)}."
)
return cached_path
fallback_downloader: CachedDownloader = HuggingFaceCompatibleDownloader()
downloader: CachedDownloader = HuggingFaceCompatibleDownloader(
base_url="https://cdn.carve.photos",
fb_downloader=fallback_downloader,
name="Carve CDN",
)
downloader._fallback_downloader = fallback_downloader
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