feat: dataset dataloader

This commit is contained in:
Laureηt 2023-01-27 18:45:20 +01:00
parent c0d5765da6
commit 9b0a8bc1af
Signed by: Laurent
SSH key fingerprint: SHA256:kZEpW8cMJ54PDeCvOhzreNr4FSh6R13CMGH/POoO8DI
6 changed files with 942 additions and 11 deletions

5
.vscode/launch.json vendored
View file

@ -5,12 +5,9 @@
"name": "Python: Current File",
"type": "python",
"request": "launch",
"program": "${workspaceFolder}/src/main.py",
"program": "${file}",
"console": "integratedTerminal",
"justMyCode": true,
"env": {
"PYGAME_HIDE_SUPPORT_PROMPT": "hide"
}
}
]
}

View file

@ -10,7 +10,13 @@
flake-utils.lib.eachDefaultSystem (system:
let pkgs = nixpkgs.legacyPackages.${system};
in {
devShell =
pkgs.mkShell { buildInputs = with pkgs; [ poetry python3 ]; };
devShell = pkgs.mkShell {
buildInputs = with pkgs; [
poetry
python3
python310Packages.numpy
python310Packages.datasets
];
};
});
}

846
poetry.lock generated
View file

@ -1,5 +1,63 @@
# This file is automatically @generated by Poetry and should not be changed by hand.
[[package]]
name = "aiohttp"
version = "3.7.4.post0"
description = "Async http client/server framework (asyncio)"
category = "main"
optional = false
python-versions = ">=3.6"
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{file = "aiohttp-3.7.4.post0.tar.gz", hash = "sha256:493d3299ebe5f5a7c66b9819eacdcfbbaaf1a8e84911ddffcdc48888497afecf"},
]
[package.dependencies]
async-timeout = ">=3.0,<4.0"
attrs = ">=17.3.0"
chardet = ">=2.0,<5.0"
multidict = ">=4.5,<7.0"
typing-extensions = ">=3.6.5"
yarl = ">=1.0,<2.0"
[package.extras]
speedups = ["aiodns", "brotlipy", "cchardet"]
[[package]]
name = "albumentations"
version = "1.3.0"
@ -55,6 +113,37 @@ six = "*"
[package.extras]
test = ["astroid", "pytest"]
[[package]]
name = "async-timeout"
version = "3.0.1"
description = "Timeout context manager for asyncio programs"
category = "main"
optional = false
python-versions = ">=3.5.3"
files = [
{file = "async-timeout-3.0.1.tar.gz", hash = "sha256:0c3c816a028d47f659d6ff5c745cb2acf1f966da1fe5c19c77a70282b25f4c5f"},
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]
[[package]]
name = "attrs"
version = "22.2.0"
description = "Classes Without Boilerplate"
category = "main"
optional = false
python-versions = ">=3.6"
files = [
{file = "attrs-22.2.0-py3-none-any.whl", hash = "sha256:29e95c7f6778868dbd49170f98f8818f78f3dc5e0e37c0b1f474e3561b240836"},
{file = "attrs-22.2.0.tar.gz", hash = "sha256:c9227bfc2f01993c03f68db37d1d15c9690188323c067c641f1a35ca58185f99"},
]
[package.extras]
cov = ["attrs[tests]", "coverage-enable-subprocess", "coverage[toml] (>=5.3)"]
dev = ["attrs[docs,tests]"]
docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope.interface"]
tests = ["attrs[tests-no-zope]", "zope.interface"]
tests-no-zope = ["cloudpickle", "cloudpickle", "hypothesis", "hypothesis", "mypy (>=0.971,<0.990)", "mypy (>=0.971,<0.990)", "pympler", "pympler", "pytest (>=4.3.0)", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-mypy-plugins", "pytest-xdist[psutil]", "pytest-xdist[psutil]"]
[[package]]
name = "backcall"
version = "0.2.0"
@ -126,6 +215,18 @@ d = ["aiohttp (>=3.7.4)"]
jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
uvloop = ["uvloop (>=0.15.2)"]
[[package]]
name = "certifi"
version = "2022.12.7"
description = "Python package for providing Mozilla's CA Bundle."
category = "main"
optional = false
python-versions = ">=3.6"
files = [
{file = "certifi-2022.12.7-py3-none-any.whl", hash = "sha256:4ad3232f5e926d6718ec31cfc1fcadfde020920e278684144551c91769c7bc18"},
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]
[[package]]
name = "cffi"
version = "1.15.1"
@ -215,6 +316,116 @@ files = [
{file = "cfgv-3.3.1.tar.gz", hash = "sha256:f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736"},
]
[[package]]
name = "chardet"
version = "4.0.0"
description = "Universal encoding detector for Python 2 and 3"
category = "main"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
files = [
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]
[[package]]
name = "charset-normalizer"
version = "3.0.1"
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
category = "main"
optional = false
python-versions = "*"
files = [
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]
[package.dependencies]
idna = ">=2.0"
multidict = ">=4.0"
[[package]]
name = "zipp"
version = "3.11.0"
@ -2211,4 +3047,4 @@ testing = ["flake8 (<5)", "func-timeout", "jaraco.functools", "jaraco.itertools"
[metadata]
lock-version = "2.0"
python-versions = ">=3.8.1,<4.0"
content-hash = "9b43d6c6edd8d6ec87f5a867989c1a51e9deece47db456a34c4e08de4631b3fa"
content-hash = "1b9564fc0ddc0f25340c3afb66a1eb968b526da498e953310a724923ccfc0af7"

View file

@ -13,6 +13,7 @@ albumentations = "^1.3.0"
python = ">=3.8.1,<4.0"
rich = "^12.6.0"
torch = "^1.13.1"
datasets = "^2.9.0"
[tool.poetry.group.notebooks]
optional = true

86
src/dataset.py Normal file
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@ -0,0 +1,86 @@
"""Dataset class AI or NOT HuggingFace competition."""
import pathlib
from typing import Optional
import datasets
import pandas as pd
_VERSION = "1.0.0"
_GIT_COMMIT_REVISION = "b843a82bd712648b2fe0dc043cf8a04475491d38"
_BASE_URLS = {
"train": f"https://huggingface.co/datasets/competitions/aiornot/resolve/{_GIT_COMMIT_REVISION}/train.zip",
"test": f"https://huggingface.co/datasets/competitions/aiornot/resolve/{_GIT_COMMIT_REVISION}/test.zip",
"csv": f"https://huggingface.co/datasets/competitions/aiornot/resolve/{_GIT_COMMIT_REVISION}/train.csv",
}
_HOMEPAGE = "https://huggingface.co/spaces/competitions/aiornot"
_DESCRIPTION = """
The dataset consists of approximately 31000 images, some of which have been generated by ai.
Your task is to build a model that can identify ai generated images.
Please use the community tab for discussion and questions.
"""
_NAMES = [
"AI",
"NOT",
]
class aiornot(datasets.GeneratorBasedBuilder):
"""Food-101 Images dataset."""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
version=_VERSION,
features=datasets.Features(
{
"image": datasets.Image(),
"label": datasets.ClassLabel(names=_NAMES),
}
),
supervised_keys=("image", "label"),
homepage=_HOMEPAGE,
task_templates=[datasets.tasks.ImageClassification(image_column="image", label_column="label")],
)
def _split_generators(self, dl_manager):
train_path = pathlib.Path(dl_manager.download_and_extract(_BASE_URLS["train"]))
test_path = pathlib.Path(dl_manager.download_and_extract(_BASE_URLS["test"]))
csv_path = pathlib.Path(dl_manager.download(_BASE_URLS["csv"]))
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"data_dir": train_path,
"csv_file": csv_path,
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"data_dir": test_path,
},
),
]
def _generate_examples(self, data_dir: pathlib.Path, csv_file: Optional[pathlib.Path] = None):
"""Generate images and labels for splits."""
if csv_file is not None:
df = pd.read_csv(csv_file)
for index, row in df.iterrows():
yield index, {
"image": str(data_dir / row["image"]),
"label": row["label"],
}
else:
rglob = pathlib.Path(data_dir).rglob("*.jpg")
for index, filepath in enumerate(rglob):
yield index, {
"image": str(filepath),
"label": -1,
}

5
src/tests/dataset.py Normal file
View file

@ -0,0 +1,5 @@
import datasets
dataset = datasets.load_dataset("src/dataset.py")
print(dataset)