update

.gitattributes

@@ -49,3 +49,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+testdata.py filter=lfs diff=lfs merge=lfs -text
+requirements.txt filter=lfs diff=lfs merge=lfs -text

data/annotations.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bfc9b871de6a1e37a0b275ccea678422e96fba72202ce1b8215cfebc69abbef0
-size 1034076
+oid sha256:aca1fed529a6f00598db63a1c685c3915d33d420430bad252a2822bac4b6609c
+size 982986

data/{fisheye.zip → images.zip}

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6bea53ee6387cb672c3586993f3091b6ab18cc96e57809c3dfe9938629a5dbd4
-size 446670238
+oid sha256:486d98266f56405840eda965c6d4e54008013e11456ed2e878abb9070cdc5286
+size 4512838147

data/soiling_annotations.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2daec4c90f44c0f981c59d5ab9916ea6d14f95a938daffee1a863e37c69aea09
-size 1195308
+oid sha256:10731fc73eead247d280ce895d342f71b934eefdec1b7ab3622c92d7a3ddf516
+size 1005826

requirements.txt

@@ -1,7 +1,3 @@
-regex
-glob2
-tqdm
-pathlib
-collections2
-typing
-Pillow
+version https://git-lfs.github.com/spec/v1
+oid sha256:75d5618340023c3bab178f665513bee627f116ad66ba3a13963d7fe798330588
+size 45

testdata.py

@@ -1,151 +1,3 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""PP4AV dataset."""
-
-import os
-from glob import glob
-from tqdm import tqdm
-from pathlib import Path
-from typing import List
-import re
-from collections import defaultdict
-import datasets
-
-
-
-_HOMEPAGE = "http://shuoyang1213.me/WIDERFACE/"
-
-_LICENSE = "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"
-
-_CITATION = """\
-@inproceedings{yang2016wider,
-    Author = {Yang, Shuo and Luo, Ping and Loy, Chen Change and Tang, Xiaoou},
-    Booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
-    Title = {WIDER FACE: A Face Detection Benchmark},
-    Year = {2016}}
-"""
-
-_DESCRIPTION = """\
-WIDER FACE dataset is a face detection benchmark dataset, of which images are
-selected from the publicly available WIDER dataset. We choose 32,203 images and
-label 393,703 faces with a high degree of variability in scale, pose and
-occlusion as depicted in the sample images. WIDER FACE dataset is organized
-based on 61 event classes. For each event class, we randomly select 40%/10%/50%
-data as training, validation and testing sets. We adopt the same evaluation
-metric employed in the PASCAL VOC dataset. Similar to MALF and Caltech datasets,
-we do not release bounding box ground truth for the test images. Users are
-required to submit final prediction files, which we shall proceed to evaluate.
-"""
-
-
-_REPO = "https://huggingface.co/datasets/khaclinh/testdata/resolve/main/data"
-_URLS = {
-    "test": f"{_REPO}/fisheye.zip",
-    "annot": f"{_REPO}/annotations.zip",
-}
-
-IMG_EXT = ['png', 'jpeg', 'jpg']
-_SUBREDDITS = ["zurich"]
-
-class TestDataConfig(datasets.BuilderConfig):
-    """BuilderConfig for TestData."""
-
-    def __init__(self, name, **kwargs):
-        """BuilderConfig for TestData.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(TestDataConfig, self).__init__(version=datasets.Version("1.0.0", ""), name=name, **kwargs)
-
-class TestData(datasets.GeneratorBasedBuilder):
-    """WIDER FACE dataset."""
-    
-    BUILDER_CONFIGS = [
-        TestDataConfig("fisheye"),
-    ]
-    
-    BUILDER_CONFIGS += [TestDataConfig(subreddit) for subreddit in _SUBREDDITS]
-    
-    DEFAULT_CONFIG_NAME = "fisheye"
-    
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "image": datasets.Image(),
-                    "faces": datasets.Sequence(datasets.Sequence(datasets.Value("float32"), length=4)),
-                    "plates": datasets.Sequence(datasets.Sequence(datasets.Value("float32"), length=4)), 
-                    
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-        
-    def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(_URLS)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "name": self.config.name,
-                    "data_dir": data_dir["test"],
-                    "annot_dir": data_dir["annot"],
-                },
-            ),
-        ]
-
-    def _generate_examples(self, name, data_dir, annot_dir):
-        
-        image_dir = os.path.join(data_dir, name)
-        annotation_dir = os.path.join(annot_dir, name)
-        files = []
-        
-        idx = 0
-        for i_file in glob(os.path.join(image_dir, "*.png")):
-            plates = []
-            faces = []
-            
-            img_relative_file = os.path.relpath(i_file, image_dir)
-            gt_relative_path = img_relative_file.replace(".png", ".txt")
-            
-            gt_path = os.path.join(annotation_dir, gt_relative_path)
-            
-            annotation = defaultdict(list)
-            with open(gt_path, "r", encoding="utf-8") as f:
-                line = f.readline().strip()
-                while line:
-                    assert re.match(r"^\d( [\d\.]+){4,5}$", line), "Incorrect line: %s" % line
-                    cls, cx, cy, w, h = line.split()[:5]
-                    cls, cx, cy, w, h = int(cls), float(cx), float(cy), float(w), float(h)
-                    x1, y1, x2, y2 = cx - w / 2, cy - h / 2, cx + w / 2, cy + h / 2
-                    annotation[cls].append([x1, y1, x2, y2])
-                    line = f.readline().strip()
-
-            for cls, bboxes in annotation.items():
-                for x1, y1, x2, y2 in bboxes:
-                    if cls == 0:
-                        faces.append([x1, y1, x2, y2])
-                    else:
-                        plates.append([x1, y1, x2, y2])
-            
-            yield idx, {"image": i_file, "faces": faces, "plates": plates}
-            
-            idx += 1
+version https://git-lfs.github.com/spec/v1
+oid sha256:3a3c670d21b2609d4427111d778dfec3438529f196a2287b778541809e357c54
+size 5682