File size: 5,310 Bytes
74f3479 ed8f186 74f3479 ed8f186 74f3479 ed8f186 07c3866 74f3479 23be2b5 aef8960 ed8f186 23be2b5 ed8f186 74f3479 584ffa2 ed8f186 e5ecdf2 74f3479 ed8f186 74f3479 ed8f186 74f3479 ed8f186 74f3479 e5ecdf2 ed8f186 5871d59 07c3866 74f3479 07c3866 74f3479 07c3866 74f3479 5871d59 07c3866 5871d59 23be2b5 5871d59 74f3479 07c3866 23be2b5 07c3866 74f3479 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 |
import json
import os
import datasets
_CITATION = """\
@SIA86{huggingface:dataset,
title = {WaterFlowCountersRecognition dataset},
author={SIA86},
year={2023}
}
"""
_DESCRIPTION = """\
This dataset is designed to detect digital data from water flow counters photos.
"""
_HOMEPAGE = "https://github.com/SIA86/WaterFlowRecognition"
_REGION_NAME = ['value_a', 'value_b', 'serial']
_REGION_ROTETION = ['0', '90', '180', '270']
class WaterFlowCounterConfig(datasets.BuilderConfig):
"""Builder Config for WaterFlowCounter"""
def __init__(self, data_url, metadata_url, **kwargs):
"""BuilderConfig for WaterFlowCounter.
Args:
data_url: `string`, url to download the photos.
metadata_urls: instance segmentation regions and description
**kwargs: keyword arguments forwarded to super.
"""
super(WaterFlowCounterConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
self.data_url = data_url
self.metadata_url = metadata_url
class WaterFlowCounter(datasets.GeneratorBasedBuilder):
"""WaterFlowCounter Images dataset"""
BUILDER_CONFIGS = [
WaterFlowCounterConfig(
name="WFCR_full",
description="Full dataset which contains coordinates and names of regions and information about rotation",
data_url={
"train": "data/train_photos.zip",
"test": "data/test_photos.zip",
},
metadata_url={
'full': "data/WaterFlowCounter.json"
}
)
]
def _info(self):
features = datasets.Features(
{
"image": datasets.Image(),
"regions": datasets.Sequence(
{
"all_points_x": datasets.Sequence(datasets.Value("int64")),
"all_points_y": datasets.Sequence(datasets.Value("int64")),
"name": datasets.ClassLabel(names=_REGION_NAME, num_classes=3),
"rotated": datasets.ClassLabel(names=_REGION_ROTETION, num_classes=4)
}
)
}
)
return datasets.DatasetInfo(
features=features,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
data_files = dl_manager.download_and_extract(self.config.data_url)
meta_file = dl_manager.download(self.config.metadata_url)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"folder_dir": data_files["train"],
"metadata_path": meta_file['full']
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"folder_dir": data_files["test"],
"metadata_path": meta_file['full']
},
)
]
def _generate_examples(self, folder_dir, metadata_path):
name_to_id = {}
rotation_to_id = {}
for indx, name in enumerate(_REGION_NAME):
name_to_id[name] = indx
for indx, name in enumerate(_REGION_ROTETION):
rotation_to_id[name] = indx
with open(metadata_path, "r", encoding='utf-8') as f:
annotations = json.load(f)
#print(annotations['_via_image_id_list'][0:5])
for file in os.listdir(folder_dir):
filepath = os.path.join(folder_dir, file)
#print(filepath)
with open(filepath, "rb") as f:
image_bytes = f.read()
#print(image_bytes)
idx = 0
all_x = []
all_y = []
names = []
for el in annotations['_via_img_metadata']:
if annotations['_via_img_metadata'][el]['filename'] == file:
for region in annotations['_via_img_metadata'][el]['regions']:
all_x.append(region['shape_attributes']['all_points_x'])
all_y.append(region['shape_attributes']['all_points_y'])
names.append(name_to_id[list(region['region_attributes']['name'].keys())[0]])
try:
rotated = [rotation_to_id[list(region['region_attributes']['rotated'].keys())[0]]]
except:
rotated = [int(region['region_attributes']['rotated'])]
yield idx, {
"image": {"path": filepath, "bytes": image_bytes},
"regions": {
"all_points_x": all_x,
"all_points_y": all_y,
"name":names,
"rotated": rotated
}
}
idx += 1
|