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# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# 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.
import dataclasses
import enum
import subprocess
from typing import Callable, Optional
class Framework(enum.Enum):
TENSORFLOW = "tensorflow"
PYTORCH = "pytorch"
@dataclasses.dataclass(frozen=True)
class DatasetSpec:
framework: Optional[Framework]
create_dataset_fn: Callable
COCO_LABELS = {
# 0: 'background',
1: "person",
2: "bicycle",
3: "car",
4: "motorcycle",
5: "airplane",
6: "bus",
7: "train",
8: "truck",
9: "boat",
10: "traffic light",
11: "fire hydrant",
13: "stop sign",
14: "parking meter",
15: "bench",
16: "bird",
17: "cat",
18: "dog",
19: "horse",
20: "sheep",
21: "cow",
22: "elephant",
23: "bear",
24: "zebra",
25: "giraffe",
27: "backpack",
28: "umbrella",
31: "handbag",
32: "tie",
33: "suitcase",
34: "frisbee",
35: "skis",
36: "snowboard",
37: "sports ball",
38: "kite",
39: "baseball bat",
40: "baseball glove",
41: "skateboard",
42: "surfboard",
43: "tennis racket",
44: "bottle",
46: "wine glass",
47: "cup",
48: "fork",
49: "knife",
50: "spoon",
51: "bowl",
52: "banana",
53: "apple",
54: "sandwich",
55: "orange",
56: "broccoli",
57: "carrot",
58: "hot dog",
59: "pizza",
60: "donut",
61: "cake",
62: "chair",
63: "couch",
64: "potted plant",
65: "bed",
67: "dining table",
70: "toilet",
72: "tv",
73: "laptop",
74: "mouse",
75: "remote",
76: "keyboard",
77: "cell phone",
78: "microwave",
79: "oven",
80: "toaster",
81: "sink",
82: "refrigerator",
84: "book",
85: "clock",
86: "vase",
87: "scissors",
88: "teddy bear",
89: "hair drier",
90: "toothbrush",
}
def _create_tfds_coco2017_validation(batch_size: Optional[int] = None) -> Callable:
subprocess.run(["pip", "install", "--upgrade", "tensorflow-datasets"], check=True)
import tensorflow_datasets as tfds # pytype: disable=import-error
return tfds.load("coco/2017", split="validation", as_supervised=True, with_info=True, batch_size=batch_size)
TFDS_COCO2017_VALIDATION_DATASET = DatasetSpec(
framework=Framework.TENSORFLOW,
create_dataset_fn=_create_tfds_coco2017_validation,
)
def _create_tfds_tf_flowers(batch_size: Optional[int] = None):
subprocess.run(["pip", "install", "--upgrade", "tensorflow-datasets"], check=True)
import tensorflow_datasets as tfds # pytype: disable=import-error
return tfds.load("tf_flowers", as_supervised=True, with_info=True, batch_size=batch_size)
TFDS_TF_FLOWERS_DATASET = DatasetSpec(
framework=Framework.TENSORFLOW,
create_dataset_fn=_create_tfds_tf_flowers,
)
DATASETS_CATALOGUE = [TFDS_COCO2017_VALIDATION_DATASET, TFDS_TF_FLOWERS_DATASET]
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