Skip to main content

A collection of useful tools!

Project description

Hello

A collection of useful tools!

pip install hello2

hello.data

python -m hello.data coco2yolo -h

COCO to YOLO

positional arguments:
  coco_dir              dataset root dir

optional arguments:
  -h, --help            show this help message and exit
  -j JSON_DIR, --json_dir JSON_DIR
                        coco json file dir
  --classes CLASSES [CLASSES ...]
                        filter by class: --classes c0 c2 c3

hello.fiftyone

import fiftyone.zoo as foz
from hello.fiftyone.utils import *

# Download and load COCO-2017
label_types = ("detections", "segmentations")
dataset = foz.load_zoo_dataset("coco-2017", label_types=label_types)
print(dataset)

# clone sample field
dataset = clone_sample_field(dataset, "detections", "ground_truth")
print(dataset)

# map labels
mapping = {"cat": "CAT", "dog": "DOG", "person": "PERSON", "*": "OTHER"}
cat_dog_person = map_labels(dataset, mapping, "ground_truth")
print(cat_dog_person.count_values("ground_truth.detections.label"))

# filter samples
classes = ["CAT", "DOG", "PERSON"]
cat_dog_person = filter_samples(cat_dog_person, classes, field_name="ground_truth")
print(cat_dog_person.count_values("ground_truth.detections.label"))

# filter labels
classes = ["CAT", "DOG", "PERSON"]
cat_dog_person = filter_labels(cat_dog_person, classes, field_name="ground_truth")
print(cat_dog_person.count_values("ground_truth.detections.label"))

# merge datasets
classes = ["CAT", "DOG", "PERSON", "OTHER"]
info = {"description": "COCO 2017",
        "version": "1.0"}
big_dataset = merge_datasets("big", classes, info, [cat_dog_person])
print(big_dataset.count_values("tags"))

# split dataset
splits = {"train": 0.8, "val": 0.1}
split_dataset(big_dataset, splits=splits, limit=200, field_name="ground_truth")
print(big_dataset.count_values("tags"))

# export dataset
results = export_dataset("/workspace/tmp/big", big_dataset, "ground_truth")
print(results)

# load dataset
test = load_dataset("/workspace/tmp/big/test", label_field="ground_truth")
print(test.count_values("tags"))

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hello2-0.1.5.tar.gz (11.2 kB view details)

Uploaded Source

Built Distribution

hello2-0.1.5-py3-none-any.whl (11.8 kB view details)

Uploaded Python 3

File details

Details for the file hello2-0.1.5.tar.gz.

File metadata

  • Download URL: hello2-0.1.5.tar.gz
  • Upload date:
  • Size: 11.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.27.1

File hashes

Hashes for hello2-0.1.5.tar.gz
Algorithm Hash digest
SHA256 75facee5b4b0d56c10d779e31bfd2d5b033a5264f8fe362be3a386970dd73655
MD5 6ce31e2b3777fdca8a9b00d8dfb058b9
BLAKE2b-256 a44882402deae95ef0a7f30f9542bd5de0f6cdaed77db1c911998b80a8d0aaf8

See more details on using hashes here.

File details

Details for the file hello2-0.1.5-py3-none-any.whl.

File metadata

  • Download URL: hello2-0.1.5-py3-none-any.whl
  • Upload date:
  • Size: 11.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-requests/2.27.1

File hashes

Hashes for hello2-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 605e45916cf753488270987e8f33fbca0dd128c39d2d28331415f621a46c49ce
MD5 de9de007c9305c50221e45e12a57ef3b
BLAKE2b-256 a083becfd92397f29d5ade4cda6647b652e6b148bd99590027ade52ad06ac6c0

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page