Skip to main content

A repository for storing my progress of researches.

Project description

Myosotis-Researches

CcGAN (myosotis_researches.CcGAN)

internal

The internal module is used for setting the local package itself, like installing datasets and so on.

Import with code

from myosotis_researches.internal import *
Function Desctiption
install_datasets(datasets_name) Install the datasets in datasets_name to the local python package.
uninstall_datasets() Remove all the datasets installed to the local python package.
show_datasets() Show all datasets installed.

Note:

  1. The path of the installed datasets are

    resources.files("myosotis_researches").join("CcGAN", "<datasets_name>")

    To run this code, remember to add from importlib import resources at the beginning.

utils

The utils module contains some basic functions and classes which are frequently used during the CcGAN research.

Import with code

from myosotis_researches.utils import *
Function Description
concat_image(img_list, gap=2, direction="vertical") Concat images vertically or horizontally.
make_h5(old_datasets_name, size, new_datasets_path, image_indexes, train_indexes, val_indexes) Get piece of original HDF5 datasets.
print_hdf5(name, obj) Print a basic structure of an HDF5 file.

Note:

  1. Function print_hdf5 should be used within a with block:

    import h5py
    
    with h5py.File(<HDF5_file_path>, "r") as f:
      f.visititems(print_hdf5)
    

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

myosotis_researches-0.1.3.tar.gz (61.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

myosotis_researches-0.1.3-py3-none-any.whl (100.4 kB view details)

Uploaded Python 3

File details

Details for the file myosotis_researches-0.1.3.tar.gz.

File metadata

  • Download URL: myosotis_researches-0.1.3.tar.gz
  • Upload date:
  • Size: 61.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for myosotis_researches-0.1.3.tar.gz
Algorithm Hash digest
SHA256 d5f858b3f6de56754a7ad44ff3e64d9009a597c254af6f1b9663370d995bfeb7
MD5 0ada508333f308202eaebe05ba81bc21
BLAKE2b-256 f4d1b8f37e727be2db2609845958d53b5606c3fa8d40fd9c31a0354a32cbc0fc

See more details on using hashes here.

File details

Details for the file myosotis_researches-0.1.3-py3-none-any.whl.

File metadata

File hashes

Hashes for myosotis_researches-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 0f4f221e9088c0b340b3a1ed0aea5623f663f845734d348aa4e1ff7cb428e863
MD5 42f7c991bb087b8480f2af6a4909a18f
BLAKE2b-256 259af58180749a88f0ca10f21142f870ee4742f69962fb082b6db1e267cc7be8

See more details on using hashes here.

Supported by

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