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0.1.0 fractalai-0.1.0-py3-none-any.whl

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Project: fractalai
Version: 0.1.0
Filename: fractalai-0.1.0-py3-none-any.whl
Download: [link]
Size: 27241
MD5: 8a2c00940481cc389bfbec6a2c733930
SHA256: f0ffc9fe679c19e59a4103033fa4e96e0fbefadda91172a56efa0452a613513c
Uploaded: 2020-08-11 06:20:23 +0000

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METADATA · WHEEL · RECORD · entry_points.txt

METADATA

Metadata-Version: 2.1
Name: fractalai
Version: 0.1.0
Summary: Integrated image classification and semantic segmentation package
Author: PrakashJay
Author-Email: vanapalli.prakash[at]fractal.ai
License: Apache-2.0
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Requires-Python: ==3.7.0
Requires-Dist: EasyDict (<2.0,>=1.9)
Requires-Dist: albumentations (<0.5.0,>=0.4.1)
Requires-Dist: click (<8.0,>=7.0)
Requires-Dist: efficientnet_pytorch (<0.7.0,>=0.6.3)
Requires-Dist: hyperdash (<0.16.0,>=0.15.3)
Requires-Dist: loguru (<0.4.0,>=0.3.2)
Requires-Dist: opencv-python (<5.0,>=4.1)
Requires-Dist: pandas (<0.26.0,>=0.25.2)
Requires-Dist: pretrainedmodels (<0.8.0,>=0.7.4)
Requires-Dist: pycocotools (<3.0,>=2.0)
Requires-Dist: pytorch-lightning (<0.8.0,>=0.7.1)
Requires-Dist: scikit-learn (<0.22.0,>=0.21.3)
Requires-Dist: segmentation_models_pytorch (<0.2.0,>=0.1.0)
Requires-Dist: torch (==1.4.0)
Requires-Dist: torchvision (<0.6.0,>=0.5.0)
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WHEEL

Wheel-Version: 1.0
Generator: poetry 1.0.10
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Tag: py3-none-any

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fractalai-0.1.0.dist-info/RECORD — —

entry_points.txt

[console_scripts]
avail_encoders = fractalai.classifier.model:available_encoders
check_csv = fractalai.sanity:check_csv
check_data_loader = fractalai.datasets.dataloader:make_data_loader
check_dataset = fractalai.datasets.dataset:run_dataset
check_metrics = fractalai.utils.metrics:check_metrics
check_transforms = fractalai.datasets.agu:understand_transforms
class_imbalance_plot = fractalai.datasets.dataloader:class_imbalance_plot
data_stat = fractalai.visual:get_data_statistic
extract_products_one_label = fractalai.labelme2folder:make_extract_products_one_label
get_mean_std = fractalai.datasets.dataset:get_mean_std
infer_folder = fractalai.engine.infer:infer_folder
infer_img = fractalai.engine.infer:infer_img_click
infer_val_f1score = fractalai.engine.infer:infer_val_f1score
infer_video = fractalai.engine.infer:infer_video_click
json_to_csv = fractalai.csv_utils:json_to_csv
labelme_counter = fractalai.labelme2folder:make_label_counter
make_csv_given_folders = fractalai.csv_utils:make_csv_given_folders
make_folders_from_csv = fractalai.engine.infer:make_folders_from_csv
make_model = fractalai.engine.utils:make_model
name_classes = fractalai.csv_utils:get_classes
seg_model_params = fractalai.engine.utils:seg_model_params
train = fractalai.engine.trainer:main
vis_random_example = fractalai.datasets.dataset:visualize_random_example