Commit
•
d5e9fa7
1
Parent(s):
26ff89e
Delete legacy JSON metadata
Browse filesDelete legacy `dataset_infos.json`.
- dataset_infos.json +0 -1
dataset_infos.json
DELETED
@@ -1 +0,0 @@
|
|
1 |
-
{"full_numbers": {"description": "SVHN is a real-world image dataset for developing machine learning and object recognition algorithms with minimal requirement on data preprocessing and formatting.\nIt can be seen as similar in flavor to MNIST (e.g., the images are of small cropped digits), but incorporates an order of magnitude more labeled data (over 600,000 digit images)\nand comes from a significantly harder, unsolved, real world problem (recognizing digits and numbers in natural scene images). SVHN is obtained from house numbers in Google Street View images.\n", "citation": "@article{netzer2011reading,\n title={Reading digits in natural images with unsupervised feature learning},\n author={Netzer, Yuval and Wang, Tao and Coates, Adam and Bissacco, Alessandro and Wu, Bo and Ng, Andrew Y},\n year={2011}\n}\n", "homepage": "http://ufldl.stanford.edu/housenumbers/", "license": "Custom (non-commercial)", "features": {"image": {"id": null, "_type": "Image"}, "digits": {"feature": {"bbox": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}, "label": {"num_classes": 10, "names": ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "svhn", "config_name": "full_numbers", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 390404309, "num_examples": 33402, "dataset_name": "svhn"}, "test": {"name": "test", "num_bytes": 271503052, "num_examples": 13068, "dataset_name": "svhn"}, "extra": {"name": "extra", "num_bytes": 1868720340, "num_examples": 202353, "dataset_name": "svhn"}}, "download_checksums": {"http://ufldl.stanford.edu/housenumbers/train.tar.gz": {"num_bytes": 404141560, "checksum": "4b17bb33b6cd8f963493168f80143da956f28ec406cc12f8e5745a9f91a51898"}, "http://ufldl.stanford.edu/housenumbers/test.tar.gz": {"num_bytes": 276555967, "checksum": "57ac9ceb530e4aa85b55d991be8fc49c695b3d71c6f6a88afea86549efde7fb5"}, "http://ufldl.stanford.edu/housenumbers/extra.tar.gz": {"num_bytes": 1955489752, "checksum": "e857e27d1e65bd1e7d3959b094061777f6506bbc39889a0df3bba6a729d60f9c"}}, "download_size": 2636187279, "post_processing_size": null, "dataset_size": 2530627701, "size_in_bytes": 5166814980}, "cropped_digits": {"description": "SVHN is a real-world image dataset for developing machine learning and object recognition algorithms with minimal requirement on data preprocessing and formatting.\nIt can be seen as similar in flavor to MNIST (e.g., the images are of small cropped digits), but incorporates an order of magnitude more labeled data (over 600,000 digit images)\nand comes from a significantly harder, unsolved, real world problem (recognizing digits and numbers in natural scene images). SVHN is obtained from house numbers in Google Street View images.\n", "citation": "@article{netzer2011reading,\n title={Reading digits in natural images with unsupervised feature learning},\n author={Netzer, Yuval and Wang, Tao and Coates, Adam and Bissacco, Alessandro and Wu, Bo and Ng, Andrew Y},\n year={2011}\n}\n", "homepage": "http://ufldl.stanford.edu/housenumbers/", "license": "Custom (non-commercial)", "features": {"image": {"id": null, "_type": "Image"}, "label": {"num_classes": 10, "names": ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "image-classification", "image_column": "image", "label_column": "label", "labels": null}], "builder_name": "svhn", "config_name": "cropped_digits", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 128364360, "num_examples": 73257, "dataset_name": "svhn"}, "test": {"name": "test", "num_bytes": 44464040, "num_examples": 26032, "dataset_name": "svhn"}, "extra": {"name": "extra", "num_bytes": 967853504, "num_examples": 531131, "dataset_name": "svhn"}}, "download_checksums": {"http://ufldl.stanford.edu/housenumbers/train_32x32.mat": {"num_bytes": 182040794, "checksum": "435e94d69a87fde4fd4d7f3dd208dfc32cb6ae8af2240d066de1df7508d083b8"}, "http://ufldl.stanford.edu/housenumbers/test_32x32.mat": {"num_bytes": 64275384, "checksum": "cdce80dfb2a2c4c6160906d0bd7c68ec5a99d7ca4831afa54f09182025b6a75b"}, "http://ufldl.stanford.edu/housenumbers/extra_32x32.mat": {"num_bytes": 1329278602, "checksum": "a133a4beb38a00fcdda90c9489e0c04f900b660ce8a316a5e854838379a71eb3"}}, "download_size": 1575594780, "post_processing_size": null, "dataset_size": 1140681904, "size_in_bytes": 2716276684}}
|
|
|
|