dataset_info.json for Stanford_dogs.py

dataset_info.json

{
  "citation": "@inproceedings{KhoslaYaoJayadevaprakashFeiFei_FGVC2011,\nauthor = \"Aditya Khosla and Nityananda Jayadevaprakash and Bangpeng Yao and\n          Li Fei-Fei\",\ntitle = \"Novel Dataset for Fine-Grained Image Categorization\",\nbooktitle = \"First Workshop on Fine-Grained Visual Categorization,\n             IEEE Conference on Computer Vision and Pattern Recognition\",\nyear = \"2011\",\nmonth = \"June\",\naddress = \"Colorado Springs, CO\",\n}\n@inproceedings{imagenet_cvpr09,\n        AUTHOR = {Deng, J. and Dong, W. and Socher, R. and Li, L.-J. and\n                  Li, K. and Fei-Fei, L.},\n        TITLE = {{ImageNet: A Large-Scale Hierarchical Image Database}},\n        BOOKTITLE = {CVPR09},\n        YEAR = {2009},\n        BIBSOURCE = \"http://www.image-net.org/papers/imagenet_cvpr09.bib\"}\n",
  "description": "The Stanford Dogs dataset contains images of 120 breeds of dogs from around\nthe world. This dataset has been built using images and annotation from\nImageNet for the task of fine-grained image categorization. There are\n20,580 images, out of which 12,000 are used for training and 8580 for\ntesting. Class labels and bounding box annotations are provided\nfor all the 12,000 images.\n",
  "downloadSize": "815912960",
  "location": {
    "urls": [
      "http://vision.stanford.edu/aditya86/ImageNetDogs/main.html"
    ]
  },
  "name": "stanford_dogs",
  "schema": {
    "feature": [
      {
        "name": "image",
        "shape": {
          "dim": [
            {
              "size": "-1"
            },
            {
              "size": "-1"
            },
            {
              "size": "3"
            }
          ]
        },
        "type": "INT"
      },
      {
        "name": "image/filename",
        "type": "BYTES"
      },
      {
        "name": "label",
        "type": "INT"
      },
      {
        "name": "objects"
      }
    ]
  },
  "sizeInBytes": "815912960",
  "splits": [
    {
      "name": "test",
      "numBytes": "322813870",
      "numShards": "1",
      "shardLengths": [
        "2145",
        "2145",
        "2145",
        "2145"
      ],
      "statistics": {
        "features": [
          {
            "name": "image",
            "numStats": {
              "commonStats": {
                "numNonMissing": "8580"
              },
              "max": 255.0
            }
          },
          {
            "bytesStats": {
              "commonStats": {
                "numNonMissing": "8580"
              }
            },
            "name": "image/filename",
            "type": "BYTES"
          },
          {
            "name": "label",
            "numStats": {
              "commonStats": {
                "numNonMissing": "8580"
              },
              "max": 119.0
            }
          }
        ],
        "numExamples": "8580"
      }
    },
    {
      "name": "train",
      "numBytes": "458077367",
      "numShards": "1",
      "shardLengths": [
        "3000",
        "3000",
        "3000",
        "3000"
      ],
      "statistics": {
        "features": [
          {
            "name": "image",
            "numStats": {
              "commonStats": {
                "numNonMissing": "12000"
              },
              "max": 255.0
            }
          },
          {
            "bytesStats": {
              "commonStats": {
                "numNonMissing": "12000"
              }
            },
            "name": "image/filename",
            "type": "BYTES"
          },
          {
            "name": "label",
            "numStats": {
              "commonStats": {
                "numNonMissing": "12000"
              },
              "max": 119.0
            }
          }
        ],
        "numExamples": "12000"
      }
    }
  ],
  "supervisedKeys": {
    "input": "image",
    "output": "label"
  },
  "version": "0.2.0"
}