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b8e0f4b64f66a3ec

Date: 2017-07-01 07:43:33.526516
License:
Module: experiment.bench.dnn.mobile
Repo: upload
CID (DOI-like distributed ID): 4dcf435bb0d92fa6:b8e0f4b64f66a3ec

Files:
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misprediction-image-d07224814897d62c.jpg    (155KB)
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Cross-linking (dependencies):

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        {
          "correct_answer": "Electrical Outlet",
          "mispredicted_image": "misprediction-image-1298883fd487698c.jpg",
          "misprediction_results": "0.4771 - \"switch (561)\"\n0.0290 - \"safe (753)\"\n0.0189 - \"rubber eraser (997)\"\n0.0162 - \"laptop (228)\"\n0.0158 - \"toilet tissue (889)\"\n"
        },
        {
          "correct_answer": "tree",
          "mispredicted_image": "misprediction-image-4b459ebd7581c381.jpg",
          "misprediction_results": "0.8578 - \"greenhouse (684)\"\n0.0670 - \"pot (838)\"\n0.0075 - \"patio (679)\"\n0.0052 - \"lakeside (366)\"\n0.0038 - \"seashore (367)\"\n"
        },
        {
          "correct_answer": "backpack",
          "mispredicted_image": "misprediction-image-024cc2e4875a74ab.jpg",
          "misprediction_results": "0.1349 - \"stretcher (957)\"\n0.1336 - \"mousetrap (599)\"\n0.1166 - \"carpenter's kit (891)\"\n0.0985 - \"studio couch (311)\"\n0.0588 - \"carton (749)\"\n"
        },
        {
          "correct_answer": "numbers",
          "mispredicted_image": "misprediction-image-65933195f4baf853.jpg",
          "misprediction_results": "0.3583 - \"hook (562)\"\n0.0734 - \"black swan (421)\"\n0.0438 - \"nail (585)\"\n0.0311 - \"albatross (441)\"\n0.0282 - \"notebook (552)\"\n"
        },
        {
          "correct_answer": "whiteboard",
          "mispredicted_image": "misprediction-image-14dcfb02c2087c49.jpg",
          "misprediction_results": "0.3583 - \"hook (562)\"\n0.0734 - \"black swan (421)\"\n0.0438 - \"nail (585)\"\n0.0311 - \"albatross (441)\"\n0.0282 - \"notebook (552)\"\n"
        },
        {
          "correct_answer": "Backpack",
          "mispredicted_image": "misprediction-image-1d9f947e4c0a91db.jpg",
          "misprediction_results": "0.2107 - \"Loafer (973)\"\n0.0994 - \"sandal (751)\"\n0.0267 - \"swing (569)\"\n0.0221 - \"jean (748)\"\n0.0201 - \"sleeping bag (943)\"\n"
        }
      ],
      "prediction": "0.7336 - \"silky terrier (131)\"\n0.0523 - \"Yorkshire terrier (59)\"\n0.0311 - \"Australian terrier (4)\"\n0.0294 - \"briard (208)\"\n0.0228 - \"Norfolk terrier (88)\"\n",
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      "user": "",
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  "meta": {
    "cpu_abi": "arm64-v8a",
    "cpu_name": "Qualcomm Technologies, Inc MSM8998",
    "cpu_uid": "5699e9b747dd85e5",
    "crowd_uid": "8ea63e841698f4ad",
    "engine": "TensorFlow CPU",
    "gpgpu_name": "",
    "gpgpu_uid": "",
    "gpu_name": "Qualcomm Adreno (TM) 540",
    "gpu_uid": "2a776ea427cad5bd",
    "model": "Inception Imagenet 20151205",
    "os_name": "Android 7.0",
    "os_uid": "de98569847a92092",
    "plat_name": "SAMSUNG SM-G950U",
    "platform_uid": "dcbee93a8d3463d8"
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}

API desc:
{}

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Implemented as a CK workflow
                         
   
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