Inspecting images for sensitive data

Cloud Data Loss Prevention (DLP) can detect and classify sensitive data within an image. Using infoType detectors and optical character recognition (OCR), Cloud DLP inspects a base64-encoded image for text, detects sensitive data within the text, and then returns returns the locations of any sensitive data that it's detected.

Given an image as input, Cloud DLP detects sensitive data in the image. The output of an inspection operation includes the found infoTypes, the likelihood of the match, and pixel coordinate and length values that indicate the areas within which Cloud DLP found the sensitive data. The coordinates at the bottom left corner of an image are (0,0).

Inspecting an image for all default infoTypes

To inspect an image for sensitive data, you submit a base64-encoded image to the DLP API's content.inspect method. Unless you specify specific information types (infoTypes) to search for, Cloud DLP searches for the most common infoTypes.

To inspect an image for default infoTypes:

  1. Encode the image as base64.
  2. Submit a request to the DLP API's content.inspect method. The request need only contain the base64-encoded image if you want to inspect for default infoTypes.

For example, consider the following image. This image is an example of a typical image file generated from a scan of a paper document.

Original image (click to enlarge)

To inspect this image for default infoTypes, send the following request to the DLP API's content.inspect method:

{
  "item": {
    "byteItem": {
      "data": 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",
      "type": "IMAGE_JPEG"
    }
  }
}

Cloud DLP returns the following:

{
  "result": {
    "findings": [
      {
        "infoType": {
          "name": "PHONE_NUMBER"
        },
        "likelihood": "UNLIKELY",
        "location": {
          "contentLocations": [
            {
              "imageLocation": {
                "boundingBoxes": [
                  {
                    "top": 98,
                    "left": 986,
                    "width": 102,
                    "height": 117
                  },
                  {
                    "top": 98,
                    "left": 1092,
                    "width": 29,
                    "height": 114
                  },
                  {
                    "top": 95,
                    "left": 1111,
                    "width": 82,
                    "height": 115
                  },
                  {
                    "top": 95,
                    "left": 1197,
                    "width": 29,
                    "height": 114
                  },
                  {
                    "top": 90,
                    "left": 1203,
                    "width": 185,
                    "height": 118
                  }
                ]
              }
            }
          ]
        },
        "createTime": "2019-11-01T22:07:05.870Z"
      },
      {
        "infoType": {
          "name": "US_SOCIAL_SECURITY_NUMBER"
        },
        "likelihood": "VERY_LIKELY",
        "location": {
          "contentLocations": [
            {
              "imageLocation": {
                "boundingBoxes": [
                  {
                    "top": 98,
                    "left": 986,
                    "width": 102,
                    "height": 117
                  },
                  {
                    "top": 98,
                    "left": 1092,
                    "width": 29,
                    "height": 114
                  },
                  {
                    "top": 95,
                    "left": 1111,
                    "width": 82,
                    "height": 115
                  },
                  {
                    "top": 95,
                    "left": 1197,
                    "width": 29,
                    "height": 114
                  },
                  {
                    "top": 90,
                    "left": 1203,
                    "width": 185,
                    "height": 118
                  }
                ]
              }
            }
          ]
        },
        "createTime": "2019-11-01T22:07:05.871Z"
      },
      {
        "infoType": {
          "name": "EMAIL_ADDRESS"
        },
        "likelihood": "LIKELY",
        "location": {
          "contentLocations": [
            {
              "imageLocation": {
                "boundingBoxes": [
                  {
                    "top": 340,
                    "left": 334,
                    "width": 57,
                    "height": 58
                  },
                  {
                    "top": 340,
                    "left": 384,
                    "width": 12,
                    "height": 58
                  },
                  {
                    "top": 340,
                    "left": 387,
                    "width": 79,
                    "height": 59
                  },
                  {
                    "top": 341,
                    "left": 467,
                    "width": 12,
                    "height": 58
                  },
                  {
                    "top": 340,
                    "left": 476,
                    "width": 119,
                    "height": 61
                  },
                  {
                    "top": 341,
                    "left": 589,
                    "width": 12,
                    "height": 58
                  },
                  {
                    "top": 342,
                    "left": 592,
                    "width": 45,
                    "height": 58
                  }
                ]
              }
            }
          ]
        },
        "createTime": "2019-11-01T22:07:05.869Z"
      },
      {
        "infoType": {
          "name": "PHONE_NUMBER"
        },
        "likelihood": "POSSIBLE",
        "location": {
          "contentLocations": [
            {
              "imageLocation": {
                "boundingBoxes": [
                  {
                    "top": 394,
                    "left": 335,
                    "width": 50,
                    "height": 77
                  },
                  {
                    "top": 394,
                    "left": 380,
                    "width": 17,
                    "height": 77
                  },
                  {
                    "top": 394,
                    "left": 387,
                    "width": 51,
                    "height": 77
                  },
                  {
                    "top": 394,
                    "left": 433,
                    "width": 17,
                    "height": 77
                  },
                  {
                    "top": 394,
                    "left": 436,
                    "width": 77,
                    "height": 77
                  }
                ]
              }
            }
          ]
        },
        "createTime": "2019-11-01T22:07:05.870Z"
      },
      {
        "infoType": {
          "name": "DATE"
        },
        "likelihood": "LIKELY",
        "location": {
          "contentLocations": [
            {
              "imageLocation": {
                "boundingBoxes": [
                  {
                    "top": 572,
                    "left": 1129,
                    "width": 71,
                    "height": 38
                  }
                ]
              }
            }
          ]
        },
        "createTime": "2019-11-01T22:07:05.921Z"
      }
    ]
  }
}

Cloud DLP has found the following infoTypes, though its match confidence for each one varies:

  • A phone number (unlikely)
  • A US Social Security number (very likely)
  • An email address (likely)
  • A phone number (possible)
  • A date (likely)

If you were to draw each of the bounding boxes on the image, it would look like the following. Be aware that Cloud DLP often uses multiple boxes to indicate where a single instance of sensitive data is in the image.

Bounding boxes overlaid on image (click to enlarge)

Note that, in addition to detecting the handwritten Social Security number, the email address, and the phone number, Cloud DLP has also detected the year. Assuming that's not optimal behavior, the next example demonstrates how to inspect for only certain infoTypes.

Inspecting an image for specific infoTypes

If you want to inspect an image for only certain sensitive data types, specify their corresponding built-in infoTypes.

To inspect an image for specific infoTypes:

  1. Encode the image as base64.
  2. Submit a request to the DLP API's content.inspect method. The request must include:

Consider the original image from the previous section. To inspect for only US Social Security numbers, email addresses, and telephone numbers, send the following JSON to the DLP API's content.inspect method:

{
  "item": {
    "byteItem": {
      "data": 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jNakkMcrK7jJQ5X2NMntbe5AE6BsdPWgDOtJJftEtk0vnKEyG7g9MUmkTwpa+TIwR4ydwY471pQWtvbAiBAuetRzWFnO/mSxgse/I/lQBVnuorqxuGiBwoIye/wBKpXH/ACD7L/eT+VbvkQiHyAoCEY2jpSNawOiRsvyxkFR6YoAo6z/x4N9R/Oq90RBe2lxIcIF2k+hx/wDXrZlhjnQxyjcp7VUvt4iVVhEyZ+de+PagCjqlxBJ5KRuGbzAcA54rdrmktzcyRpb25giVgzlupx9a6WgDmFhT7fcRTTPBuO4YbAINX7SC1S6Zo52lkCYOTng+9aM9tb3IxOgbH5/nSR20MK+XCoRc8470AYdv/wAgWb6t/SrFwCdDXH9xP6VqpbwrCYQgCN1XtUnlR+X5O0bMYx2xQBWguIFtEkLrtVVBOehxVsEMAw5BrMudPBt/s1oAiu4L9entWmBgADtQBhyrZ3N1JvZreaPjdnGfem28k0wubHzPOCoQr/UdM1rz2ltc4M6BiO/f86fFDFAuyFQo9qAOdsooGtxvupImXIZd2MfhTriCJNMDWrGRBJvJP5GtuWxtJn8yWMFvX/GrARFTYoAXGMdsUAZV/d28unuUdSXUYGefyq3p/wDx5Q/7ooXT7JWLCJcng/jVpVVFCIMADAFAGPcstvqsVxLwjoVz2BqHVJopLm1WNgxD84Oe4rclhinTy5VDL6GoEsLOMAJGBtO4fWgCg7i21cyTfKkqYVj0yMU3UJUuZ7e3t2DtvDEjnAFa8sMU6bJlDD3pkFrb22fIQLnr6/nQBYrlrKBP3kMtw8Lox+UNtB966mq09na3J3TRhj69D+lAGdbw20cdy0ErSsVIYnnnB71TlBOhRkDODk/ma6FYIkjMKKAh4wOnNKsMSxeSFGzpt7UAZeo3du2nsEdSXAwM5NRztam0tobtTtdVww42nA71fXTrJM7Yl+br3qy0MTxiFlBQDGCOOKAMPfJZXEMcE5mSRsFSc4HrmplB/txs/wDPPj9K0IbK1t23wxhT69T+tTeTF5vn7RvxjPfFAFCRf+JtG2P+WR/nUN5/yFbX6GtYxoZBKQNwGAfakaGJpFlZQWXofSgDItZEtb+5inIQyHcpPAIpXdbrVYvJwwhUlmHTntmtOe2guRtnQNjpmnQwQ267IVCj2oAx9NlitXntp2CMHJBPGQaW0kSXV53jII2Dke2K05rO2uCGmjDEd6fHbwRNviQKSMZAxxQBK3Q1haWVfT3t1Ybzu4zzW9VeO0topTPGgV26kUAc/YRRPBte5eFkJBTdtA/A1NJFbx6XO1vIZAzDJPrkVsS2NpO/mSxgt6/41KYITF5JQbP7uOKAKA/5A/8A2x/pRaf8gkf9c2/rWj5Ufl+TtGzGMdselCxRpH5SqAoGMdqAOWH/ACAj/v8A9a2Zr61Fkzh1OUwBnnJHpTNRtf8AQDDap3B2r9asrYWhZZWiXeMf5x0oAxWiaKwtJ5B8sb7mHsxzWjqF5bGycI6uXGAAc9a1SqsCrDIPY1VjsLSKTzY4wG9f8KAMqaNov7Pjf7ysM/pXQVG8MUjK7qCUOVJ7GpKAMjURm7s/98/0oj/5DMv/AFzH9K03ijkZXdQShypPagRRiQzBRvIwT3xQBnS4/teLP/PM4/WoNOljtpLi3nYI3mFueMg1sGKMyCYqN4GAe+KjntLa5x56BiO/egCobyO5S4SIZWND83Y8dqzWjaTQk2DO35j9ATXQpDFGnlIoVfQDiljjSJBHGAqjoBQBmXN7bS6e5WRcsmAM85I6YqjLzo0BPHzL/M1sixtFcyCJdx6/jUxghMYhKDYOg7UAZN0y22qQ3MnCMpXPoaj1K4hlntkjYMRICcc45Fbkkccq7JFDA9jzUS2dqmAsSjByOO9AGZK6w6wrynarR4BPTNNnnim1W3ETBtuc45HIrYlghnAWZAwHTNNS2t48eXGo29MDpQBn2H/H9ef7w/rRF/yGZf8ArmP6VqhEVi6qAW6kDk/WkEcYcyhRuIwTjnFAGTZMkeoXSOQpZlwCevXpWtIC0bKOpBFNaCFpBMyKXHRsc1LQBh6XdW8NiFlcKUJyD16+lJpJ32c5X+J2x+IFaptLVpPNaNS3ripUjjjBEahQTk4GOaAMvRpIzZrGGG4Ekjv1rXqFLeCJzJGiqzdSBU1ABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUhJ4xS0UAFFFFAH//S6SiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAorP1QlbGRlOCMcg47irEUiLbJI52rtByT7e9AFiiqsN7aztsikDN6VQkmEWrEyNtRYsnJ460AbNFV4Lq3uc+Q4bHbvTpriG3XdM4Ue9AE1FQwzw3C74WDD2qN720jBLyKMHB570AWqKhluIIFDyuFB6Z706KaKdd8TBh7UASUUVVe9tI5PKeRQ3pmgC1RVK+uxaQFwVL9VU9+RmpredbiJZFIJIGcHODQBPRSMyqCzEADqTWJqt4htc20o3bwDtPPf0oA3KKYGCxhnOAByTTIrm3mOIpFYjsDQBNRWXPJINUt4wSFKsSM8Hg1oSTRQjdKwUe5xQBJRTI5I5V3RsGHqDmmm4gXO6RRg4PI4PpQBLRTHkjjG6RgoPcnFKjpIoeMhge45oAdRSMwUFmOAOpNRG5t1xukQZ5HIoAmoqN5oY8eY6rnpkgU8EMAynIPQigBaKi8+ANsMi7umMjNSkgDJ4AoAKKhFzbkEiRMDr8wp5kjUqCwBbpz1+lAD6KjWaF22I6s3oCCaezKgLOQAO5oAWimJLHIMxsGA9Dmn0AFFMeWKLHmMFz0ycU13BhZ0OflJBFAEtFZFtLdS6YJEcGU5+ZvrWopIjBkIzjk9qAH0VGssTjKOpA9DTyQCATyaAFopCQOpxmhmVBucgAdzQAtFIGVhlSCPaloAKKCQBk8AVjpcX18zNaFY4lOAzDJOKANiisy2vJvtBs7wASYyCvQitIkAZJxigBaKTIxnPFAIYZU5FAC0VWgN0ZJPPChc/Jjrj3qzQAUUm5c7cjPpS0AFFJkZxnmloAKKimmWGJ5TzsBOPpTbW4F1As6jAbsfrigCeikyAcE80tABRRSAgnAPSgAYkDK8mgHIzS0gIIyOaAF57UUUUAFFFGQOtABRRRQAUVS1CV4bOSWI4YYwfxFT27F4I3Y5JUE/lQBNRRVaM3JuHEgURcbcdaALNFIWVRliAKWgAopNyg7SRn0paACikyM7c8+lLQAUUm5c7c8+lLQAUUgZW+6QcUEgDJOBQAtFAIIyKKACiikJA6nFAC0UVQ1KaSCzeWI7WGOfxoAv0U1SSgJ7ilDK3KkH6UALRQSByaQMGGVOR7UALRSEgDJOKMjGe1AC0UgIYZU5HtQSAMk4FAC0UZHWqlpdrdqzKpXaxXn2oAt0UVQ1Gea1g8+HB2kbgfQ0AX6KajiRFdejAEfjWbb3c9zLcCMLsj+VM92+tAGpRVIzy29mZ7oDeoyQvTrxViCUTwpMBjcM4oAlopNy525GfSloAKKQMpOAeRS0AFFISAMk4FKCCMjmgAopCyr94gfWloAKKQsq/eIH1paACikDKSQCMiloAKKCQOTRQAUUgZW+6QfpS0AFFIWUDJIAo3KBuJGPWgBaKQMrDKkH6U15Y48eYwXPTJxQA+ikyMZzxQCCMg5FAC0Um5SNwIx60xnGCqMu/GQCf1+lAElFQWxnMINwVL99vSniWJm2K6lvQHmgCSiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAP/0+kooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAzdWP+gScZ6fzFQ3htvssBuQzdNqDqxx3q5fwPc2rwx/ebGM/Wq91ZzSxwvEQJYcEZ6Hp/hQBl3jk+RILYwFXGG4H4Vckijm1oCQbgI84PrST2up3WxpjHhGB2jPPvmpri0vGvvtdsyrhMc9/Y0ARXsaW99azQgKWbaQOMj/JpYFS61Od5gG8rCqD296ljtbue6W5vSoEf3VX19afPa3CXP2uyK7mGGVuh96AIZI0t9UhMIC+aGDAcdB1xUGlwxSXV00ihir8EjOOTV23tblrn7XeFdyjCqvQUthaS20s7yYxI2Rj0yf8aAMvzN+oTvJA0+w7VAGQoFT2O/7e0iQtDG68gjAyKsy2lzFdG6sivz/eVuh96s2y3vmNJdMADwEXoPfNAC6hK0NlLInUDA/HisGOSIWnk/Y3YleX28knvnFdNNEs8TQv0YYrKii1W2j8iMxuo4VjnIoAqPGx0Um4TEicAsOcbq27OOOO2j8tQuVBOB1OKhmtZprBraR90hH3unOc1JZi5WER3KqCoAG05yB3oAo6p+9lt7QnCyN834VBrNrbxWqvFGqkMBkDHGDWjf2j3KK0J2yRncpNULq31O+hEciogU565yf6UAPvB9ou7azfPlkbiPXA/wDrUapbxQQC6t1EbxsCCvGfarN3ZyS+XNbkLNF0z0PtUEkF/fFY7pVjiUgsAclsUAJMc6tbH1Q/yNNtokvL+4luAHER2KD0FW5baRtQhuVxsRSD696iktrq3umurPDCT7yHjn1FAEJRbPVY1h+VJlO5R0yM9qZY20E13dPKgYrIQM8jkmrdvbXEl19tvMBgMIo7VJZW0sE1w8mMSPuXHpzQBlGaOTUZWuI2mWP5VVV3AfUVY0/K30nkxvHC65wykDdU0tvdW1013ZqHEg+ZCcc+tWrX7aztJdbVU/dQc4980AOv/wDjym/3D/Ks+0sbV9OVnQMzLksev51p3cbS20kacsykCo7WF4rJYWGGC4I96AM3S7O3ns/MmQOzZGTzgDgY9KNNIbTZEkcooLDd6CtDTreS2tFilGGGSR9TVG20+YWE1tLhWc5HOfTHSgCjI2n/AGRo4YJGABxJt7+uamuZGksbOBif3pAY+w4/rU5j1N7Y2XlooC7d+eoxUj2Uj6dFExCSxYIyeM/X3oAi1WytYrIvGgVkxgj3Pf1pt/Gsr2UbdG4OPwqLUJdQktGW4jWNQRk5yWOe1aE9tLLJaSIOIjlvbpQBV1O3gtxBNAgRhIBkelWNRFp50TXRZsZxGozn3qbUreW5jjWIZKuGPOOKhu7e5S8W+tlEhC7Sp4/KgCjC8S6nCbeJoQ4IYMMZ4rpaxBDfTXkN1MgVVz8oPI+tbdAHPN/Z4upPN3XMhPQLnb7cUumkBLuNMhFPyhuoyDUkMd9YNJHFEJVdtwbOOvrUlnb3UZuTcAZk5GOhOD0oAoHA0AfX/wBmq1fsZXtbLJCyYLY7ila0uP7HFsFzJ6fjmp720mkjhmg/1sOCAe/tQBQ1Swtre3WSBdp3AdTzVu5/5C1t/ut/I1T1Oa8lt186HylDDOTkk+1aN9BOZobu2Xe0fBX1BoAj1P8A19p/11H9KTUBZi4V7xy3GFjH8+KimW/u54JHh2JG4JGQT2yfpU00NzBfm8hj85XXGM4I/OgCnZSQrqQS0DJG6cq3qK6SsSJL2TUUupoti7SvBBwOetaUUlw00iSxhY1+62etABeEi0lI67G/lUGl4+wRY9D/ADq+yhlKtyDwaxoFvdOzAsfnRZypU4Iz2NADr3jUrRh1O4fhVZLeK61WdJgSoAO3OATxVy3t7ia6+23a7CowiZzj60sEEyalPOw+RlAB9elAFWSJLrUBZtxDAgOwHr/nNW49P+zXSzWp2xkYdCTz9KZcQ3EN4L63XzAV2uvf8KfC97cXAkdTDCo+6erGgCLTf+Pm7/66f41Lq/8AyD5Pw/mKLGCWKe5eRcB3yvuOaXV/+QfJ+H8xQBUl0yAWZmQnzVXfvzySBmmzXc01lbojEPOdpI68cGlkmvpbUWqwHc6hd+flx61Pcae32OKKDHmQkFc9z3oAiutOht7cz225JIhkMD1x1zVe+kNylk+dpkPJHGM4zVmaW+vITbLAYy3DMx498U67s5c2iQKWWE8npxxzQA670+0is5NqEbQW6nqBSaTAiWQlT5XkByeo4JxxWjcxma3kiXqykCsu0S4exexeMxsqEbj0JOaAM6QaWsbI8jSy8/vOetb2mSPJYxvISTg8n2NZ8Ju0tfsa22G2kbiRt+tX9NV4rKOOVSrDIwfrQBT1VDJcWsYYruYjI69qhvrWGw8me2BVg4U8nn61evYZZLq2eNchGJY+nSjVIJZ4o1iXcRICfpzQBBebru+SxLFYwu5sd/ao7qBNNkjurXKqWCuucgg/WrV3BOl0l9bLvKjay5xkVBItzqUsavEYYkbcd3UkelADZoFudWMbltojBYDjPPSlWFbLVI0t+ElU5XPpVpYZBqjT7TsMeM+9E8Ej6jBKq/KgOTQBpHpXN6ZYQXVsZJ9zckAZ4H0rpD0rmNNup7a1OIWkQscFeue+aAJIi8UV5YsSVjUlSeeCK1LM/wDEujPX93/SqltaXEkVxLONklwCAPQdqiguL2K3+x/ZmMiqQD/DQBEn/IAb8f8A0KpbkeRFZ3y/wBVb6EU5Laf+xTblD5n93v8AezWg1v51gLdxgmMDnsQP8aAKs/8ApOpxQjlYV3n6np/Sks/+Qndf8Bp+l200KPLcjEjkD8FGBTrWGVL+5lZcK+MH1oAz9Nsbe5jkknBf5yAMnj/69WdLDJFcQb8LG5Ck9qs6ZBJBAyygglycVBDaTGK7jYbDKx28+tAGXJ/ZSRum55Zef3nPWrE0ry6GrucnIGfocVNCb2O1+xLbYYAjdn5ee9NNpcnRxbbD5gbpx65oA0LG0ghjSZR87KMsTknPNV9bz9kUA4y4/rWpCrLEiv1CgH64qjqkMs9uqQruO8H8KAKN/p8FtZmePPmoQd+TknNO1G5PkW8UjFVlALsOuMCrmobrm1kggG88dD3BqO5tZmgglhA82ADg9+ORQBkzTWELRzaeSHVhkc4I75zV+VBf6mbeY/u4lB2+pOP8asC5v5WVEt/L5G5mPGPamXMVzb3n222XzAw2uo60ARG1itdTtxDkKwb5c8DjtU1if+Jhd/Vf61B5k8up27zR+WMNtBOT05zTytzZ30syRGVJcH5eoNAEiEDV5ST0iH9Kyop7G6d59RYliSFXnAH4VqWkd099JcXMewOmAODUcK3Wml4ViM0ROVK9RntigB2kTBjNAjFo0IKE9cGptZx9gfPqP51atWuXVnuEEeT8qjqB71FqcUk9m8cQ3MSMD8aAIb9Ymt4/tEvlxjGQOre1ZBlskuYG0/cpLAMOcYP1rVvrectBPEnmeV1TNV7gXl5JC4gKIjgnJGetAEs6fbtRNrJnyolDEA9SaZLCmm3cMlvlUlbYy9RU9zDPBeC+tk35Xa69/qKYEub+5jlmj8qKI5APUmgCsLeO51eaObJUANjOAeB1pLx7ZbtbOclIIlztGeT6Vegt5k1SadlIRlwD+VJcwTxXgvbZd+Rtde5HqKAM+Ce1iv4xYsfLk+Vl5xnt1pGuLS4u5Wv2O1DtReccd+K14JruaYEw+VGBzu6k+1VdlzY3MrxRmWKU7sDqDQBXsRbzSzWSEvAQGUHPHTPvT9Ft4sSTY+dXKg+grStZLqVmeeMRr/CP4vxqpp6XFrLJbyRnazlg46UAbFRzRLNE0T9GGKjt5J5N/nx+Xg4XnORVigDAtrowabKrnEkGU/wq1bW/2fTGVvvMjMfqRVW60+aS/BQfuZCGf0yK2p1LwOi9SpA/KgDAeGKTRUmcZaNTt59TV+zgjj04FD5ZkQFm9OOtCWsp0n7MRh9pGD65zUUcdxPpzWjRmNlUKCT1IoAy5f7KWEpFvaUDIkGeTV+7upE02AbiGlADN7Y5o33zWn2NLbawTaSSMdO3ualayml0+FB8k0WCM+ooAy5202OEPZMwmQgg88/XtXVxP5kSyf3gD+dZn2m/cCNLbY/dmPyitYdKAMLy11DUZUnyY4cAL0BPrVqKzNlO0sLYgKklCScH1FRSR3NpePdQJ5qSgblHUEVNbm8uJmknXy4duAhwSfc0AUrG0jv42u7zLs5OBk4A9qdbkwNdWOSVRSy57AjpSwC700NAsRmjzlSvv2NS29rcbZ7m4H72ZSAo7DHAoAq6dp1vcWayT5YtkDJPy8npTILmSHSJG3HKsUU+mcVrabFJBZpFKNrDOR+JqjbWMrafLbSjYzsSM/higBh0y2WwMo3eZs3bsnOcZ/KopiRo8HPVl/rUkk98lk1u8JBVCC+eMAdfrTvsz3WkRLF95cMB64zQBc1f/kHyfh/MVn384CW1s7FI2UFyPTHSn3Ul/eWxgW3KnjcSfQ9qsXNrcFIJ4P8AWQgfKe/HIoAy5JrGGaKXTyVYNhhg8qfrXV1lpcX00iqtv5a5+cv/AErUoA52ztILq5ujONwWQ4GTjknmkt7GFr6e2ckxR4ITJxkj+laFhBLFNctIuA75X3HNOt4JEv7iZhhXC7T64FAFO1RbbVZLeEbYygOM9+Kil/s1Z5PtJaeQk5wD8vtxV5LeUaq9wV+QpgH34qrbreaf5kSwebubKsD1z60AR2D5s7uNSdi7toPUAg1o6V/yD4vof5mq9hbXCi5S6XaZTnI6HOc4plsdRtrf7KIdxUkK+RjB7mgCpB/yBJv94/zFX7S0t0s1uAMyGM5bnPIqCG0uV0mW3ZP3jHIHHtWnDHIlisR++I8fjigDNto5X0XZB98g4x9eaqImmsiwuGtphj5mznP8q0oba6GmLApMUq5I59+nFQTjULy3FtJbgMcZckY470AbqghQGOSByfWlpkaeXGqZztAGfpT6AEAxS0UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH/1OkooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKZLIkMbSvwqjJoAfRTI5FljWRPusMin0AFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFQXFvHdRGKXODzxxUrusaGRzhVGSaEdZEDocqwyDQBmx6WgkDzSvKFOQrHIzWpRRQAUVEs0TyNCrZdOo9M09XR87CDg4OPWgB1FFFABRRRQAUUUUAVby1W8i8pmK4IOR7VaopiSxyFlRgSpwcdjQA+iiigAoooBBGRQAUUUUAFFFFABRRRQAVXurcXUDQMdobHI9jmrFFADVUIoUdAMU6iigAooooAKKKKAD3ooooAKKKKACiiigAooooAKqWVr9jh8ndu5JzjHWrLuka7pCFHqeKQyRqQrMAW6Anr9KAH0UUUAFFFFABRRRQAUUUUAFFFFABRRRQBDDBHBnZnJPJPNTUUUAFFFFAFaS2ElxHcE4MeePXNWaKKACiiigAooooAKKKKACiiigAooooAKKKakiSAmNg2Dg4OeaAHUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABTJIxLG0bZAYYOOtCyRuxVGBK9QD0+tPoAyG0yV1EMlw7RD+HHP51qoixoEQYVRgCnUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH//1ekooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAqX1y1pbtOoDEEcH3qlPNcT2UzyRCOMoSuTlvyqTWf+PB/qP50+6/5Bj44/d/0oAowXl7HZJJHBujRRyTycdTitL7dD9jF63CkZx3z6fnTIP+QYuOf3X9Kx5VY6LCw5Ctlh7ZNAGgb+9SP7RJb4i6nDc49alutQW3to7iIb1kP6Hmpbi5t/sTSlgUZDj3yOlYsiNHptoH6mQH8DkigDRa/uoislxBsiY4znJGfWrF5eG3ZIYk8yWTovT8ai1j/jxb/eX+dQTER6xC8hwrJgZ9eeKAJ47+ZLhbe8iEZf7rA5Bqe1umuJp4iuBE2B79adNcWyzRwyDe7H5RgHHv7VRsGC312jHBLAgH05oAuR3TPfSWm3ARQc+ucf41V+33Uzv9jhDohxuJxkj0ptuyNq87IcjYOntiooIVm3zadM0PzfMjDjP0oA1bS6W7i8wKVIJUg9iKLu5S0hMrgnnAA7moNOuXuYmMmNyMVJXocd6TUrmS1hUxY3OwXJ6CgCudSuYSGu7cxxscbs5xn1q7dXi221VBeR+FUd6xdShuYrTM9zvyR8uAM0+9Ev8AaEBR/LymFYjIzzQBfgv5fOW3vIvKZ/unOQaSXUXS6e0ihMjKBjB9s8+lV3s7gzQm6uVJVsqMYJ+lS2//ACGLj/cX+lAE9pfPNM1tcR+XKozjOQRTJb+VpXhs4TKYzhjnAB9KY3/IaXnH7r+prO0+K7YSRwziJlc7lIyfrQBuWt4lzGzkFChIYHtiqX9pXDr58NuWhGcsTyQPaktojaG5uZJRK2MsF9R61HH9uubb7U9wIkIJ2hRgAUAXZdRjSzF5GpZScY6VA+qSoonNuwhP8RPPPtWWf+QEP9/+tbmo/wDIOk/3R/SgC8rB1Dr0IyKrC7H2w2bKQdu4HsadZf8AHpD/ALi/yqlqQ8mSG+X/AJZthv8AdNAFs3Q+1i0VcnbuJ9KqnUndm+ywNKiHBYHA/D1qK0Vp0ubwfelyE+g4FVtNjvHtR9nnVVBOV2gkH3oAvT3KXWlyTJxlSCD2PpVuxGLOHP8AcH8qyxbm3sLr94sm7JO3se9atn/x6Q/7i/yoAbd3aWqrlS7ucKo6moIdQZp1t7mIws33cnIP41SvhJ/akOxxGSmFYjIzzUstndSSxNczodjAqMYJ9qAH2xH9q3OPRabbTxJBLLaQMT5hDKDkn3p1rn+1brPov8qbo/8AqZv+urfyFADNHuZpYzHIrMMk7ycj6VsyOsSNI5wqjJrL0T/jyP8Avmr90YRbuLg4QjBP1oAz/wC1iEExt3ERP3v64q7PewQW4uScq2NuOpzWZtu7S18yORJ4AM7WGDtpt1IjvYzY2RE5x2HTFAFxNSPmIk8LxCQ4Unpmp7q9S3dYlUySN0VeuKfd/ZfLH2r7u4Y69e3SsjFydVmELKr7RjfzleOlAGpbXq3DtC6mOReSrenqKradj7Rdt/00/wAabHa3ZvkuLiSMlVIwuckfT6mq0O/ZqBTruOP1oAttqoyxhheRE6uOlWJb+FLQXiZdDjp1rMsF1BrRPs7xbOeCDn8aintntdJkjdlbMgPy9O1AGn9sW4hlJicRBCcnjcPalguLa209JgCsYHAPJqa5/wCPCT/rmf5VmqtvJpMMdw+zd90++TQBYXVVBXz4niV+jEcVbu7yK0UF8szHCqOprNnkvbSPN6EnhyATjn8qkmK/2tBu+7sO3680AOGroCqSxOjsQACPXvV43SC6Fpg7iu7PaqGrY/0f/rqKH/5DSf8AXL/GgC/LdJDPHAwJMucEdOKhub+O3fylVpZOu1ecD3qte/8AIRtPq1Uoftp1C5NsU3bud/XHbFAGzaXsd3lQCjr95W6ip55lgiaZgSFGeOtZltbXgvjc3BQZXBC/pVvUiRYy4/u0AVjq8O0SLHIU7tjgUSatEPmhjeVR1ZRwKW3AOkAHp5Z/rTtNXbpie6k/qaALaXUElv8Aag2Exkk9qof2xCDuaNxGeA+OKp2UyW+kNJKocbjhT36Ut0NRaxdpPLWPA+UDkDtQBszXUUAjZskSMFBHv0pbm5jtYvOlztzjj3rFuji1sSegZOfwFXNaOLEj1YUAWbm/htXRJQfnBIwM1UubiCe3SS5jkQeYAB0OfX6U27AOpWmfQ07Wf9RF/wBdR/WgC9dXkVoF35ZmOAq8k1DbahHcSeQyNHJjO1hjIqO9hE1xGYpQk6AlQecio0mkF3HFfRJ5hB2OvP1oA2CcDJ7Vk/2vE67oYpJPXA6fWtVhlSKy9GA+wjHXcc/nQBdtrmK6i82I8dDnqDVN9VhUnYjuinBdR8o/GqEWR/aBh4AzjHrzmn2P9ofY0WBYjGR3zn3zQBY1SVJtMMsZyrbSPzpt5g3Fjjpn/Cqk1vNa6O8UxBO8EYOeMird3/r7H6/4UAaFzeRWu0PlmboqjJNNtr6G6Zo1DK69VYYNZkhuv7Wk+zhSwQY39AOOlTR29818l1OI1wCp2k8igCX+1rdsiJHkYHBVRzx3qaK/hmtzcIGO04KgfNn6VV0bmKZscmU/0o07/j8vP98f1oAj0q9lmZ45d7HccMRwB6GrM2pxxyGOJHlK/e2jgVU0gsILjZyd5wPfFV9N/tD7Mfsvl4LHO7Oc+9AG7DdwTQG4RvkHXPbHrVD+2I/vmKTyv7+OKjgtWihuftrKiSnnaeAT/kU0re2ttxsuLcL0PB20Aas93Bbw+e5yp6Y759KzzrEca7poZEz0yOtQXTRubF1G2IsDj06Yq1rWPsLf7woAuSXccUsUJBJm6H/GlubpLXZvBO9gox71m3f/AB+2X4/0p+rkf6OP+mooAuXV7Ha4Ugu7dEXkmm2t9HcsYirRyKMlWHNZcv2o6vJ9n27wgxv9OOlWI7a/a+jubkp8oIO3uMUAbVFFMkkWKNpG6KCT+FAGBqbSzTt5Jx9lUP8AiT/hW2lwj2wuRyu3d+lYNk94EkmFv5onJJO4Dj0qWwd0tLizlG1olYgH0IoAs/2vGyCSKKRx3IHA/GnHVoWUG3R5e52jp9adpAH9nx++c/mai0QAWrY/56H+lAF+1uoruLzY846EHqDVJ9WiDHZG7opwzgcCs+1Zxa3wTqCf61LZDUvsiCARGMjjOc++aALd9fAWXmW+4+YMhlHTnv6VY0+4a4t1LKwKgAlh97jqKzjby2ukSxSkE5yMHIxkVrWX/HpD/uL/ACoAS7u47NFklBILbeKp/wBrxBwHjdI2OA5GBTda5giB/wCeg/kak1gD+z39iv8AOgCS6+z/AGq380MXJOzHT8aW5v0t3EKq0shGdq84HvVW5BNzY556/wAhSzRSNePNYyr5oADo3SgC5a3sV3uVQUdfvKwwRVbSP9RJ/wBdGpbWffdyRTxKk6ryy8gjim6OP3Mv/XVqANGeeO3iM0pworOTVULgSxPGrHCsw4NWNRjhmt/Kmfy8kbT71QuJLu3T/TkSeHIyRwfrigDVNwguRa4O4ruz2x0pJLpIriO2IO6TOD24qmx/4m6Z7wn+dNuz/wATS1Hs38qAJ7nUEgk8lEaWTGSFGcfWpLS9iuwQoKuv3lPUVTkhka6knsJV8zADoenFJFMztcRyRrHcqhyV7jHFAEkmqxhysMbyhThmUcCnT3Nrc6e8x3NH0IHB6im6Nt+wLjrk5/Oorz7MLC4+ykdfmwe+RmgCy97b2cEO4NscADuQMd6jGqxiQLNE8ascBmGBVW6xssAem5f5CrWs7PsLbuuRj65oAkufs/2y380NvOdpHT8az59QlXUUCrJsUEFMct15A71LOW+1WBk5ODnPrgUXH/Ibg/3D/wCzUAbYOQDVC51GOCXyERpZAMkKOgrQrHM0813JFYqibDh3Yck0AXLW9iu9wUFWT7ysMEVXk1RFlMUMby7ThioyBVWyEw1OcTEF9gyV6dqn0Xb9lb+/vO71zQBV0xkmubt+drc+hwSat21zbW2nfaIlfy1PQ9eTiq9h/wAfl79f6moYz/xIW49f/QqALraxEMP5Unln+PHFSag9q9tG825kZgRt9xxUjBP7MO7G3yv6ViyZ/se3z/z0/qaAN26vYrTapBd2+6q8k1HbajHcSeQ6NFJ1CsOoqO8hWW5jMMojuEGVB5yKZFNMt3HFfRp5hB2Ov60ATXGopDL5EaNK45IXtT4LyK7jcYZSowyngiqumf6+63ff8zn6c1bP2Xz5dmPO2fNj09+1AFW2uba2077REreWp6Hk8nFDauigSCKQxf38cVnL/wAgBv8Ae/8AZq17gD+y2GOPK/pQBZluoYbf7Sx+TAIx3z0rPOriNPMmhdAfu571Rnx9gsi/3Ny7vStPV8f2fJ07Y/OgDRRg6Bx3GadUUH+pT/dH8qloAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigD/9bpKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAI5YY50Mco3Ke1K0aPGYmGVIxj2p9FAEaxRrH5KjCAYx7UJDFHF5KqNg4x2qSigCgul2KvvEYz7kkflVqWCGcASruCnI9iKlooAjlhjnQxyjcp7U2a3huE2TKGFTUUAVLextbU7oUw3qeTTbjT7W6cSSr83qDjP1q7RQBVgsra2cyQptJGD16VDNplnO/mOmCeTg4zWhRQBHFDFAgjhUKo7CkmhinQxzKGU9jUtFAGYukWKqVKls+p6fSrc1rBPGIpl3KOmev51YooAowada27iRQSw6FjnFWFt4kma4UfO4wT9KmooAh+zxef8AacfPt25z2qvPp1rcP5rAq3cqcZq9RQBWgtILaMxRLgHrnnP1qqNIsg+7acZztzxWnRQBQ/s63+zfZfm2Z3datSwpNEYX+6wwalooAZHGsUaxr0UAD8KSaJJ4mhk+6wwakooAjiiSGNYo+FUYFUpNLtZJGkG5C3XacA1o0UAVVs4EtzaoMIRg+pzU8UawxrEnRRgZp9FAFe5tYbtNky5x0PcfSoIdOt4pBN8zsvQsc4+lX6KAIEt40ne4XO5wAfwpLe2itVZYs4Ztxz6mrFFAFKCwhtpTLEWAOflz8vPtVt0WRSjjIIwRTqKAMr+yLbhdzlB/Bu4q9LbQTQ/Z3X5MYA9MelT0UAZ0WmQRSCRmeQr93ecgfSprmyhuiHfKuvRlODVuigClb2ENu/m5Z3xjc5ycVLDbRwNIyZzIdxz61YooAyzpUG4mJ3jBOSqnANTtp9u1r9kAKp1465q7RQBG8SyQmE5wy7ff0qD7FAbUWjgsg6Z61booAyl0mPcPNlkkVeiseKt3VnFdqA+QV+6w6irVFAHN3tmLZoJDI8jmQDLHPHsK17qyS6ZZNzI6dGXrVwgHqM4paAM2PTIo5kuGd3kXuxzmn3FhHPJ56M0cn95TjP1q/RQBStrKO2YylmkkYYLMcnFWJ4lniaF+jDFS0UAV0tkjtvsqk7dpXJ680sMAht1twSQoxmp6KAKEWnwx2hs2JZDzz1qv/ZKsnlyTSMgGApPA9PyrXooApSWMctotpISQoAB78dKqPpAlTZNPI+Pu5PStiigCpJaLLcRXBYgxZwPXNLd2qXaKjkjawbj2q1RQBTu7KO62sSUdejL1FRwaesc32iWRpXAwC3atCigBGGVIrnNOsfOtRJHK8ZYkNtPB5rpKaqIg2oAo9BxQBBbWkVrD5MYyD1J6n61T/ssIWFvM8SN/CDx+FatFAFB9Pia0+xqSq9c9T1zUktokskMhYgwnI96t0UAUrqyS5dZQxjkToy9aSCxEUxuJZGlkxgE9voKvUUAVbW1W0VkQkhmLc+9LBapBLLKpJMpBI9Ks0UAZ8WnrBcGeKRlVjkp2pj6YnmNJbyPDu6hTxWnRQBThsYIoWhI3h/vFuSTVT+yEx5fnSeV/czxWvRQBUlsrea3Fsy4UdMdR9KxdSsfJtDI8ryFSAu48CulpGVXG1wCPQ0AU57OO8hRXJUrgqw6iq39kozLJNK8jKQQSfTtWtRQBSurGK6YSElHXoy8Gm29gsMvnyO0smMAt2HtV+igCtDbCGWSUMzeYc4J4H0p1zAtzCYXJAbrjrU9FADY0WNFjTooAH4VUkske4a43EFkKEDuDV2igCva2y2kIgQkgZ5PvTbS1WzjMSEkFi3PvVqigCpbWaWpk2knzG3HNVTpSrkQTSRK3VQeK1aKAKos4FtjaAfIRj3570lpam0Qp5jOOMbuwHpVuigCtdWqXSqrkjawYY9qW6t1uoGgckBscj2qxRQBVltI5ZIpCSDCcjH9aiuLBJpfPjdopOhZe/wBav0UAUrWxjtWaTczyNwWY84qS1tltUZFJO5i3PvVmigCG4t4rmMxTDIP6VnjSlJUTSvIi9FY8VrUUAU7qyS6KPuKOnRl61DFpkcc63LSO8i55Y9a0qKAKE+npLL58btFIeCVPX60+1so7XcwJd26s3U1cooAy30uMuWhkeJW5ZVPBqf7BALQ2aDajd++fWrtFAGFqcKZtLc8rvC/hwKsDSozIrTSvKq/dVjkVqFVbBYA46ZpaAK0tqk08U5JBizgeuajurJbl0lDtG6dGX0q7RQA1F2IFyTgYyetUJ9OSSYzxSPE7cNtPWtGigChbafFaymZGYswwcnOfeo5dMRpWlhkeIv8AeCng1p0UAUbawhtGcxE/OADn2qpeWyWmlSQxEkDnnr1FbNIQCMEZFAGLHpaSQRgyyeWQCUzxWhPZRTwrByqoQRj2q2AAMCigCpdWUV1tZiVdejKcEVFBp8cMvnyO0sg4BY9PpWhRQBnz6fHLKZ43aKQ9Sp6/WpbeyhtlYJkl/vMxyTVuigDPGnQizNlubYTnPGeuatPAjwG3OQpXb74qUEHoaWgDNuYre3sPJlVnjXA46j3/AArDuEtWiEVtK9w7EBFJJC/hXXUxYokJZFVSepAxQARKUjVT1AAp9FFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAf/9fpKM84oooAKKKKACiiigAopCMjHSloAKKKKACiiigAooooAKKKKACiiigBCeQMdaWiigCjqNxJa2pmixuBHX3q2jbkVj1IBrM1okWJA7sKgm0xFtjOruZlXduz3HNAGrcvcRqDboJCTggnGB61XkuZV1GO1GNjIWPrnms67neaxtZieWdc/qDT7yIzatFHuKgx8kdcc8UAb3WiufmgGlzwzW7NsdtrgnPWmXdxFPevb3chjhjHQZ+Yn1xQB0dHSuesJo4777PayGSF1yAc8EfWmWFml7E7XDsVDkBc8D3oA6SkPAJrCtZ5bW1uVJL+QxC5ot9P8+2FzLI/muN2QemelAF/TbmS6tvNlxuyRxV+uZgYpocjLwd3bjuK13JGmFs8+T/7LQBformp3kGkW7qxDbhzn61Lf2jWsH2qKV/MUjJJzmgDoKKwLmzaO0N2ZXMygNnPH0ArYtZGlto5G6soJ/KgCeisXUbjNwln5nkoRuduhx6Cq6yxWt3F9lmMkch2spbOCe9AHRUVgXUivftDeSNFEFG3BwDnrk1ZtraUrJF5xeBh8jBvmH40AXbe6jud/l5+RtpyO9Wa57SLceZLLvfKORjPB9z6muhoAr3U32a3ecDO0Zx0qOxu1vYPNA2kHBHXFM1P/jwl+n9azdOP2W5WM8LcRqw/3sc0Aal9eLZQ+aRuJOAM4qe2m+0QJNjG4ZxWFfsbq4l/uW0Z/wC+iP8AP5VegE50uMW5AcqME9B70AatVrq6itEEk2cE445rn7ho7aPzbe8Z5VIyC2QfXipdZTfBHc7m+baNueOhOfrQBu3FxHbQmeTO0Y6e9I85Ft9ohQyZUMFHU5rH1K08uwDCR22dic5yR1+lPKNb6OzrIxLKrZJ6ZxwKANuNiyKzDaSASPT2p1Yt/LNFZwhGKq2A7jkgYpIIXWVJLK581f41ds8UAbdFFc9Ak97dXCPM6Ij9FPue9AGml07X8loQNqKGz37f41ernzDJJq0kcchQbBuI64wOlTQebaaiLTzGkjkQsN3JB/yKANqisRfP1KeXEjRwxnaNvBJHfNS2sk1vdmwmcyAruRj1x6GgDWornbOO6vkkMlw6qrkDB5z9fSrdlcSxwTi5bf8AZ2Iz3IFAGvRWHBDeXsIunuGjLcqq9B9aLme8i07dPlJQ4GR3HrxQBuUVUvpGjs5JEO0heDVC5uporK3KvjzNoaQjpkdaANqisiOO6jkjkt5/tEZPzhiOnqDWvQAUVm2Mssk9ysjEhHwo9BzTY5pTqNxEW+RFBA98CgDUorB077XexieWdgqt0HGcetLD9su7i4j84pGj4GBz34BoA3aKybCWdbiazncyGPBUn0qN0u5HZ7i4+z8/IoI6e9AG1RWZpdzLcQsJjuaNiu4d6dqk0sFoXhO1twGaANGisK6F/aQC7abcQRuXA24NWry7kURQ22BJP0J6AetAGnRWJLJdWDxyPN50bEKwIAIz3GKknmuLi9+x2z+WqDLt3+lAGvRWIHvbfUIreSXzI3yRxz07/SrVvLI9/cRs2VTbtHpkc0AaNFZwml/tNoSfkEW7HvnrVaKS51Bnkjl8mJSVUADJx3NAG1RWbp1zLL5kFwcyQtgkdx2pdTknht/PgbBRgSPUUAaNV2uVW5W22tlgTnHHFU7+5kEEYtjh5mAUj060ryzLqcUAY7DGSR6nnmgDTorMsZ5N89vcNuaJuCf7p6VXhvZFtp76Qlk3YjX2zxQBt0VhMuorbm7M43Ab9mBjHXFF1eztBay27BDK2Dnp+PtQBu0Vh3hvLK0Lmcu5cc4Ax14q2iX0Mbyu/muRwgAAB+tAGjRWBN9vghM73I8wfMY8DH0rZt5fPgSYjG5QaAEe4CTpAVYlweQOBj1qes24mlTUbeFWwjhsj1wKLaaR7+4iZiVTGAe1AGlRWYJpf7VMG75PLzj3qmkk15cSo1x5BRsKg4Jx3PrQBvk4GTUUM8VwnmQtuXpms+NL+S1aOd/LdTw4wdwqnpLNBZPdO5KKD8mO496AOhorEgjvryH7SZzGX5VQOB9auafdPcxMJRiSNirY6ZHegC/RWZq000FsrwNtYuBn86q3aX9pD9rM5YqRuXHy8ntQBu0Vl3l5IqxRW5Akn6E9h61Xla50945GmM0bNtcHHfuKANyisqaWe5vDZwP5axjczDqc9hT7b7ZDctBMTLGRlXI6exoA0qKrXsjRWksiHDBSQaSCR2sklY5Yxgk++KAC8uPslu0+3dtxx06nFOe6hihSaY7A+PzIzWNNLJNofmSncxxk/wDAqj1WOX7LDIH+T5Rtx3x1zQB0tRzSeTE0u0ttGcLyayb57q0s49spZy4G7GMg54qSdbq1tJpmmLOQD04Bz2oA04n82NZACNwzg9afWRPdzR2duIzmWcKAT7jk02WLUbVVljlacg/MhHb2oA2aKyrmeaa6FlbN5ZA3O3cD0FMilntb1bWaTzUlBKk9QRQBsUVhCWe8upY/P8gRnaqjGT71o2RuwjJdjJU4DD+IetAFyoLmUwQPMBkoM4qDULo2lsZF5YnC59TWbdW97HZNJLPuO35lI459PegDat5TPAkxGN4BxU1YPnSxWtiI22h2UN7ireqzSwWoeFtrbgM0AW5J/Lnjh2Md+fmA4GPWrFZlxPKmoW8KthHByPWtOgAorAjkmvp5QbgwFGwqDg8dz61oW5vlt3E4DSrnac/e9M0AX6KwJVvI4Wnkutsygts4x9MU+6vJzpsVzEdrsQDj8c0AblVri48gp8jPvbb8o6fWsy5iv7eE3QuCzLyy4+X8KluLuRktJITtWVwG/HtQBr0VlXlxM9yljbsIyRuZvQegqNZJ7O8jgll82OXgE9QRQBs0VhRG8u7m4iExSON8cde+AKnsJZ1uZrOdzJswVY9cUAa1RyypDG0shwqjJqSqt7btdWrwKcFhx+HNAFL+1Tt80W8hi/vY7euK0op4p0WSNgQwyKy4NREKrb3yNEwG3JHynHFSSNBpdkZIPmBPy855P9KANWisCVb2CH7V9p3SKMshxjHpiprm8lmW3htTtecZJ64HegC1f3jWaoyqG3tjmrzAkfL1rmNSt54Fi8yYyqWHDdQa6igBmwBcLwfWnjOOetZttNK99cxsTtTbgemaFmlOqNBu+QR5x70APtrx52nBUDyWIHvjNSWNwbu2WdgATngexrPsPv3v++f60/TxP/ZS+Rjec7c9OtAGxRXOTtNbRGYXm+VcZTIwfYCrN9c3HlWzwNsaVh+o70AbVFYF4l5YqtzHO0hLAFW6HPtRdx3lpb/avtDMwIyD93n2oA36Kyry5mPk28B2yT9/Qd6abe+tXSSGVplJw6t6eooA16KyZWnvLt7aKQxJEBuI6kmmQvPZ3iWcrmVJB8pPUYoA2aK5+NLi9uriLz2SNG42n/PFSOLmbUHtUmZEVATjr26e9AG5RWHGZrC+S2eQyRyjjd1BqOSc3txJG0/2eKI4HIBJ9aAOgorGsbhxLNaPJ5oQblfrxUGmx3N3GtxLO+EbgDvj1oA6CiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA//9DpKKKKACiiigAooooAKKKKACiiigBMfNn1paKKACiiigAooooAKKKKACiiigDL1eKSWz2xKWIYHA5qCe6u3gNqLdxIw2k/w89TmtuigDCu7SSOztreMFyjjOB9c0t79oj1GO4hiMgVOcfjnn1rcooAwpPP1G4iHlNHFGdzFxjNLPA1tetc+T58coGQACQfpW5RQBmWjGWYstsIUA6sMNn/AApNKikigcSAqTISMjHFalFAGLbWjvHdwuCokc4JH602C6uobcWrwOZVG1SB8p9Oa3KKAMC2tJn0mS3ZSrknAPHQ5oN1cPYm2FvJv2bDxx0xmt+kzyR6UAc7PbzNpUCBGLKwyMc961NUR5LGRIwWJxwOT1FX6KAKF4jtp7ooLMUAwBzU1mrJaRKwIIQZB+lWaKAMa/hdLmO9WPzVA2uuMnHrilhnhnmQW1rwD8zsoXH0962KKAMieeSKZ0vIjLCeUKrnH1qPTImW4mljRo4GxtDevrituigDD05zb3MtpIrBncspxxj1zWpBOZmkUoybGwCe/uKsUUAUtSVmsZVUEnHQfWqFxBIdPgnjH7yAKwGPYZFblFAGFFbyJpczsMyTAs3rzSTRTvo0aRg5AG5e5HpW9RQBy1xLbTWZis7Zgwxk7fu8+tXdSieXTYzGCdu0kY5xityigDHu3+3aY7QA9uo5OCM4qEzLcaQyRhsoiqeO4x0reooAyZJLmC1gKR749oEi4ycYqh+5uLuKTTo2Uq2XbGBjvXS0UAFYumIy3V2WHBf+praooAyIQf7ZmOOPLH9KJQf7ZhP/AEzP9a16KAMKKUaXNLFOG8p23IwGR7ipLbfeX324ArGi7Vz1NbNFAGRowIhlz/z1P9KjtovOF7F/fcgGtuigDCtL+O0g+y3KsskXGMZz9Kddi6u9NLtHtfIbb3wK26KAOfu9ShnsWjhDF2XBGPu+uasyTPb2UBMQki2gOOuBgdq18YooA5ndatdwtpYIYn58A42985rpqQAD7oxS0AYMNzHY3lxHdZXzG3KcZBFJZTC4v7iYAqGQYz6cVvEA9RnFLQBjaGMWR4x85/pT9OBFxdnH/LTr+da1FAGTbg/2ndEf3V/lWXbmyXzP7TBM+45Byc/SuqpNoJyRyKAMXRcBJlwV+f7p7CptZGbL/gS1q0EA9aAMzVv+Qc//AAH+Yqjfwhora4dS8aKA4HXBA5roSARg80e1AHNBdGZ0WBGkZj0Xdx+ZqxJILDU3mnBEcygBvQjFbKRohJVVGfQYpzKrDawBHoeaAMM3UV1qkBhOVUNyRwTjtS/aI7PU52uTsWRQVOOuPpV2S2c3sE0YASMMD7ZHHFXXjjkGJFDAeozQBi206XWqvJHnb5WATxnkVQhhsbdng1JCrg5VucEfhXVhQOQPakeNJOHUNj1GaAM3TRaYke0RlUnGTnDY9M1oSxrNG0T9GBB/GngAdBiloA5zTUlkuQkw4tAVH1J/wq7L/wAhiL/rkf61rYA5HekwM5xzQBgaqJLeYXEI/wBcpjP17VbubNv7L+yxDLKo49SOTWqQD1ooA5VP7F8kNIpDgcrls5qzdqiJZCJSq+YCFPUZNb3lR7/M2jd645/OnEA9RnFAGRrf/HmP98f1q3qBmWykMGd2O3XHerhAPBGaWgDk3/sv7GfKBeYrnuSD3J7cV0Gn/wDHlD/uCrIijUllUAnqQOtPAAGBxQBj3X/IWtR7N/I1F58VjqcxuPlWUAg9uKmWG7n1BbidAiRZC89c5rVZEcYdQ31GaAMO2nS51dpYs7fLwCRjPIqOSWymd01OMRSqeCM8j6iuhwM5xSMit94A49aAMnSfNNq4OSm4iPd6VT08pNYSWAOJTu4NdJ0pAqg5AGTQBiWupwW9ssNzlJIxgrg5OPSrGlxSKklxKCrTMWweuO1aRRCdxAJHenUAY+tf8eqf9dB/WptX/wCQfJ+H8xWkQD1oIBGDQBgahCGjtrkpviQDco9CBTF/sZnRIIzIzEDAzx9c10VNVET7oAz6UAYzuthqTzz5EcygBsZAI7Grdvem6uCsC5hUcucjJ9BV9lVhtYZB7GgAAYAwKAK94jyWkscfLFSBWVFqdqtiIiT5ipt245yBj6VvU0RoGLhQCepxzQBzrf8AIvj/AD/FU+pg/wBnQuBwpQn6Yrcwv3f0pSARg0AYOqTRXNnHJEdymUDPTsav6nxYS49P61dCIBtAAA7U4gEYNAGDcI4tLS6Rd3khSQPTAqxJqsbhUsgZZGPTB4+ta1NVEUkqAM+lAHP3sUUeoefeIWhdQMjPBHripbRdLa7UWaMzAE7hnA+ua3SARg01UVBhAAPagDBlmspZHj1OMRupwCM8j6irWks7RyYLGIN+7LdcVqMiPw4DfUZpwGBigDM1WF5rXdGMtGwYD1xVS71K3ubJ448l2XlcdPXP0repNqgkgDmgDnpwy6faTgZWIqzAelN1S/t7m3EcBLfMCTg4FdJgYxTFjjVdqqAPQDigDKuv+Qpa/Rv5VsUY70UAc7JPZys6anGI5FOAQDyPYinWv2r+zpxFu6nyyeu32rfKq3UA4paAOTzpn2MgIXnKnOc5BxyfTjrUk5/4kkBHPzD+tdPtXOcDJrP1K2kubdYoQMhgfTigCpeanBLbNDFuMrjbtwcjPXNJPCYILKMjlZFz9e9bm0Z3Y59aXr1oA57UYIlvVuLpS0LLtJGeD+FOt10prlFtYy5HO4ZwuPXNb5AIweRSBVXhQB9KAMnTgftV5/10/wAaS3/5DFx/uD+lbFFAFe3uo7nf5efkODkYpt41ykBe1ALjnBGcirVFAGO+q2EkJEoOccoV5z/KqQs7h9I2FTuV96qeuPSuj2KW3EDI796dQBzIk0XytwiJc/wc5zVm6T7LJbXscZEcY2svdQf/ANdbm1c7sDPrS0Ac1qd3DdrELclwrgk4OBXS0gAXgDFLQBh/aEstSnNzlVlClW6jgUWs63OqvKgO3y8AkdeRzW2QG4YZpaAMSwB33v8Avn+tV0Wf+wwIgc5OcdcZ5ro6KAOSnOmG022sZaTAycHK+57VdueYLDbz8yf0rfAA6CloAydZBNmABk7xxTtXB/s9x/u/zFalFAGHco8ItbxVLCIYYDrgjrVj+0hNIkVkpkJPzEggKK1KKAMd5PsF9JLMD5U4HzAZwRxg0xX/ALRv0mjB8mAHDEYyx9K26KAMfTgReXn++P61Xe5W21aWSQEqUAJHOOldBVCO2kXUJLo42OoA9e3+FAFFZDqN/FJEGEUPJJ4yaqvFbWt1KL6IsjtuR8evUcV09FAGPZfZWMj20BRQuNx/i9qXRQRZc/3jWvRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFAH/9HpKKKKACiiigAooooAKKMUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFQXFxHaxebLnaDjj3qm2r2SybCTj+9j5aANOisyTV7ON9mWYDqwGQPxq+ZohF55YbMZz2xQBJRWYmr2byeXkrk4DEYBq3cXUFrtMzY3nAoAsHA60Vg315Dd2MhizhGXkjAPParY1ey8zy9xx03Y+WgDToqhemLdCJJGjy4xt7n0NX+lABRWCurIb7bvPklcAbed386v8A7s6hjzG3hM7P4cetAF+is99Us492XyVO3AHOasW91DdJvhbIHX1FAFiiqM2pWcEnlO/zDrgE4+tJcywzWTSLMUQ4+de3NAF+jOOtQCWOG3Esj/KFHzHvWJqd/a3NmyRNlgwOCMfjQB0VFQefEjRws2HcfKPXFOknihZEkODIcL7mgCWiqst7awu0crhWUZIPpTbe/tbrIiblRkgjBxQBcorEj1aN74x7x5RACnBzuOK26ACiqs97a2zBZnCk9up/SpYZ4rhPMhYMvtQBLRVH+0rI7f3g+Y4HBp0l/aRbhJIAVOD160AXKKhguIbld8DBgKhm1Czgfy5ZAG9Bk/yoAuUVD58Pk/aNw8vGc+1RR31rLIsUbhmYZAGfrQBboqnLqFnA/lySAN3HJx+VWlZXUOhBB6EUAOoqKWeGEqJWC7jgZ7moE1Cykk8pJQW/z36UAXKKpf2jZeZ5Xmjd09vz6VbeRI1LyEKo7mgB1FVYL61uG2QyBm9On86kmuIbdd8zBR70ATUVDBcQXK7oHDD2pk15a27bZpAp9O9AFmimo6SKHjIYHuORVY31msnlGVQw9/60AW6KKRmVFLMQAOpNAC0VXiu7aZtkUisfQGnyzRQLvmYKPegCWioEubeTbskU7unPWnSzwwLumcKPegCWioVuIHjMyupQdTngVTtNQW5mliYqNrYTB+8OeaANKiiq8l3bQsElkVWPYmgCxRSAgjIORUAu7UkgSoSOvI7UAWKKarq6h1IKnuOlRpc28rbI5FY+gIJoAmopjyRxLvkYKPUnFNjmhlBaN1YDrg5oAlorKi1JJL17clNgHytnqeOK0ZJooRmVwgPqcUASUVHHLFMN0TBh6g5pslzbxNtlkVT6EgUATUUgYMAynIPcU15I4gDIwUE4GTjmgB9FQC5t2fyxIpb0yM1I0kaEB2CljgZPU0APopkkkcS7pGCj1JxSNNEjbHcBsZwT29aAJKKiFxAwUq6kMcDnqfanPJHGAZGC5OBk45oAfRTJJI4l3SsFHqTikjmimGYnDgehzQBJRTXdI1LuQqjqT0pQyld4IxjOe2KAFoqjcyNJCj206ICw+Y8g+1WxJGXMQYbhyRnmgB9FMMkauIywDN0GeTTJLm3hO2WRVJ7E0ATUUwyRhPNLDZjOc8Y+tRi5ty2wSKTjOM9vWgCeiq/2u2yqiRSX+7z17UslzbwnbLIqk9iaAJ6KarK6hkIIPQinUAFFFYVtfzSXx3/6mUlU+q0AbtFNd0jUvIwVR3PApizwu/lo6luuAeaAJcDOaKga6tkbY0qBvQkZqR5I4wDIwUE4GTjmgB9FNd0jXfIwVR3PApwIIyKACisTVLn95FbJL5YZsOQeQOPyrSgEUFuCJCyDnexz+tAFmioYp4J/9U6vj0OapQM51SdSx2hVwM8UAadFU7QyESF5Vl+bjb29ql+1W2/y/NTdnGMjOaAJ6KKyrmVo9RgXdhCrbucDgd6ANWioY7iCYkROrkdcHNRZf7ZjzV27f9X3+tAFuisWwuVRrlriTAEpA3H68DNa8ckcq74mDD1HNAD6KgkureFtksiqT2JqUyIE8wsAuM5zxigB1FV2vLVCFaVQTz1FT5AG4nj1oAWisi/vIJLOUW8oLjH3Tz1FXYJkWCHzGALqMZPU4oAtUUx5I4hukYKOmScUjzRRsFd1UkZwTjigCSiq8d1bTEiKRWI64NLHdW0r7IpFZvQGgCeiimLJGzFFYFl6gHkUAPoqNpoUJDOoKjJyegqjaaglzNLESo2thMH7w55oA0qKa7qil3IUDqTWfY6gt0zoxUEMQoB6j1oA0qKrNeWq/elXrjr3pkfmfbJMzBlwP3fdaALlFV5Ly1ifZJIqt6E025uo4Lczbl6Erk8E0AWqKoWt2Lu0MgZUfac4/h64Jqa1J+zqXkEnBy46GgCzRVVb6zYkLKvHXmpjNEoUs4Af7vPX6UASUUySSOJd0jBR6k4pXkSNS8jBVHc0AOoqCG6t7jIhcMR2HWp6ACiq811b25AmcKT0BoluYYoDPvG3HB7E0AWKKoafefbIAzlfM5yB254q/QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAf//S6SiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDH1v8A48v+BCn36qNKYY4Crj9Ks39ob2DyQ23kHOM064tvPtDbBsZAGfpQBW8tBpO0Djyc/jjNZUrM2mWkbfcdsMfbNb5gJtPs2f4NmfwxmoRYIbEWUhyAOo9c5zQA6+jiNlIjAbVQ49iBxWJcl5LSxMnJJ/PpWi2n3UyCG4uC0Y6gDBP1NWLqxFx5IU7ViYHHsO1AEWsAfYWHuv8AOpdQiiNhIpAAVePbHSpL22N3bmANtyQc/SqT6dcyoIJbgmIHpj5iPQmgCpKzNDp5buy/piujqjcWQmaAoQohYHGOw7VeoAxlA/ttv+uX+FKv/Ibb/rl/hU1xZTtdC7tpAjbdpBGeKlFoRfG83cFNuMUAUtJRPMuZMDd5hGfam2p8q7vdnAA3Ae+DV+ztDamUlt3mOW6dM0QWhiuZpywIlxxjpigCtpEaGyDkZaQksT35qK9torXTZ0hJwzA4J6cjpTxYXduWWymCxuc4YZ2/SpP7NAsXtFb5nOWY9znNAFS7Hm/Ybd/uNgn0OAOKl1tIxZA7RkMAD6VbubFbi3SHdtaPG1vQiqU2n313HsuZl+XkADgn3oAfMc6paj0Qn9DTtS/4+bP/AK6f4VPd2bzeXLC+yWLoex9qrfYb2aaKe6lUmNgdoHFADPLSTW23gHbGCM+vFPmVV1mEqANyHPv1q4toy37Xm4YZNuO/akktWe+iuwRhFII785/xoApRxxjWXXaMCMEDHQ8Vt1mS2lwL4XduyjcArg+ntWnQBi6SiTLLcyDc7uQc84FFuBb6tLBEMI6biB0BqRrO6t5XlsHULIclH6Z9RU9nZmBnmmbfLJ949voKAKeiRR/Z2k2jcXIz9MUadFE93dSMoLCQgE9uTV3T7V7OAxOQSWJ496LS1e3kmdiCJX3DHagCnZqsep3SJ8q4Bx2qK3kj+cWVqZUJO52IGfzrQjtGW7muGIKyqBjuKqRWeoWym3t5E8ongkfMM0AVLTP9lXS9AC2B6cVetVWDSxLEoDeWWz3zilgsJorOa1ZwTJnB+vrV23g8q1S3kwcLtPpQBhWTstqALQy78lmyPmrS0mOeK3aOZSuGO0H0qFLTULQGK0kQxnoH6itO2jkiiCzOZG6kmgDJ1oBvIU93xRrMEK2gZEAIYDIGOKuahaSXZi2EAI2Tn0p2o2sl3b+VGQDuB59qAKuoWtvHpzbEA2AYOOeo70tw9v8AY7c3QZ8hSFHVjirt7A9xavAmNzAYz061VnsZZIYDEwWWADGeh4H+FAGfO5aa3cWxgPmLhuBkHtgVcvoJheJdrF5yKuCvcfhSS2uo3EkckrRgRuGCjOOO+anuba5W4F3aMN2MMjdDQBDaGzkvDJEGhl24aMjGffFQCOS0nla4tzMkjZDAbiB9Kt29rcvd/bbvaGC7VVe31pi2+o2juLYrJG5yA5ORmgBbQWX2OVonYRNksDwV9qz2kgNo0dvaM0e04kI5+ucVpQ6ey2s0UzAvMSWI6AmoRb6p9n+x5RVAxv7kelAF3TSTYxE8/LVHV3zLBbsC0bHLKvU47Vo2MMlvapDLjcuRx060y9tGuQkkTbZYzlT2+hoAyLo+YY3tLWSOSNgQduBj8KtbFutXdZhuWFBtB6ZOP8amC6rKVWQpEoPJXkn86S6gmW7FzZsvm7cMjHqPWgCCe3hi1W3aIBd2SQOnAqv5qy6lK88TyiM7VCjcB7kVIDcPqsBuSu7B+ReQowf51amtbqC6a8ssNvHzIeM0AV7WPN8+yB0hlTDKy4GadpcEQurk7RmN8L7delX7Zb4yGW6KqpGAi9vfNVoILu2vZCqhopW3FieR1oA05XMcTuOqqT+QrnLSS3MBa4gklklyS23Ofoa6ZlDKVbkEYNY0cOo2IMNuqyxkkrk4K/WgDOEk0emPCQygyBVyMHaea07vTrSOxcIgBjUkN3yKkltpprForuQByd24cAegqncyal9keO4VUVVwXznd7Ae9AFe4lZdOtIRnbJ94L1IHam3TWxjU2cEkciEEHbj860RZvc6fBsbbJGAyn3p4bV5SEZEiGRluvHsKAItQikeWG5aMzRqPmQdcnviktFsJbrzLfMb7SGjIxkVauoLtZ1urRtxAwUY8GooILua8W7ulWPYpAUck5oAp21rANXlj2DaigqPQ8VNdmzW9LTBp5MACMDIWpXt7uHUGubdQ6ygBsnp0/wAKJYL23u5Lm0VZBKBkE4IxQBX08oNSkWJGiUpnYwxzkVGY0t5pnv4GlDsSHAyMf0q9bW92t811cBfnTB2np7UwR6lZsyQATITkbjyPbk0AWdNSBID9mkLxliQD29qra0AYIlPeQfyNWdPtJLZHaYgvI24gdBVXWwTBEFOD5gx+RoAL/T7ZLNniQK0YyCOvHrUNzIZo7CR+rOpP14qSePVbpfssioiHG5weo+lWb2zd4IhbffgIKg98UAR61/x6D/fWq97FHNq0EcoypTkeuM0tzFql6iq8aRqrA4zkn3+lW5bWV9SiuQPkRcE5780ARXcUcM9okShR5hOBRrH3IP8ArqKsahBNKI5bcAvE24A9DVC4i1K8MZkjVFRwcZ5+tAE2owubmKd4zNCgIKjqD64ptl9hkuzLakxMBgxkYz+FWLqG8W4F1aHdxgoTxTIILqa8F5cqse1SAoOSfrQBpTRiaJom6MCKwEuXXSngP+tVvKx9f/rV0dZD6ezaiLn/AJZcMR/tDgUAQ3sIt7O2gH8Mig/XvUt0Ps2ow3Q+7J+7b+lWdQgluEjWIZ2yBjzjgVJfW5ubZo0+91X6igCjCfNvri8IysI2L+HWs+zkgdHnuYJJpHJJYLkY6cVvWVuba2WJ+W6t9T1qgkF/YFo7VVliY5AJwVoApxB00+7iKssYOU3DBwa0LWCGPThIqjc0eSe/I9ae8F5LZSxzMGkfoBwB7VYihdbFYD94R7fxxigDO0W3hNqJigL7jyeTx6VEGskllCRPcuSdzYzj2rS063ktrRYZfvZOce9UYYNSst0FuqOjEkMT0z60AP0U/upVGQBIcA9q2qybG2u7WKdW2l2JKnPBPvWhb+f5K/aceZ3x0oAr6lcfZ7N37sNo+prClns1sIo4ZAZYSGHB5PftW3dW0lzcQ5A8pCWb3PbirpijIKlRg+1AGXqMqzaU0q9GCn9RTDFFZaabiJAJPLHzd8nHemixuhp0lnwTu+TntkGtTyA9qLeTugU/lQBRtNPtXslDoCZFBLd8n3qrewNb2UEMj79soGfbmpETVoI/siKjADAkz0FTTafI1isCuWkQhgSepoAfrH/IPk+q/wAxWhF/ql6dB06ViXMWq3sBikREAxxnlq3EBCAHsKAMW+toGvrfKA+YzbvfAFM1BkW6gtWQmFV3FEHX049K0Lm3klureVANsZJY/Wm3tpLJJHdWxAlj9ehHpQBmSOhu4ZbSGSJgwDfLgFT9KvwHOq3GOyrToW1OWVTMqwop5A5Lfzp8FvLHfzXDAbHAx+FAFHTkeS0uUjO1mdgD74qoiWkVv9nvoGibp5mM8+ua07WxlS2mhkOwyOSCp6elQlNWMJs2RGBG3zCe1AGvbhVgRUbeAow3qKyb+FZ9Rt43GVIbI+latvF5ECQ5ztAGao3ltdSXUdxbEDywevr6fjQBBfxR2s9vcQKEO8KccZBp/wDzG/8AtlQsF7d3CSXiqiRHIAOcmrH2aX+0vtXGzy9vvmgChptvDLcXMkihiJCBnnHJpYcWWoTwxDCGPeB2BFOjt9RtJJpIVRxI5O0nn61Ys7SYPJc3mDJKMEDoB6UAZlk8JiaW5t5JnkJJbbuH0FSRLKmm3MbKyoM7N4wcGrEVvqNiDFbBZYycruOCKsvb3ctlJDM4eR+nYD2oArpYW39m/Mg3GPcW75xnrVSRpG0u2h3YErBSfbNbYhYWfkfxeXt/HGKpHT3k05LZyFkTkH0NAEep2drHYMyRhSmMEdeoqO5A26fj+8v9KdNFqt3A1vIqKPXP3sfyqzdWk0trCIiBLDtIz0yBQAms5+x/8DWq97Ek2qwRyjKlTn0OMmm3MGqXsYWREQKwO0Hk+9XZbWV9RiuV+4ikHn60AUr+zg+124RQockMBxkDFO1KGKBreSBAjCQD5eOKvXVvLLc28qfdjJLc+tN1C2luPK8oA7HDH6UAaNY9l/yEbv6rWxWNLBe2129zZqsiygblJxgigB6Kr6pMjgEGMAg1X0y3h+1XDbBmOTC+3XpVq0t7tbuS5udvzqB8vb2plvBd217IVVWilbcWzyOtAGq6JIpRwGU9QaxNIhi3TPtG5ZCAccgVu1lWlvdWtw6YUwuxbdnnntQBW0q3hkeeWRQzCQgZ5xU1t/yF7n/dX+Qqxp9tJbCUSY+eQsMelJFayLfTzuPlkAAIPPTmgDMjRbPzFvrcyBmJ8wDdwf5VYEFsdLfym81AGK7uqmnJHqlqGhi2ypklWY8j61Pb2DRWT20jAtJkkjpk0AQWUcaaSzqAGaNskd+vWqUrMujQRqcCRsE+xJrRtLe8S0e0mCgBSqkHrnNH9nF9OW0c4deQR2NADNQs7aPT22IAUAwe/X1qvc/6iw/3k/kKS8GpmzdbjYEUckdW5q1JavdafB5RxIgVlz9KAF1v/jy/4GKrahKWvooXjaSNF3FF5yafc22p30eyTy0AIOAev86t3lnLLJHc2zBZY+OehFAGcxZ7yCa3tpItrYY7cAg/SujrOiGpSSq05SNF6qvJatGgDlrOZXMs81u87SMeQuQB6VYtYn+y3UckTKgy0YcdMg9M+lWRa3lnK7We145Dna3GD7VbghuDC6Xjh2fOcdAD2FAFbRkQWSuAAzZye5wTWtWZp0F1aoYJtuxc7SOpya06ACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigD/0+kooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACimqyuNyEEeo5p1ABRRRQAUUUUAFFQw3ENxu8o52nB4IwfxpZ54raPzJm2r0oAloqD7TD5iRbvmcZUeoqegAooooAKKKKACiiigAooooAKKKg+0RfaPs2fn27vwoAnoqJJ4pWZI2DFDhgO1S0AFFFFABRRRQAUUZA60UAFFFFABRRRQAUUUUAFFFFABRRTHkSMAyMFycDPHNAD6qXFlBcsJHyrgYDKcGrdFAFO2sYLZjImWdurMcmrlFFABRRRQAUUUUARzRRzxmKUZVuorP/smEsDI7uo6ITxWpRQAAADA6CiiigAoopkkiRIZJDhR1NAD6KieeJFVnYAOQF9yelS0AFFFFABVa5tY7pVWQkBWDDHqKs0UAFFIzKo3MQAO5qL7Rb/89E/MUATUUisrjchBHqKWgAooooAKKKKACimhlLFARkdR3od1jQu5wFGSaAHUU1HWVBIhyrDINDMqKXcgAdSaAHUVC9xDGELsAHOFPrmpqACiiigAooooAKKKhS4hklaBGy6dR6UATUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAGO9FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQBFNCk8TQyfdbrT40WNFjXooAH4U6igAopiSRyrujYMOmQc0+gAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA//U6SiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigCtd3K2kBmYZxwB6k1mPc6pbp9qnVDH3UdQDUmtRs9oGUZCMCcenSqLW9g0PmPduVI6Fsn8qANS6vXQRRWqhpJvu56AetVJrvUrTYs6o29gNw/l2pkojtLu0lJPlBNoY/zP50urXEMghjjcMfMB4OeKAL11dyidbS1UGVhklugFMgurlLkWd6F3MuVZehrOvIkOqnz5DEsijawOOnGKsQWtol5Hi4aSRckAnNAErXV7cXEkNkEAiOGL9zTjcXc9nJhAkikq27OMd8VA6WNzcSMrtbzIcE525x3qWyuJbi1nWRt+zcoYdxigCPRWm+zZIXyhnGM7ic1J5+qygyxRqiDOFfO44pmlyrHppKEM6hm296qQql1bm7urplPOQDgD2xQBqpqKNYG9K9Oq+/Sqxu9SSEXbxxmMgHaM7sGobB4o9JZplLpk7gPQ0yVEtbf7VY3JCjGEJyD7UAdCjiRFcZAYZ5p1Vo7lDDFJMQjSAcE45ParNAGLH/omrPH0W4XcPqP8mlv83N7BZDlQd7fQU/VoyIku0+9CwP4UzTc3M01+wxvO1foKALEswXUIYdincpO49R16U6zu3neWKYBXibGB6etVrj/kL2/+639ag1BzY3f2pOksZX/gQ6UAXYb/AH+fK4AihOAe5x1qub6/8r7WsK+T1wT8231pktq0WimJRlsBj65yCfyqOGBZbYSC8YJt+YEjj1FAFy61LyoIriFdyyHGDRLd3lvayXE8aAjG0A56nnNZ90kUNnarE+9BJkN0960tYH+gSH6fzFACx3Vzsa4miCxbcqByx9OKrm+1ARfajAvl43YzzirU0722necgyyouPxxWXLEzWJuZrpiWXO0HAOe2KAOghlWeJZl6MM1Wu7p4CsUKGSR/ujt+Jo07/jxh/wB2q1/PN9oitIn8oSZJf+goAVL25juEgvYwnmcKVORmmDJ1o5HSKqU0IhvbVfPaU7+Qxzjp/Or3TWvrF/WgCSznjaS5bYqBHOSO+M8moUv72fM1tAGiB4ycE49KhgRmTUEXqWbp+NW9Lmh+woAwGwEHPagBsGoyS2c1yUAaMkY+lXYpzJaC4YAEpuxWLbHdpl0V5yzfyrQtpoV0xW3AAR88+1AD4r9TYi9mG3rkD1ziqzX97EguJbcCH6/MAe9Zrxu2hxleitk/TJFXGtpZbYu17+7YdwMY/OgBmrTTOItiZiLKytnqSOmK3YGleMNMmxu4zn9axNQRYrG2RW3KHXDeowea6CgCnd3i2oVVUvI5wqjvVaO+nSZYb6Ly/M+6QcjPoaqakr/2hARJ5QZcBuuDSyWMxeM3N2DhgVBGMn25oAu3F7Ks/wBltI/McDLZOABSW9/JLdfZZYvLYLk5OfyqCzOzVLlHPzNgj3FCsG1ptpBxFigCd7+V5Wis4vN2HDHOBn0p0d800DtHETIh2smcEfjWVp0V2yyJFOImVzuUqCc+vNaVlamGaaR5hK7YDYGMH3oAq6JLM0bKykruJ3k98DjHWtuWRYY2lfhVGTWRofFs4/6aH+QrTuTCLd/tH+rx830/CgDNOp3Aj+0m2Pk+ueceuKlvJ7Z4YXdPNWRxt5xjNVDFc2tt51rOJYAudrjt6ZpL2VZ7W0lVdoaRePSgBdTnuFuYUWNgA/GG+/04rbiZ3jDuuwnqvXFZWqDM9oPWT/CtmgChdXphlW3hjMsrDOBxgepNMt79pLj7LcRmKTGRzkH8aiuZ7mW9FlbMIztyXIyfwqmsU0WrQLPL5rbSemMcGgC+2oubiS2hhZ3T0PH4+lRpqrMxgMDecDgJn+tNsj/xNLofSnJ/yG3/AOuX+FAE9vftLcG1niMUgGeuQaJb8ic29tEZnX72DgD8aqTf8hyH/c/o1QWKXRnuFhlWNvMJYMuT9aANGPUPNhdkiYyxkBo+/Jqlo1xO4aN1ZlJJ3k5A9qt2ttLHeSTyyq7MoBAGD7ZqDQ/9RL/vn+VAGldzSQwlo4zITxgdves3RriWSHy5EYgZO8ng89K2JP8AVt9DWLYB20d1T7xD4oAnOpsxY20DSonVhwPw9abe3EdzpTzR8g447jmq2npftaL9mlQIM8Ecg+9JLbNbaXOGdX3Nn5enUUAT6h/x62uOu9MflWi10Fu1tNudyls+lZuo4+x22Rn50/lUsxxrEOe8Z/rQBcmuhDPFBtyZSe/TFQzX5Sc20ETSuoy2OAKhviv260BIzub+lMeES3kktjNsmXAdSODQBdtL1boshUxyJ95Wq7WXY3ErzywXCr5seMsvetTOelAGfqv/AB4S/QfzFQ29jp7QRsyKSVGc/SptU/48JfoP5ioLfS7F4I3ePJKgnk9SPrQBYlmisBDDEnyyNtGDwM96kvboWcPnFd3IGOnWs/U1WJrRRwqyAfQDFP1v/jzH++KANisuTUwtw9skTO64wB3/AMK1B0rDtf8AkM3H+7/hQBINXGTE0LiYHATrn8ant78y3BtpojE+MgHnNQAD+2z/ANcqS6/5C9t/un+tAE8TQ/2lMipiQIMtnqOO1T35xZy5/uGqUH/IZn/3B/Srt9j7HNn+4aAMy1v5ktEMduzpGoBbOOR6DvV2W5t59Pa4K74yOVPHfpT7Bk+wRNkYCDP4dayLYY0e4I+6S2PpxQBNeyRRwWcgXaoZWCjnAxVltSki2tcQNHGxxuJ6fUVTuMCzsQem5OT9Kv6uUFg+7vjH1zQBPd3kdqq5Bdn4VR1NQxX7+etvcxGJn+6c5BrNmWYXlp84Q+WAGYZGcc1bms7qSSJri4X5XBX5cHPoKAJpNRKXTWkcTO64xg9c/wAqfbX/AJ07W0sZikUZwTnIqvb/APIYuP8AcH9KH/5Daf8AXL/GgCVtRZp2gtYjKU+8QcCqWmyGXUriQqVJHIPUcip9GwEmRv8AWCQ7vWmWX/IWufp/hQBo2V2LyIyhduGK4znpUC6iGgmn2f6liuM9ah0U4tnB6iQ5/SqERB0+9I5Bc/0oA0P7UlMXnpbuYwMls4+v1HvSjU2lQyW0DSIOpyBTrb/kED/rmf5GjTAP7NTtw38zQBdtrhLqFZo84PrUV7eCyjWVl3Att4qlof8Ax5n/AHz/ACFP1cfu4Tx/rV60AD6o8W15oGSNjgMSP1FXLq7jtIw7ZYscKo6k1W1j/kHv9R/MVRvVk+2WpVgo24ViMjP+cUAX49QbzkhuYWiMn3STkH2p1xf+VOLaGMyyEZIHGBVW4tLuXZ9onQbXBHy45otSRq1yrkZIGPpxQBPDqJkuhaSRNG5BJyfT+dWILsTzzQhceUQM565qjKR/bMIHaM/1o08j7feDvuH9aALyXYa8ez28ou7Ofp/jVZtRZpHS1haYJwWBwM+1QIc6vcBOT5X68VW0yO9Nv/o8qKAx3AjJBoA27S6jvIvNjyOcEHqDUk88dtE00pwq1S0+3aAylpFcu2Tt7HvVfXATbIecBxn8jQBL/abJseeBo43OAxOfzHap7u+FqUjRDJI/3VFU7m2u57crJcIY2xztwPbnNMwYtUiEhDEQ4Xtk/wD16AJzqUiTJBNAyO7AdcjB75qxc3whlEESGWU87R2HqTVPVGH2i0Xv5gOPxFQhZzqs6xyCNiBjIzkcdKANG2vfOla3ljMUijODzkexqI6hI8rx2sJlEZwxyBz7U1LSUXyTzTqzqpG0Lgkfn71DFAXkkn0yfGWO5WHG6gCc3/n2bSwRszDKsvQrx1qHRp5XgKyKdoyd5Oc+1S2twZ7acOiq6blbb0Jx1qPSXEeml8Z2ljj6UAPGpySK0kFuzxr/ABZx09qtpfQPafbOQgHI7/Ss6Fr67g+0rOsKc4UAHAHqajsfI/shhcnEZYgkfXjpQBaOqSKgmkt3WI/xZ7djitZWV1DqcgjINYbreWVt5iSLPABnaw529ua2YmDxI6jAYAgelAFW5vRBIsEaGSVuQo449zTYL/zJ/ss8ZikxkAnII+tVosLrUu/gsg25/Cr8j2v2mON8edgleOcfWgCu9+5maC1iMpT7xzgA/WprW8S5DAqUdPvK3UVS0YqIpYzxIJDuB60keH1iUx9BHhvTPFADotVknUtBbs+3ryMfh61ctr2K4tjc/dC53A9sVW0YAWf/AANqzo1J0+9Cdd5/IUAXl1SV1M6W7GEfxZ5+uKlGpKbE3uw4Bxtz7461JaPH/Z8bAjAj5/Ac1jL/AMgF8f3v/ZhQB0M03k27T4ztXOKhe9jjtFu5AQGAIXvk9qivGT+y2JIAMYx/Ssu8VvsdkQ21RtyeuCQMGgDRGpSRsn2qBokc4DZzj6+latYlxZ3UsJS5ulKHHJUDntzmtlFKoqk5IAGaAM+e/dLj7LbRmWQDJ5wBRBqDS3X2WSIxsBk5NVrEhNSukcjcxBH0p2QdbAB6RYNAF62uxcvKgXb5TbevWkjuxLdS2u3HlgHOeuap6ZxcXanr5mcfnTbRg2q3RU5GB0/CgCWyubZLJ50TykUnIzmozqdwsYuJLYiI45zzg98VBp5gGlyfaf8AVliD+OPSlZLqzt/OhmWaAD7rjt9aANO5vYreBZ/v78bQO+apSalcW0Ye4tioPTDZH4+lQ3kqu1jcEbYy2T6DOMVY1plFiRn7zDFAF17nZcRQbc+aCc+mPai4uRbyRIRnzW25z0qjcYW/s2JGCGAP4UuospurRCRnzM4oAsXN60cotrePzZSM4zgAe5pLW9aaVraeMxSqM4zkEe1Znlztqs6xS+SxAIyM5GKtw2kiXqS3FwJHVSAuADigDYooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooA//9XpKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAAgEYNU1sLJW3iJc/SrlFAFC/wDM8tQIRMmfmXv7YrLW2F1PGsFuYYlbcxYYJx2ro6ji+5+JoASWCKddsyhh702G1t7ckwoFJ6kVPRQBVls7ad98sascde9TxxxxII4lCqOwp9FAFeO1t4ZDLGgVm6kVH/Z9l5nmeUu7r7fl0q5RQBFFBDChjiUKp5IFVxptirhxEuR+X5VdooAikgimKmVQ205GexqWiigBrosilHGVIwRSRxRwoI4htUdAKfRQBEYYmlWZlBdRgH0omginULKu4A5H1FS0UAFUG0uxd95jGfbIH5VfooAqGCCeNPNUFUbK9sY4FTzQxzxmKUZU9RUa/wCoX8P51YoAZ5abPKIyuMYPpVFdKsVYt5fXtk4/CtGigCOKJIYxFGMKvQVHcWsF0u2dd2OnqKsUUAUI9Mso9pWPlTkHJzmrXkRed9ox8+NufapaKAIYoIoWdoxguct7mqr6XZPL5rR8k5IzwfwrQooAxtHUeTMpHy+YRj2qcaRYB9/l/hk4pmkf6iT/AK6tWrQBDHbwxQ/Z1X5MYweetUxpNiH3bO+cZOPyrSooAgntobiLyZVyvbtj6U6CCO3jEUedo9eetS0UAQz28NymyZQwqtBptpbuJEXLDpk5xV+igDEv2s/tAF7GygD5ZBnn24qPTYke7a5gQpCq7Vz1Y+tGv/6iP/e/pVzSP+PFPxoAll0+2mk80gq56lTjNTW9rDaoUhXGep7mrFFAFKKwt4ZjPGCCcnGeOfarjKrqUcZB4INLRQBl/wBkWmcfPtznbu4q3LaQTKiMMCMgqBxjFWaKAK9zaxXaBJc8HII4INSRRLDGI1JIHcnJqSigCnc2MF0wd8h14DKcGmR6bbRSLMobevck5P1q/RQBXjtoopnnQHdJ15pRbRC4N0M7yu0+mKnooArtawtcLdEHeowDn/PrUFxp0Fw/m5ZHP8SnBq/RQBVtbOG0B8vJZurHkmootPiguDcRswzklc/Lk1fooAKoW2nxWsrSRM2G/hzwM1fooAy5NJgdy8bPFu5IU4Bqx9htxbG0UFUbrjrVyigCrNaRTxpE+cRkEY9qbdWUV3gvlWXoynBFXKKAM2LSreORJiWZ0Ocsc5p9xp0M8nnKzRyHqyHGav0UAVLWyhtQ2zJZvvMTkmn21tHaoUizgknk561YooAinhS4iaGTO1uuKoDSYQMCWUAf7X/1q1KKAKJ0+Brf7NIWdc5yTk5+tV/7HgZdsskj46Enp9K1qKACqsdpFHcvdKTvcYPp2/wq1RQBW+yx/avteTv27fbFD2sUlwl02d8YwPSrNFAFdbaNLl7oZ3uAD6cVLLGssbRNnDDBx70+igDKOj22Aqs6r3UHg/WrxtoTb/ZQMR4xgVPRQBTlsYJoo4ZMlY8YHrjjmoF0q2Dh2LuF6KxyBWnRQBXubWG7TZMuQOnqKrw6bBDIJSWkZehc5xWhRQBXS2iS4e5Gd7gA+nFBtojci6Od4XaPTFWKKAM6fTYJpTMC0bnqVOM1Nb2NvauZIQQSMHmrdFAGbJpVs8plBZdxywU4BqRNPt44HtkyEk681eooAhS3jSD7MudmNvvg0QQR28IgTO0evvU1FAFa1tY7SMxRZwTnmluLaO5CiTPyMGGPUVYooAhuLdLmIwyZ2nHT2ps9rDcxCKVcgdPUVYooAzotMt45BIzPIV5G85AqS6sIbpg7ZVx0ZTg1dooAwFt0ttWhRCTlCSScknmr9xp0NxL525o3IwSpxmq83/IZg/65n+tbFAFK3sLe1kMsQO4jByc1FNpdvI5kQtEzHJ2HGa0qKAK9taw2qeXCMA8knqT71LJGkqGOQblPUGn0UAZa6RahhuLso6ITwKbqZtR5a3SMF5xIv8JrWrE13/j0X/eFAFGKO3uLyFbQtIEO53bPboK3rmyguiHkBDjoynBFYOgf66X/AHR/OupoApW1hBbN5gy7njcxyaZJpttJKZAWRm5Ow4zWhTP+Wn4UARW9tDbRmOIYBOTnnNQ2+nwWrFoy2CCNpOV59qvUUAZg0m1DcFwp/g3fLVmKygiga3AzG3Y89atUUAZX9kW2cFnKf3N3FaiqqKFUYA4AFLRQBVuLOC6IaQEMvRgcEU23sYLZzIuWcjG5jk4q5RQBQn063nkM3zI56lDjNT29rBaqVhXGep7mrFFAENvbx20flRZ25J596jjt47WOTYCwYliDzkntVqg9KAOUL6UIyw8wMefKycbvStiwtduniC4H38kj0zXHv/x8N/vH+dehigDKGj2mNrF2XspbgfSrrWsLW4tWXKAYx9KsUUAZi6TaqQW3OFOQrHIH4Vp0UUAU7mxgumEj5Vx0ZTg1mQ28dtq4jizjy8nJySa36xz/AMhsf9cqALE2m280xnJZWPXacZqS3sbe1YtCCCwweauUUAVorOCGE26rlGySDz1qr/ZFn0O4qOdu44rTooAhlt4ZovIkXKenpWJqOn29vZtIm4lcAZOcDPauhrM1j/jwf6r/ADoAsTWkF1GizD7vQg8io00y0SRZQCXU5BJJNXh0FLQBVuLK3uiDKvK9CODSQWVvbuZIwSzdWJyf1q3RQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAf/9k=",
      "type": "IMAGE_JPEG"
    }
  },
  "inspectConfig": {
    "infoTypes": [
      {
        "name": "US_SOCIAL_SECURITY_NUMBER"
      },
      {
        "name": "PHONE_NUMBER"
      },
      {
        "name": "EMAIL_ADDRESS"
      }
    ]
  }
}

Cloud DLP returns the following:

{
  "result": {
    "findings": [
      {
        "infoType": {
          "name": "US_SOCIAL_SECURITY_NUMBER"
        },
        "likelihood": "VERY_LIKELY",
        "location": {
          "contentLocations": [
            {
              "imageLocation": {
                "boundingBoxes": [
                  {
                    "top": 98,
                    "left": 986,
                    "width": 102,
                    "height": 117
                  },
                  {
                    "top": 98,
                    "left": 1092,
                    "width": 29,
                    "height": 114
                  },
                  {
                    "top": 95,
                    "left": 1111,
                    "width": 82,
                    "height": 115
                  },
                  {
                    "top": 95,
                    "left": 1197,
                    "width": 29,
                    "height": 114
                  },
                  {
                    "top": 90,
                    "left": 1203,
                    "width": 185,
                    "height": 118
                  }
                ]
              }
            }
          ]
        },
        "createTime": "2019-11-01T22:58:56.985Z"
      },
      {
        "infoType": {
          "name": "EMAIL_ADDRESS"
        },
        "likelihood": "LIKELY",
        "location": {
          "contentLocations": [
            {
              "imageLocation": {
                "boundingBoxes": [
                  {
                    "top": 340,
                    "left": 334,
                    "width": 57,
                    "height": 58
                  },
                  {
                    "top": 340,
                    "left": 384,
                    "width": 12,
                    "height": 58
                  },
                  {
                    "top": 340,
                    "left": 387,
                    "width": 79,
                    "height": 59
                  },
                  {
                    "top": 341,
                    "left": 467,
                    "width": 12,
                    "height": 58
                  },
                  {
                    "top": 340,
                    "left": 476,
                    "width": 119,
                    "height": 61
                  },
                  {
                    "top": 341,
                    "left": 589,
                    "width": 12,
                    "height": 58
                  },
                  {
                    "top": 342,
                    "left": 592,
                    "width": 45,
                    "height": 58
                  }
                ]
              }
            }
          ]
        },
        "createTime": "2019-11-01T22:58:56.984Z"
      },
      {
        "infoType": {
          "name": "PHONE_NUMBER"
        },
        "likelihood": "POSSIBLE",
        "location": {
          "contentLocations": [
            {
              "imageLocation": {
                "boundingBoxes": [
                  {
                    "top": 394,
                    "left": 335,
                    "width": 50,
                    "height": 77
                  },
                  {
                    "top": 394,
                    "left": 380,
                    "width": 17,
                    "height": 77
                  },
                  {
                    "top": 394,
                    "left": 387,
                    "width": 51,
                    "height": 77
                  },
                  {
                    "top": 394,
                    "left": 433,
                    "width": 17,
                    "height": 77
                  },
                  {
                    "top": 394,
                    "left": 436,
                    "width": 77,
                    "height": 77
                  }
                ]
              }
            }
          ]
        },
        "createTime": "2019-11-01T22:58:56.985Z"
      }
    ]
  }
}

As you can see from the output, Cloud DLP has found a US Social Security number, an email address, and a telephone number.

See the JSON quickstart for more information about using the Cloud DLP API with JSON.

Code examples

Following is sample code in several languages that demonstrates how to use Cloud DLP to inspect an image for sensitive data.

Java

import com.google.cloud.dlp.v2.DlpServiceClient;
import com.google.privacy.dlp.v2.ByteContentItem;
import com.google.privacy.dlp.v2.ByteContentItem.BytesType;
import com.google.privacy.dlp.v2.ContentItem;
import com.google.privacy.dlp.v2.Finding;
import com.google.privacy.dlp.v2.InfoType;
import com.google.privacy.dlp.v2.InspectConfig;
import com.google.privacy.dlp.v2.InspectContentRequest;
import com.google.privacy.dlp.v2.InspectContentResponse;
import com.google.privacy.dlp.v2.ProjectName;
import com.google.protobuf.ByteString;
import java.io.FileInputStream;
import java.util.ArrayList;
import java.util.List;

public class InspectTextFile {

  public static void inspectTextFile() {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "my-project-id";
    String filePath = "path/to/image.png";
    inspectTextFile(projectId, filePath);
  }

  // Inspects the specified text file.
  public static void inspectTextFile(String projectId, String filePath) {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (DlpServiceClient dlp = DlpServiceClient.create()) {
      // Specify the project used for request.
      ProjectName project = ProjectName.of(projectId);

      // Specify the type and content to be inspected.
      ByteString fileBytes = ByteString.readFrom(new FileInputStream(filePath));
      ByteContentItem byteItem =
          ByteContentItem.newBuilder().setType(BytesType.TEXT_UTF8).setData(fileBytes).build();
      ContentItem item = ContentItem.newBuilder().setByteItem(byteItem).build();

      // Specify the type of info the inspection will look for.
      List<InfoType> infoTypes = new ArrayList<>();
      // See https://cloud.google.com/dlp/docs/infotypes-reference for complete list of info types
      for (String typeName : new String[] {"PHONE_NUMBER", "EMAIL_ADDRESS", "CREDIT_CARD_NUMBER"}) {
        infoTypes.add(InfoType.newBuilder().setName(typeName).build());
      }

      // Construct the configuration for the Inspect request.
      InspectConfig config =
          InspectConfig.newBuilder().addAllInfoTypes(infoTypes).setIncludeQuote(true).build();

      // Construct the Inspect request to be sent by the client.
      InspectContentRequest request =
          InspectContentRequest.newBuilder()
              .setParent(project.toString())
              .setItem(item)
              .setInspectConfig(config)
              .build();

      // Use the client to send the API request.
      InspectContentResponse response = dlp.inspectContent(request);

      // Parse the response and process results
      System.out.println("Findings: " + response.getResult().getFindingsCount());
      for (Finding f : response.getResult().getFindingsList()) {
        System.out.println("\tQuote: " + f.getQuote());
        System.out.println("\tInfo type: " + f.getInfoType().getName());
        System.out.println("\tLikelihood: " + f.getLikelihood());
      }
    } catch (Exception e) {
      System.out.println("Error during inspectFile: \n" + e.toString());
    }
  }
}

Node.js

// Imports the Google Cloud Data Loss Prevention library
const DLP = require('@google-cloud/dlp');

// Import other required libraries
const fs = require('fs');
const mime = require('mime');

// Instantiates a client
const dlp = new DLP.DlpServiceClient();

// The project ID to run the API call under
// const callingProjectId = process.env.GCLOUD_PROJECT;

// The path to a local file to inspect. Can be a text, JPG, or PNG file.
// const filepath = 'path/to/image.png';

// The minimum likelihood required before returning a match
// const minLikelihood = 'LIKELIHOOD_UNSPECIFIED';

// The maximum number of findings to report per request (0 = server maximum)
// const maxFindings = 0;

// The infoTypes of information to match
// const infoTypes = [{ name: 'PHONE_NUMBER' }, { name: 'EMAIL_ADDRESS' }, { name: 'CREDIT_CARD_NUMBER' }];

// The customInfoTypes of information to match
// const customInfoTypes = [{ name: 'DICT_TYPE', dictionary: { wordList: { words: ['foo', 'bar', 'baz']}}},
//   { name: 'REGEX_TYPE', regex: '\\(\\d{3}\\) \\d{3}-\\d{4}'}];

// Whether to include the matching string
// const includeQuote = true;

// Construct file data to inspect
const fileTypeConstant =
  ['image/jpeg', 'image/bmp', 'image/png', 'image/svg'].indexOf(
    mime.getType(filepath)
  ) + 1;
const fileBytes = Buffer.from(fs.readFileSync(filepath)).toString('base64');
const item = {
  byteItem: {
    type: fileTypeConstant,
    data: fileBytes,
  },
};

// Construct request
const request = {
  parent: dlp.projectPath(callingProjectId),
  inspectConfig: {
    infoTypes: infoTypes,
    customInfoTypes: customInfoTypes,
    minLikelihood: minLikelihood,
    includeQuote: includeQuote,
    limits: {
      maxFindingsPerRequest: maxFindings,
    },
  },
  item: item,
};

// Run request
try {
  const [response] = await dlp.inspectContent(request);
  const findings = response.result.findings;
  if (findings.length > 0) {
    console.log(`Findings:`);
    findings.forEach(finding => {
      if (includeQuote) {
        console.log(`\tQuote: ${finding.quote}`);
      }
      console.log(`\tInfo type: ${finding.infoType.name}`);
      console.log(`\tLikelihood: ${finding.likelihood}`);
    });
  } else {
    console.log(`No findings.`);
  }
} catch (err) {
  console.log(`Error in inspectFile: ${err.message || err}`);
}

Python



def inspect_file(
    project,
    filename,
    info_types,
    min_likelihood=None,
    custom_dictionaries=None,
    custom_regexes=None,
    max_findings=None,
    include_quote=True,
    mime_type=None,
):
    """Uses the Data Loss Prevention API to analyze a file for protected data.
    Args:
        project: The Google Cloud project id to use as a parent resource.
        filename: The path to the file to inspect.
        info_types: A list of strings representing info types to look for.
            A full list of info type categories can be fetched from the API.
        min_likelihood: A string representing the minimum likelihood threshold
            that constitutes a match. One of: 'LIKELIHOOD_UNSPECIFIED',
            'VERY_UNLIKELY', 'UNLIKELY', 'POSSIBLE', 'LIKELY', 'VERY_LIKELY'.
        max_findings: The maximum number of findings to report; 0 = no maximum.
        include_quote: Boolean for whether to display a quote of the detected
            information in the results.
        mime_type: The MIME type of the file. If not specified, the type is
            inferred via the Python standard library's mimetypes module.
    Returns:
        None; the response from the API is printed to the terminal.
    """

    import mimetypes

    # Import the client library.
    import google.cloud.dlp

    # Instantiate a client.
    dlp = google.cloud.dlp_v2.DlpServiceClient()

    # Prepare info_types by converting the list of strings into a list of
    # dictionaries (protos are also accepted).
    if not info_types:
        info_types = ["FIRST_NAME", "LAST_NAME", "EMAIL_ADDRESS"]
    info_types = [{"name": info_type} for info_type in info_types]

    # Prepare custom_info_types by parsing the dictionary word lists and
    # regex patterns.
    if custom_dictionaries is None:
        custom_dictionaries = []
    dictionaries = [
        {
            "info_type": {"name": "CUSTOM_DICTIONARY_{}".format(i)},
            "dictionary": {"word_list": {"words": custom_dict.split(",")}},
        }
        for i, custom_dict in enumerate(custom_dictionaries)
    ]
    if custom_regexes is None:
        custom_regexes = []
    regexes = [
        {
            "info_type": {"name": "CUSTOM_REGEX_{}".format(i)},
            "regex": {"pattern": custom_regex},
        }
        for i, custom_regex in enumerate(custom_regexes)
    ]
    custom_info_types = dictionaries + regexes

    # Construct the configuration dictionary. Keys which are None may
    # optionally be omitted entirely.
    inspect_config = {
        "info_types": info_types,
        "custom_info_types": custom_info_types,
        "min_likelihood": min_likelihood,
        "limits": {"max_findings_per_request": max_findings},
    }

    # If mime_type is not specified, guess it from the filename.
    if mime_type is None:
        mime_guess = mimetypes.MimeTypes().guess_type(filename)
        mime_type = mime_guess[0]

    # Select the content type index from the list of supported types.
    supported_content_types = {
        None: 0,  # "Unspecified"
        "image/jpeg": 1,
        "image/bmp": 2,
        "image/png": 3,
        "image/svg": 4,
        "text/plain": 5,
    }
    content_type_index = supported_content_types.get(mime_type, 0)

    # Construct the item, containing the file's byte data.
    with open(filename, mode="rb") as f:
        item = {"byte_item": {"type": content_type_index, "data": f.read()}}

    # Convert the project id into a full resource id.
    parent = dlp.project_path(project)

    # Call the API.
    response = dlp.inspect_content(parent, inspect_config, item)

    # Print out the results.
    if response.result.findings:
        for finding in response.result.findings:
            try:
                print("Quote: {}".format(finding.quote))
            except AttributeError:
                pass
            print("Info type: {}".format(finding.info_type.name))
            print("Likelihood: {}".format(finding.likelihood))
    else:
        print("No findings.")

Go

import (
	"context"
	"fmt"
	"io"
	"io/ioutil"

	dlp "cloud.google.com/go/dlp/apiv2"
	dlppb "google.golang.org/genproto/googleapis/privacy/dlp/v2"
)

// inspectTextFile inspects a text file at a given filePath, and prints results.
func inspectTextFile(w io.Writer, projectID, filePath string) error {
	// projectID := "my-project-id"
	// filePath := "path/to/image.png"
	ctx := context.Background()

	// Initialize client.
	client, err := dlp.NewClient(ctx)
	if err != nil {
		return err
	}
	defer client.Close() // Closing the client safely cleans up background resources.

	// Gather the resources for the request.
	data, err := ioutil.ReadFile(filePath)
	if err != nil {
		return err
	}

	// Create and send the request.
	req := &dlppb.InspectContentRequest{
		Parent: "projects/" + projectID,
		Item: &dlppb.ContentItem{
			DataItem: &dlppb.ContentItem_ByteItem{
				ByteItem: &dlppb.ByteContentItem{
					Type: dlppb.ByteContentItem_TEXT_UTF8,
					Data: data,
				},
			},
		},
		InspectConfig: &dlppb.InspectConfig{
			InfoTypes: []*dlppb.InfoType{
				{Name: "PHONE_NUMBER"},
				{Name: "EMAIL_ADDRESS"},
				{Name: "CREDIT_CARD_NUMBER"},
			},
			IncludeQuote: true,
		},
	}
	resp, err := client.InspectContent(ctx, req)
	if err != nil {
		return fmt.Errorf("InspectContent: %v", err)
	}

	// Process the results.
	fmt.Fprintf(w, "Findings: %d\n", len(resp.Result.Findings))
	for _, f := range resp.Result.Findings {
		fmt.Fprintf(w, "\tQoute: %s\n", f.Quote)
		fmt.Fprintf(w, "\tInfo type: %s\n", f.InfoType.Name)
		fmt.Fprintf(w, "\tLikelihood: %s\n", f.Likelihood)
	}
	return nil
}

PHP

use Google\Cloud\Dlp\V2\DlpServiceClient;
use Google\Cloud\Dlp\V2\ContentItem;
use Google\Cloud\Dlp\V2\InfoType;
use Google\Cloud\Dlp\V2\InspectConfig;
use Google\Cloud\Dlp\V2\ByteContentItem;
use Google\Cloud\Dlp\V2\ByteContentItem\BytesType;
use Google\Cloud\Dlp\V2\Likelihood;

/** Uncomment and populate these variables in your code */
// $projectId = 'YOUR_PROJECT_ID';
// $filepath = 'path/to/image.png';

// Instantiate a client.
$dlp = new DlpServiceClient();

// Get the bytes of the file
$fileBytes = (new ByteContentItem())
    ->setType(BytesType::IMAGE_PNG)
    ->setData(file_get_contents($filepath));

// Construct request
$parent = $dlp->projectName($projectId);
$item = (new ContentItem())
    ->setByteItem($fileBytes);
$inspectConfig = (new InspectConfig())
    // The infoTypes of information to match
    ->setInfoTypes([
        (new InfoType())->setName('PHONE_NUMBER'),
        (new InfoType())->setName('EMAIL_ADDRESS'),
        (new InfoType())->setName('CREDIT_CARD_NUMBER')
    ])
    // Whether to include the matching string
    ->setIncludeQuote(true);

// Run request
$response = $dlp->inspectContent($parent, [
    'inspectConfig' => $inspectConfig,
    'item' => $item
]);

// Print the results
$findings = $response->getResult()->getFindings();
if (count($findings) == 0) {
    print('No findings.' . PHP_EOL);
} else {
    print('Findings:' . PHP_EOL);
    foreach ($findings as $finding) {
        print('  Quote: ' . $finding->getQuote() . PHP_EOL);
        print('  Info type: ' . $finding->getInfoType()->getName() . PHP_EOL);
        $likelihoodString = Likelihood::name($finding->getLikelihood());
        print('  Likelihood: ' . $likelihoodString . PHP_EOL);
    }
}

Ruby

# project_id   = "Your Google Cloud project ID"
# filename     = "The file path to the file to inspect"
# max_findings = "Maximum number of findings to report per request (0 = server maximum)"

require "google/cloud/dlp"

dlp = Google::Cloud::Dlp.new
inspect_config = {
  # The types of information to match
  info_types:     [{ name: "PERSON_NAME" }, { name: "PHONE_NUMBER" }],

  # Only return results above a likelihood threshold (0 for all)
  min_likelihood: :POSSIBLE,

  # Limit the number of findings (0 for no limit)
  limits:         { max_findings_per_request: max_findings },

  # Whether to include the matching string in the response
  include_quote:  true
}

# The item to inspect
file = File.open filename, "rb"
item_to_inspect = { byte_item: { type: :BYTES_TYPE_UNSPECIFIED, data: file.read } }

# Run request
parent = "projects/#{project_id}"
response = dlp.inspect_content parent,
                               inspect_config: inspect_config,
                               item:           item_to_inspect

# Print the results
if response.result.findings.empty?
  puts "No findings"
else
  response.result.findings.each do |finding|
    puts "Quote:      #{finding.quote}"
    puts "Info type:  #{finding.info_type.name}"
    puts "Likelihood: #{finding.likelihood}"
  end
end

C#

private static readonly Dictionary<string, ByteContentItem.Types.BytesType> s_fileTypes =
    new Dictionary<string, ByteContentItem.Types.BytesType>()
{
    { ".bmp", ByteContentItem.Types.BytesType.ImageBmp },
    { ".jpg", ByteContentItem.Types.BytesType.ImageJpeg },
    { ".jpeg", ByteContentItem.Types.BytesType.ImageJpeg },
    { ".png", ByteContentItem.Types.BytesType.ImagePng },
    { ".svg", ByteContentItem.Types.BytesType.ImageSvg },
    { ".txt", ByteContentItem.Types.BytesType.TextUtf8 }
};

public static object InspectFile(
    string projectId,
    string file,
    string minLikelihood,
    int maxFindings,
    bool includeQuote,
    IEnumerable<InfoType> infoTypes,
    IEnumerable<CustomInfoType> customInfoTypes)
{
    var fileStream = new FileStream(file, FileMode.Open);
    try
    {
        var inspectConfig = new InspectConfig
        {
            MinLikelihood = (Likelihood)System.Enum.Parse(typeof(Likelihood), minLikelihood),
            Limits = new FindingLimits
            {
                MaxFindingsPerRequest = maxFindings
            },
            IncludeQuote = includeQuote,
            InfoTypes = { infoTypes },
            CustomInfoTypes = { customInfoTypes }
        };
        DlpServiceClient dlp = DlpServiceClient.Create();
        InspectContentResponse response = dlp.InspectContent(new InspectContentRequest
        {
            ParentAsProjectName = new ProjectName(projectId),
            Item = new ContentItem
            {
                ByteItem = new ByteContentItem
                {
                    Data = ByteString.FromStream(fileStream),
                    Type = s_fileTypes.GetValueOrDefault(
                            new FileInfo(file).Extension.ToLower(),
                            ByteContentItem.Types.BytesType.Unspecified
                    )
                }
            },
            InspectConfig = inspectConfig
        });

        var findings = response.Result.Findings;
        if (findings.Count > 0)
        {
            Console.WriteLine("Findings:");
            foreach (var finding in findings)
            {
                if (includeQuote)
                {
                    Console.WriteLine($"  Quote: {finding.Quote}");
                }
                Console.WriteLine($"  InfoType: {finding.InfoType}");
                Console.WriteLine($"  Likelihood: {finding.Likelihood}");
            }
        }
        else
        {
            Console.WriteLine("No findings.");
        }

        return 0;
    }
    finally
    {
        fileStream.Close();
    }
}

Try it out

You can try each of these examples out yourself—or experiment with your own images—in the APIs Explorer on the reference page for content.inspect:

Go to APIs Explorer

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