Выводим изображение в кодировке base64 на html/css и сохраняем его на jquery+php

Limits of the IMAGE function

Images in tables only

fields only work in tables. If you change the visualization type, any fields in the chart will be ignored, or the image URL will appear as the dimension value.


Images and your data

In addition to the name of a file you want view, hyperlinks and image URLs can also send information, in the form of query parameters appended to the URL path. For example:

This URL is requesting the JPEG image . It is also sending data via the and parameters.

When reports or data sources contain hyperlinks or image URLs, you should make sure that these point to trusted domains, and that any additional data being sent makes sense to you.

To help with this, images in Data Studio have the following limits:

Images and the data control

When a report includes a data control, images appear when:

  • the data control is showing the default data set
  • the data control is showing a different (non-default) data set AND the field is serving images from a trusted domain. Currently, this includes most Google domains.

If the data control is showing a different (non-default) data set AND images are requested from an untrusted domain, images won’t appear. Instead, the table will display the image URL. Report viewers can click the URL to view the image, and are shown a dialog asking them to make sure the link goes to a trusted domain.

Images in copied data sources

When you copy a data source, all fields are disabled in the copy. You can re-enable images by doing the following:

  1. Edit the data source
  2. For each field you want to enable, click
  3. Select Enable.

API

Callback

Function signature

var loadingImage = loadImage(
  'https://example.org/image.png',
  function (img) {
    document.body.appendChild(img)
  },
  { maxWidth: 600 }
)

Cancel image loading

var loadingImage = loadImage(
  'https://example.org/image.png',
  function (img) {
    document.body.appendChild(img)
  },
  { maxWidth: 600 }
)

if (loadingImage) {
  // Unset event handling for the loading image:
  loadingImage.onload = loadingImage.onerror = null

  // Cancel image loading process:
  if (loadingImage.abort) {
    // FileReader instance, stop the file reading process:
    loadingImage.abort()
  } else {
    // HTMLImageElement element, cancel the original image request by changing
    // the target source to the data URL of a 1x1 pixel transparent image GIF:
    loadingImage.src =
      'data:image/gif;base64,' +
      'R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7'
  }
}

Please note: The element (or instance) for the loading image is only returned when using the callback style API and not available with the based API.

Callback arguments

For the callback style API, the second argument to must be a function, which is called when the image has been loaded or an error occurred while loading the image.

The callback function is passed two arguments:

  1. An object with the original image dimensions as properties and potentially additional .
loadImage(
  fileOrBlobOrUrl,
  function (img, data) {
    document.body.appendChild(img)
    console.log('Original image width: ', data.originalWidth)
    console.log('Original image height: ', data.originalHeight)
  },
  { maxWidth: 600, meta: true }
)

Please note: The original image dimensions reflect the natural width and height of the loaded image before applying any transformation. For consistent values across browsers, parsing has to be enabled via , so can detect automatic image orientation and normalize the dimensions.

Error handling

Example code implementing error handling:

loadImage(
  fileOrBlobOrUrl,
  function (img, data) {
    if (img.type === 'error') {
      console.error('Error loading image file')
    } else {
      document.body.appendChild(img)
    }
  },
  { maxWidth: 600 }
)

Promise

loadImage(fileOrBlobOrUrl, { maxWidth: 600, meta: true })
  .then(function (data) {
    document.body.appendChild(data.image)
    console.log('Original image width: ', data.originalWidth)
    console.log('Original image height: ', data.originalHeight)
  })
  .catch(function (err) {
    // Handling image loading errors
    console.log(err)
  })

The resolves with an object with the following properties:

  • : The original width of the image.
  • : The original height of the image.

Please also read the note about original image dimensions normalization in the section.

If has been parsed, additional properties might be present on the object.

microaneurysms¶

()

Gray-level “microaneurysms” image.

Detail from an image of the retina (green channel). The image is a crop of image 07_dr.JPG from the High-Resolution Fundus (HRF) Image Database: https://www5.cs.fau.de/research/data/fundus-images/

Returns
microaneurysms(102, 102) uint8 ndarray

Retina image with lesions.

Notes


No copyright restrictions. CC0 given by owner (Andreas Maier).

References

1

Budai, A., Bock, R, Maier, A., Hornegger, J., Michelson, G. (2013). Robust Vessel Segmentation in Fundus Images. International Journal of Biomedical Imaging, vol. 2013, 2013. DOI:10.1155/2013/154860

lfw_subset¶

()

Subset of data from the LFW dataset.

This database is a subset of the LFW database containing:

  • 100 faces

  • 100 non-faces

The full dataset is available at .

Returns
images(200, 25, 25) uint8 ndarray

100 first images are faces and subsequent 100 are non-faces.

Notes

The faces were randomly selected from the LFW dataset and the non-faces were extracted from the background of the same dataset. The cropped ROIs have been resized to a 25 x 25 pixels.

References

1

Huang, G., Mattar, M., Lee, H., & Learned-Miller, E. G. (2012). Learning to align from scratch. In Advances in Neural Information Processing Systems (pp. 764-772).

binary_blobs¶

(length=512, blob_size_fraction=0.1, n_dim=2, volume_fraction=0.5, seed=None)

Generate synthetic binary image with several rounded blob-like objects.

Parameters
lengthint, optional

Linear size of output image.

blob_size_fractionfloat, optional

Typical linear size of blob, as a fraction of , should be smaller than 1.

n_dimint, optional

Number of dimensions of output image.

volume_fractionfloat, default 0.5

Fraction of image pixels covered by the blobs (where the output is 1). Should be in .

seedint, optional

Seed to initialize the random number generator. If None, a random seed from the operating system is used.

Returns
blobsndarray of bools

Output binary image

Examples

>>> from skimage import data
>>> data.binary_blobs(length=5, blob_size_fraction=0.2, seed=1)
array(,
       ,
       ,
       ,
       ])
>>> blobs = data.binary_blobs(length=256, blob_size_fraction=0.1)
>>> # Finer structures
>>> blobs = data.binary_blobs(length=256, blob_size_fraction=0.05)
>>> # Blobs cover a smaller volume fraction of the image
>>> blobs = data.binary_blobs(length=256, volume_fraction=0.3)

What are the pros and cons of using Base64 encoded data URIs?


Since data URI has its advantages and disadvantages, as well as gray magic, it can be harmful if not used wisely. So read carefully what you get by using Base64 encoded data URIs on HTML pages.

  • pros:
    1. Speeds up page loading, because the browser will not be limited by the maximum number of concurrent HTTP requests.
    2. Reduces the server load, since the browser makes only one HTTP request. As result, the server can simultaneously serve more clients.
    3. Provides a simple hotlinking protection since no one can embed images onto their pages directly from your server.
    4. Makes pages independent of external files, allowing you to easily share them even offline.
    5. Improves performance (preliminary tests showed that the browser requires less CPU).
  • cons:
    1. The size of the Base64 encoded data grows by 33%.
    2. Even on minimal page changes, the browser must re-cache and reload all images.
    3. Difficult image editing, because you first need to decode the Base64 string.
    4. It is more difficult to debug, especially that Base64 strings are very long.
    5. Ignores user settings who have disabled images to save Internet bandwidth usage.
    6. It always takes up space even if images are not used on the current page.
    7. Unlike images, stylesheets block the webpage rendering.

How the IMAGE function works

The function takes a URL as input. The parameter can come from existing URL fields in the data source, or the parameter can be an expression that builds URLs from other fields and functions.

The optional parameter provides the the image’s alt text, which can be used by screen readers to assist vision-impaired users.

To display images in a report, add the field created by the function to a table in your report. The size of the image displayed depends on the width of the column containing the image. If the URL is incorrect, or the image type is not supported, a broken image icon is displayed instead.

The Type drop-down menu is disabled for fields.

HTML Tags

<!—><!DOCTYPE><a><abbr><acronym><address><applet><area><article><aside><audio><b><base><basefont><bdi><bdo><big><blockquote><body><br><button><canvas><caption><center><cite><code><col><colgroup><data><datalist><dd><del><details><dfn><dialog><dir><div><dl><dt><em><embed><fieldset><figcaption><figure><font><footer><form><frame><frameset><h1> — <h6><head><header><hr><html><i><iframe><img><input><ins><kbd><label><legend><li><link><main><map><mark><meta><meter><nav><noframes><noscript><object><ol><optgroup><option><output><p><param><picture><pre><progress><q><rp><rt><ruby><s><samp><script><section><select><small><source><span><strike><strong><style><sub><summary><sup><svg><table><tbody><td><template><textarea><tfoot><th><thead><time><title><tr><track><tt><u><ul><var><video>

lfw_subset¶

()

Subset of data from the LFW dataset.

This database is a subset of the LFW database containing:

  • 100 faces

  • 100 non-faces

The full dataset is available at .

Returns
images(200, 25, 25) uint8 ndarray

100 first images are faces and subsequent 100 are non-faces.

Notes

The faces were randomly selected from the LFW dataset and the non-faces were extracted from the background of the same dataset. The cropped ROIs have been resized to a 25 x 25 pixels.

References

1

Huang, G., Mattar, M., Lee, H., & Learned-Miller, E. G. (2012). Learning to align from scratch. In Advances in Neural Information Processing Systems (pp. 764-772).

cell¶

()

Cell floating in saline.

This is a quantitative phase image retrieved from a digital hologram using the Python library . The image shows a cell with high phase value, above the background phase.

Because of a banding pattern artifact in the background, this image is a good test of thresholding algorithms. The pixel spacing is 0.107 µm.

These data were part of a comparison between several refractive index retrieval techniques for spherical objects as part of .

This image is CC0, dedicated to the public domain. You may copy, modify, or distribute it without asking permission.

Returns
cell(660, 550) uint8 array

Image of a cell.


References

Paul Müller, Mirjam Schürmann, Salvatore Girardo, Gheorghe Cojoc, and Jochen Guck. “Accurate evaluation of size and refractive index for spherical objects in quantitative phase imaging.” Optics Express 26(8): 10729-10743 (2018). DOI:10.1364/OE.26.010729

HTML Reference

HTML by AlphabetHTML by CategoryHTML Browser SupportHTML AttributesHTML Global AttributesHTML EventsHTML ColorsHTML CanvasHTML Audio/VideoHTML Character SetsHTML DoctypesHTML URL EncodeHTML Language CodesHTML Country CodesHTTP MessagesHTTP MethodsPX to EM ConverterKeyboard Shortcuts

HTML Tags

<!—> <!DOCTYPE> <a> <abbr> <acronym> <address> <applet> <area> <article> <aside> <audio> <b> <base> <basefont> <bdi> <bdo> <big> <blockquote> <body> <br> <button> <canvas> <caption> <center> <cite> <code> <col> <colgroup> <data> <datalist> <dd> <del> <details> <dfn> <dialog> <dir> <div> <dl> <dt> <em> <embed> <fieldset> <figcaption> <figure> <font> <footer> <form> <frame> <frameset> <h1> — <h6> <head> <header> <hr> <html> <i> <iframe> <img> <input> <ins> <kbd> <label> <legend> <li> <link> <main> <map> <mark> <meta> <meter> <nav> <noframes> <noscript> <object> <ol> <optgroup> <option> <output> <p> <param> <picture> <pre> <progress> <q> <rp> <rt> <ruby> <s> <samp> <script> <section> <select> <small> <source> <span> <strike> <strong> <style> <sub> <summary> <sup> <svg> <table> <tbody> <td> <template> <textarea> <tfoot> <th> <thead> <time> <title> <tr> <track> <tt> <u> <ul> <var> <video> <wbr>

microaneurysms¶

()

Gray-level “microaneurysms” image.

Detail from an image of the retina (green channel). The image is a crop of image 07_dr.JPG from the High-Resolution Fundus (HRF) Image Database: https://www5.cs.fau.de/research/data/fundus-images/

Returns
microaneurysms(102, 102) uint8 ndarray

Retina image with lesions.

Notes

No copyright restrictions. CC0 given by owner (Andreas Maier).

References

1

Budai, A., Bock, R, Maier, A., Hornegger, J., Michelson, G. (2013). Robust Vessel Segmentation in Fundus Images. International Journal of Biomedical Imaging, vol. 2013, 2013. DOI:10.1155/2013/154860

stereo_motorcycle¶

()

Rectified stereo image pair with ground-truth disparities.

The two images are rectified such that every pixel in the left image has its corresponding pixel on the same scanline in the right image. That means that both images are warped such that they have the same orientation but a horizontal spatial offset (baseline). The ground-truth pixel offset in column direction is specified by the included disparity map.

The two images are part of the Middlebury 2014 stereo benchmark. The dataset was created by Nera Nesic, Porter Westling, Xi Wang, York Kitajima, Greg Krathwohl, and Daniel Scharstein at Middlebury College. A detailed description of the acquisition process can be found in .

The images included here are down-sampled versions of the default exposure images in the benchmark. The images are down-sampled by a factor of 4 using the function . The calibration data in the following and the included ground-truth disparity map are valid for the down-sampled images:

Focal length           994.978px
Principal point x      311.193px
Principal point y      254.877px
Principal point dx      31.086px
Baseline               193.001mm
Returns
img_left(500, 741, 3) uint8 ndarray

Left stereo image.

img_right(500, 741, 3) uint8 ndarray

Right stereo image.

disp(500, 741, 3) float ndarray

Ground-truth disparity map, where each value describes the offset in column direction between corresponding pixels in the left and the right stereo images. E.g. the corresponding pixel of is . NaNs denote pixels in the left image that do not have ground-truth.

Notes

The original resolution images, images with different exposure and lighting, and ground-truth depth maps can be found at the Middlebury website .

References

D. Scharstein, H. Hirschmueller, Y. Kitajima, G. Krathwohl, N. Nesic, X. Wang, and P. Westling. High-resolution stereo datasets with subpixel-accurate ground truth. In German Conference on Pattern Recognition (GCPR 2014), Muenster, Germany, September 2014.

More Examples

Example

Use getImageData() to invert the color of every pixels of an image on the canvas:

YourbrowserdoesnotsupporttheHTML5canvastag.

JavaScript:

var c = document.getElementById(«myCanvas»); var ctx = c.getContext(«2d»); var img = document.getElementById(«scream»); ctx.drawImage(img, 0, 0); var imgData = ctx.getImageData(0, 0, c.width, c.height); // invert colorsvar i; for (i = 0; i < imgData.data.length; i += 4) {   imgData.data = 255-imgData.data;   imgData.data = 255-imgData.data;   imgData.data = 255-imgData.data;   imgData.data = 255; } ctx.putImageData(imgData, 0, 0);

Usage

Image loading

In your application code, use the function with style:

document.getElementById('file-input').onchange = function () {
  loadImage(
    this.files,
    function (img) {
      document.body.appendChild(img)
    },
    { maxWidth: 600 } // Options
  )
}

Or use the based API like this ( a polyfill for older browsers):

document.getElementById('file-input').onchange = function () {
  loadImage(this.files, { maxWidth: 600 }).then(function (data) {
    document.body.appendChild(data.image)
  })
}
document.getElementById('file-input').onchange = async function () {
  let data = await loadImage(this.files, { maxWidth: 600 })
  document.body.appendChild(data.image)
}

Image scaling

It is also possible to use the image scaling functionality directly with an existing image:

var scaledImage = loadImage.scale(
  img, // img or canvas element
  { maxWidth: 600 }
)

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