Skip to main content

Why would this JavaScript work when hosted but not when offline? [duplicate]

When using this code to sort pixels, the code works fine with the default image when hosted online. However, when testing the script offline, the default image loads but does not process correctly through the sorter. What is causing the behavior to work in an online hosted environment but not in a localized, offline environment?

See online code here: http://birdhat.org/misc/sort-pixels/

var READY_STATUS = ' '
var FIRSTLOAD_STATUS = ' ';
var SORTING_STATUS = 'Sorting (be patient)';
var FINISHING_STATUS = 'Finishing up...';
var FILENAME = null;
var SORTING_FILENAME = null;
var STATE = 'ready';

//================================================================================
// UTILS

var rgb2hsv = function(r, g, b) {
  // given r,g,b in the range 0-255,
  // return [h,s,v] in the range 0-1
  var rr, gg, bb,
    r = r / 255,
    g = g / 255,
    b = b / 255,
    h, s,
    v = Math.max(r, g, b),
    diff = v - Math.min(r, g, b),
    diffc = function(c) {
      return (v - c) / 6 / diff + 1 / 2;
    };
  if (diff == 0) {
    h = s = 0;
  } else {
    s = diff / v;
    rr = diffc(r);
    gg = diffc(g);
    bb = diffc(b);

    if (r === v) {
      h = bb - gg;
    } else if (g === v) {
      h = (1 / 3) + rr - bb;
    } else if (b === v) {
      h = (2 / 3) + gg - rr;
    }

    if (h < 0) {
      h += 1;
    } else if (h > 1) {
      h -= 1;
    }
  }
  return [h, s, v];
};

//================================================================================
// INTERFACE

var setStatus = function(msg) {
  document.getElementById('status').innerHTML = msg;
};

//================================================================================
// SORTING

var sortOneStep = function(sort_list, my_canvas, context, ii) {
  // do one step of sorting and queue up the next one

  var first_is_horizontal = 1;

  // on first step, remember the filename
  if (ii == 0) {
    SORTING_FILENAME = FILENAME;
  }

  // if the filename has changed, stop
  if (ii > 0 && FILENAME != SORTING_FILENAME) {
    finish(my_canvas, false); // need to avoid copy here or something
    return;
  }

  // stop when we've finished all the sorts
  if (ii >= sort_list.length) {
    finish(my_canvas, true);
    return;
  }

  sortImage(my_canvas, context, ii, (ii + first_is_horizontal) % 2, sort_list[ii]);
  var bar_chars = [];
  for (var char_ii = 0; char_ii < sort_list.length; char_ii++) {
    if (char_ii <= ii) {
      bar_chars.push('=');
    } else {
      bar_chars.push('&nbsp;');
    }
  }
  setStatus(SORTING_STATUS + ' <code>[' + bar_chars.join('') + ']</code>');
  var timeout_length = 100;
  //if (ii === 1) { timeout_length = 2500; }
  setTimeout(function() {
    sortOneStep(sort_list, my_canvas, context, ii + 1);
  }, timeout_length);
};

var finish = function(my_canvas, done) {
  setStatus(FINISHING_STATUS);
  var my_image = document.getElementById('my-image');
  if (done) {
    my_image.src = my_canvas.toDataURL('image/png');
  }
  my_image.className = '';
  my_canvas.className = 'invisible';
  setStatus(READY_STATUS);
  console.log('DONE');
  STATE = 'ready';
  document.getElementById('sort-button-quick').className = 'ready-button';
  document.getElementById('sort-button-thorough').className = 'ready-button';
}

var sortImage = function(my_canvas, context, ii, is_horizontal, kind) {
  // sort the entire image

  var dir_name;
  if (is_horizontal) {
    dir_name = 'horizontal';
    for (var y = 0; y < my_canvas.height; y += 1) {
      sortRegion(context, 0, y, my_canvas.width, 1, kind);
    }
  } else {
    dir_name = 'vertical';
    for (var x = 0; x < my_canvas.width; x += 1) {
      sortRegion(context, x, 0, 1, my_canvas.height, kind);
    }
  }
  console.log('' + ii + ' -- sorted ' + dir_name + ' by ' + kind);
};

var sortRegion = function(context, x, y, width, height, kind) {
  // sort a rectangular region of the image, usually a single row or column of pixels
  // kind should be one of: random, semirandom, v, h, h2, s, magic

  // fetch image data
  var imgData = context.getImageData(x, y, width, height);
  var data = imgData.data;

  // convert to sortable pixel array
  var pixels = [];
  for (var ii = 0; ii < imgData.data.length; ii += 4) {
    var pixel = [data[ii], data[ii + 1], data[ii + 2]];

    switch (kind) {
      case 'v':
        var sortValue = -(pixel[0] + pixel[1] + pixel[2]);
        var sortValue = -(pixel[0] * 0.30 + pixel[1] * 0.59 + pixel[2] * 0.11);
        break;
      case 'semirandom':
        var sortValue = ii / 4 + Math.random() * 25;
        break;
      case 'random':
        var sortValue = Math.random();
        break;
      default:
        hsv = rgb2hsv(pixel[0], pixel[1], pixel[2]);
        var h = hsv[0];
        var s = hsv[1];
        var v = (pixel[0] + pixel[1] + pixel[2]) / (255 * 3);
        if (kind === 'magic') {
          var sortValue = 1 - ((h + 0.2) % 1);
          if (s < 0.07) {
            if (v < 0.5) {
              sortValue = v - 300;
            } else {
              sortValue = v + 300;
            }
          } else {
            if (v < 0.2) {
              sortValue = v - 300;
            };
            if (v > 0.9) {
              sortValue = v + 300;
            };
          }
        } else if (kind === 'h') {
          var sortValue = h;
        } else if (kind === 'h2') {
          var sortValue = (h + 0.15) % 1;
          if (s < 0.07) {
            sortValue -= 900;
          }
        } else if (kind === 's') {
          var sortValue = s;
        }
    }

    pixels.push([sortValue, pixel]);
  }

  // sort
  pixels.sort(function(a, b) {
    return a[0] - b[0];
  });

  // write back to data array and then back to canvas
  for (var jj = 0; jj < pixels.length; jj++) {
    var pixel = pixels[jj][1];
    data[jj * 4 + 0] = pixel[0];
    data[jj * 4 + 1] = pixel[1];
    data[jj * 4 + 2] = pixel[2];
  }
  context.putImageData(imgData, x, y);

};

//================================================================================
// MAIN
var wo = window.onload;
window.onload = function() {
  wo && wo.call(null);

  setStatus(FIRSTLOAD_STATUS);


  var handleDragOver = function(evt) {
    evt.stopPropagation();
    evt.preventDefault();
    evt.dataTransfer.dropEffect = 'copy';
    dropZone.className = 'big-border';
  };

  var handleDragLeave = function(evt) {
    evt.stopPropagation();
    evt.preventDefault();
    dropZone.className = '';
  };

  var handleFileDrop = function(evt) {
    // when the user drops a file,
    // load it into an img tag
    // and then copy the data into the canvas
    console.log('[handleFileDrop]');
    evt.stopPropagation();
    evt.preventDefault();

    dropZone.className = '';

    var files = evt.dataTransfer.files;

    // only allow one file to be dropped
    if (files.length !== 1) {
      return;
    }

    for (var ii = 0; ii < files.length; ii++) {
      var file = files[ii];
      FILENAME = file.name;
      console.log(FILENAME);

      // only allow images
      if (!file.type.match('image.*')) {
        continue;
      }

      var reader = new FileReader();
      reader.onload = (function(theFile) {
        return function(e) {
          droppedImageTag = document.getElementById('my-image').src = e.target.result;
        };
      })(file);

      reader.readAsDataURL(file);
    }
  };

  var body = document.getElementById('body');
  var dropZone = document.getElementById('drop-zone');
  body.addEventListener('dragover', handleDragOver, false);
  body.addEventListener('dragleave', handleDragLeave, false);
  body.addEventListener('drop', handleFileDrop, false);

  var copyImgToCanvas = function(image_id, canvas_id) {
    console.log('[copyImgToCanvas] ' + image_id + ' --> ' + canvas_id);
    var my_image = document.getElementById(image_id);
    var my_canvas = document.getElementById(canvas_id);
    var context = my_canvas.getContext('2d');

    my_canvas.width = my_image.width;
    my_canvas.height = my_image.height;

    my_canvas.className = '';
    my_image.className = 'invisible';

    context.drawImage(my_image, 0, 0);
  };

  var handleButtonClick = function() {
    STATE = 'sorting';
    console.log('[click]');
    setStatus(SORTING_STATUS);
    document.getElementById('sort-button-quick').className = 'disabled-button';
    document.getElementById('sort-button-thorough').className = 'disabled-button';
  };

  var launchSorting = function(sort_list) {
    var my_canvas = document.getElementById('my-canvas');
    var context = my_canvas.getContext('2d');
    copyImgToCanvas('my-image', 'my-canvas');
    sortOneStep(sort_list, my_canvas, context, 0);
  };

  document.getElementById('sort-button-quick').onclick = function() {
    if (STATE === 'sorting') {
      return;
    }
    handleButtonClick();
    // random, semirandom, v, h, h2, s, magic
    var sort_list = ['semirandom', 'v']
    setTimeout(function() {
      launchSorting(sort_list)
    }, 1)
  };
  document.getElementById('sort-button-thorough').onclick = function() {
    if (STATE === 'sorting') {
      return;
    }
    handleButtonClick();
    // random, semirandom, v, h, h2, s, magic
    var sort_list = ['h2', 'v', 'h2', 'v', 'h2', 'v', 'h2', 'v', 'h2', 'v', 'h2', 'v', ];
    setTimeout(function() {
      launchSorting(sort_list)
    }, 1)
  };
  document.getElementById('sort-button-quick').className = 'ready-button';
  document.getElementById('sort-button-thorough').className = 'ready-button';
};
body {
  text-align: center;
  padding: 0px;
  margin: 0px;
  color: #bbb;
  font-family: 'Helvetica Neue', Helvetica, sans-serif;
  background: #333;
  font-size: 14px;
  line-height: 20px;
}

#copy {
  background: #000;
  padding: 10px;
  padding-left: 30px;
  padding-right: 30px;
  text-align: left;
}

#topbar {
  text-align: left;
}

#sort-button-quick {
  padding: 12px;
  display: inline-block;
  text-align: center;
  border-style: solid;
  border-width: 2px;
  margin-left: 30px;
}

#sort-button-thorough {
  padding: 12px;
  display: inline-block;
  text-align: center;
  border-style: solid;
  border-width: 2px;
  margin-left: 15px;
}

.ready-button {
  background: #777;
  color: white;
  border-color: white;
}

.ready-button>a {
  color: white;
  text-decoration: none;
}

.disabled-button {
  font-style: italic;
  background: #606060;
  color: #ccc;
  border-color: #bbb;
}

.disabled-button>a {
  color: #ccc;
  text-decoration: none;
}

#status {
  padding: 12px;
  display: inline-block;
  color: #ff8;
}

#drop-zone-wrapper {
  background: #000;
}

#drop-zone {
  padding-top: 50px;
  padding-bottom: 50px;
  background: #000;
  border-radius: 30px;
  border-style: dashed;
  border-color: black;
  border-width: 10px;
}

.big-border {
  border-color: #aaa !important;
}

.invisible {
  display: none;
}

.dotted {
  border-style: dotted;
  border-color: red;
  border-width: 1px;
}
<!DOCTYPE html>
<html>

<head>
</head>

<body id="body">

  <div id="copy">
    <h3> Image pixel sorter </h3>
    <p>
      Drag an image from your computer into this page, then click Sort. The pixels will be sorted vertically by brightness and horizontally by hue.
    </p>
    <p>
      To use an image from the web, drag it to your desktop first and then into this page. Use small images or it will be very slow.
    </p>
    <p>
      <a href="http://sorted-pixels.tumblr.com/" style="color:#8af;">Blog of results</a>
    </p>
  </div>

  <div id="topbar">
    <div id="sort-button-quick" class="disabled-button"><a> Two-Step Sort </a></div>
    <div id="sort-button-thorough" class="disabled-button"><a> Twelve-Step Sort </a></div>
    <div id="status">&nbsp;</div>
  </div>

  <div id="drop-zone-wrapper">
    <div id="drop-zone">
      <canvas id="my-canvas" width=100 height=100 class="invisible"></canvas>
      <img id="my-image" src="img/sunset.png">
    </div>
  </div>

</body>

</html>

I've tried moving the images, rerouting the sources for the loading of them, moving the image loading into the onload function... I have the sunset.png default image in an img folder with code. It displays correctly, but does not execute the pixel sorting when offline.

Via Active questions tagged javascript - Stack Overflow https://ift.tt/BNalQG7

Labels

Labels:

Comments

Post a Comment

Popular posts from this blog

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...
Post a Comment
Read more

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings
Post a Comment
Read more

How to load Javascript with imported modules?

I am trying to import modules from tensorflowjs, and below is my code. test.html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Document</title </head> <body> <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.0/dist/tf.min.js"></script> <script type="module" src="./test.js"></script> </body> </html> test.js import * as tf from "./node_modules/@tensorflow/tfjs"; import {loadGraphModel} from "./node_modules/@tensorflow/tfjs-converter"; const MODEL_URL = './model.json'; const model = await loadGraphModel(MODEL_URL); const cat = document.getElementById('cat'); model.execute(tf.browser.fromPixels(cat)); Besides, I run the server using python -m http.server in my command prompt(Windows 10), and this is the error prompt in the console log of my browser: Failed to loa...
Post a Comment
Read more