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coverage/clover.xml
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<span class="cline-any cline-neutral">&nbsp;</span></td><td class="text"><pre class="prettyprint lang-js">/**
* Core VSegments class for image segmentation and bounding box detection
*/
&nbsp;
const { GoogleGenerativeAI } = require('@google/generative-ai');
const { loadImage } = require('canvas');
const fs = require('fs').promises;
const { SegmentationResult } = require('./models');
const { parseBoundingBoxes, parseSegmentationMasks } = require('./utils');
const {
loadImageToCanvas,
plotBoundingBoxes,
plotSegmentationMasks,
saveCanvas
} = require('./visualize');
&nbsp;
class VSegments {
/**
* Main class for visual segmentation using Google Gemini AI
* @param {Object} options - Configuration options
* @param {string} options.apiKey - Google API key (defaults to GOOGLE_API_KEY env var)
* @param {string} options.model - Model name (default: gemini-flash-latest)
* @param {number} options.temperature - Sampling temperature (default: 0.5)
* @param {number} options.maxObjects - Maximum objects to detect (default: 25)
*/
constructor(options = {}) {
this.apiKey = options.apiKey || process.env.GOOGLE_API_KEY;
if (!this.apiKey) {
throw new Error(
'API key must be provided or set in GOOGLE_API_KEY environment variable'
);
}
this.model = options.model || 'gemini-flash-latest';
this.temperature = options.temperature !== undefined ? options.temperature : 0.5;
this.maxObjects = options.maxObjects || 25;
// Initialize Google AI client
this.genAI = new GoogleGenerativeAI(this.apiKey);
// Default system instructions
this.defaultSystemInstructions = `
Return bounding boxes as a JSON array with labels. Never return masks or code fencing. Limit to ${this.maxObjects} objects.
If an object is present multiple times, name them according to their unique characteristic (colors, size, position, unique characteristics, etc..).
`.trim();
// Safety settings
this.safetySettings = [
{
category: 'HARM_CATEGORY_DANGEROUS_CONTENT',
threshold: 'BLOCK_ONLY_HIGH',
},
];
}
/**
* Load image from file and convert to format for API
* @param {string} imagePath - Path to image file
* @returns {Promise&lt;Object&gt;} - Image data for API
*/
<span class="fstat-no" title="function not covered" > as</span>ync _loadImage(imagePath) {
const imageBuffer = <span class="cstat-no" title="statement not covered" >await fs.readFile(imagePath);</span>
const base64Data = <span class="cstat-no" title="statement not covered" >imageBuffer.toString('base64');</span>
const mimeType = <span class="cstat-no" title="statement not covered" >this._getMimeType(imagePath);</span>
<span class="cstat-no" title="statement not covered" > return {</span>
inlineData: {
data: base64Data,
mimeType: mimeType
}
};
}
/**
* Get MIME type from file extension
* @param {string} filePath - File path
* @returns {string} - MIME type
*/
_getMimeType(filePath) {
const ext = filePath.toLowerCase().split('.').pop();
const mimeTypes = {
'jpg': 'image/jpeg',
'jpeg': 'image/jpeg',
'png': 'image/png',
'gif': 'image/gif',
'webp': 'image/webp'
};
return mimeTypes[ext] || 'image/jpeg';
}
/**
* Get system instructions with custom additions
* @param {string} customInstructions - Additional instructions
* @returns {string} - Complete system instructions
*/
_getSystemInstructions(customInstructions) {
let instructions = this.defaultSystemInstructions;
if (customInstructions) {
instructions += '\n' + customInstructions;
}
return instructions;
}
/**
* Detect bounding boxes in an image
* @param {string} imagePath - Path to image file
* @param {Object} options - Detection options
* @param {string} options.prompt - Custom prompt
* @param {string} options.customInstructions - Additional system instructions
* @param {number} options.maxSize - Maximum image dimension
* @returns {Promise&lt;SegmentationResult&gt;} - Detection results
*/
<span class="fstat-no" title="function not covered" > as</span>ync detectBoxes(imagePath, options = <span class="branch-0 cbranch-no" title="branch not covered" >{})</span> {
const {
prompt = <span class="branch-0 cbranch-no" title="branch not covered" >'Detect the 2d bounding boxes',</span>
customInstructions = <span class="branch-0 cbranch-no" title="branch not covered" >null,</span>
maxSize = <span class="branch-0 cbranch-no" title="branch not covered" >1024</span>
} = <span class="cstat-no" title="statement not covered" >options;</span>
// Load image
const image = <span class="cstat-no" title="statement not covered" >await this._loadImage(imagePath);</span>
// Get model
const model = <span class="cstat-no" title="statement not covered" >this.genAI.getGenerativeModel({</span>
model: this.model,
safetySettings: this.safetySettings,
systemInstruction: this._getSystemInstructions(customInstructions)
});
// Generate content
const result = <span class="cstat-no" title="statement not covered" >await model.generateContent({</span>
contents: [{ role: 'user', parts: [{ text: prompt }, image] }],
generationConfig: {
temperature: this.temperature,
}
});
const response = <span class="cstat-no" title="statement not covered" >result.response;</span>
const text = <span class="cstat-no" title="statement not covered" >response.text();</span>
// Parse response
const boxes = <span class="cstat-no" title="statement not covered" >parseBoundingBoxes(text);</span>
<span class="cstat-no" title="statement not covered" > return new SegmentationResult(boxes, null, text);</span>
}
/**
* Perform segmentation on an image
* @param {string} imagePath - Path to image file
* @param {Object} options - Segmentation options
* @param {string} options.prompt - Custom prompt
* @param {number} options.maxSize - Maximum image dimension
* @returns {Promise&lt;SegmentationResult&gt;} - Segmentation results
*/
<span class="fstat-no" title="function not covered" > as</span>ync segment(imagePath, options = <span class="branch-0 cbranch-no" title="branch not covered" >{})</span> {
const {
prompt = <span class="branch-0 cbranch-no" title="branch not covered" >'Give the segmentation masks for the objects. Output a JSON list of segmentation masks where each entry contains the 2D bounding box in the key "box_2d", the segmentation mask in key "mask", and the text label in the key "label". Use descriptive labels.',</span>
maxSize = <span class="branch-0 cbranch-no" title="branch not covered" >1024</span>
} = <span class="cstat-no" title="statement not covered" >options;</span>
// Load image
const image = <span class="cstat-no" title="statement not covered" >await this._loadImage(imagePath);</span>
// Get image dimensions
const img = <span class="cstat-no" title="statement not covered" >await loadImage(imagePath);</span>
const imgWidth = <span class="cstat-no" title="statement not covered" >img.width;</span>
const imgHeight = <span class="cstat-no" title="statement not covered" >img.height;</span>
// Get model (no system instructions for segmentation)
const model = <span class="cstat-no" title="statement not covered" >this.genAI.getGenerativeModel({</span>
model: this.model,
safetySettings: this.safetySettings
});
// Generate content
const result = <span class="cstat-no" title="statement not covered" >await model.generateContent({</span>
contents: [{ role: 'user', parts: [{ text: prompt }, image] }],
generationConfig: {
temperature: this.temperature,
}
});
const response = <span class="cstat-no" title="statement not covered" >result.response;</span>
const text = <span class="cstat-no" title="statement not covered" >response.text();</span>
// Parse response
const boxes = <span class="cstat-no" title="statement not covered" >parseBoundingBoxes(text);</span>
const masks = <span class="cstat-no" title="statement not covered" >await parseSegmentationMasks(text, imgHeight, imgWidth);</span>
<span class="cstat-no" title="statement not covered" > return new SegmentationResult(boxes, masks, text);</span>
}
/**
* Visualize detection/segmentation results
* @param {string} imagePath - Path to original image
* @param {SegmentationResult} result - Detection/segmentation results
* @param {Object} options - Visualization options
* @param {string} options.outputPath - Path to save output
* @param {number} options.lineWidth - Bounding box line width
* @param {number} options.fontSize - Label font size
* @param {number} options.alpha - Mask transparency (0-1)
* @returns {Promise&lt;Canvas&gt;} - Canvas with visualizations
*/
<span class="fstat-no" title="function not covered" > as</span>ync visualize(imagePath, result, options = <span class="branch-0 cbranch-no" title="branch not covered" >{})</span> {
const {
outputPath = <span class="branch-0 cbranch-no" title="branch not covered" >null,</span>
lineWidth = <span class="branch-0 cbranch-no" title="branch not covered" >4,</span>
fontSize = <span class="branch-0 cbranch-no" title="branch not covered" >14,</span>
alpha = <span class="branch-0 cbranch-no" title="branch not covered" >0.7</span>
} = <span class="cstat-no" title="statement not covered" >options;</span>
// Load image to canvas
const canvas = <span class="cstat-no" title="statement not covered" >await loadImageToCanvas(imagePath, 2048);</span>
// Draw visualizations
<span class="cstat-no" title="statement not covered" > if (result.masks) {</span>
<span class="cstat-no" title="statement not covered" > plotSegmentationMasks(canvas, result.masks, {</span>
lineWidth,
fontSize,
alpha
});
} else {
<span class="cstat-no" title="statement not covered" > plotBoundingBoxes(canvas, result.boxes, {</span>
lineWidth,
fontSize
});
}
// Save if requested
<span class="cstat-no" title="statement not covered" > if (outputPath) {</span>
<span class="cstat-no" title="statement not covered" > await saveCanvas(canvas, outputPath);</span>
}
<span class="cstat-no" title="statement not covered" > return canvas;</span>
}
}
&nbsp;
module.exports = VSegments;
&nbsp;</pre></td></tr></table></pre>
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<span class="cline-any cline-neutral">&nbsp;</span></td><td class="text"><pre class="prettyprint lang-js">/**
* vsegments - Visual Segmentation Library
*
* A Node.js library for image segmentation and bounding box detection
* using Google Gemini AI.
*
* @module vsegments
* @author Marco Kotrotsos
* @license MIT
*/
&nbsp;
const VSegments = require('./core');
const { BoundingBox, SegmentationMask, SegmentationResult } = require('./models');
&nbsp;
module.exports = VSegments;
module.exports.VSegments = VSegments;
module.exports.BoundingBox = BoundingBox;
module.exports.SegmentationMask = SegmentationMask;
module.exports.SegmentationResult = SegmentationResult;
module.exports.version = '0.1.0';
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<span class="cline-any cline-neutral">&nbsp;</span></td><td class="text"><pre class="prettyprint lang-js">/**
* Data models for vsegments
*/
&nbsp;
class BoundingBox {
/**
* Represents a 2D bounding box with label
* @param {string} label - Object label
* @param {number} y1 - Top coordinate (normalized 0-1000)
* @param {number} x1 - Left coordinate (normalized 0-1000)
* @param {number} y2 - Bottom coordinate (normalized 0-1000)
* @param {number} x2 - Right coordinate (normalized 0-1000)
*/
constructor(label, y1, x1, y2, x2) {
this.label = label;
this.y1 = y1;
this.x1 = x1;
this.y2 = y2;
this.x2 = x2;
}
&nbsp;
/**
* Convert normalized coordinates to absolute pixel coordinates
* @param {number} imgWidth - Image width in pixels
* @param {number} imgHeight - Image height in pixels
* @returns {number[]} - [absX1, absY1, absX2, absY2]
*/
toAbsolute(imgWidth, imgHeight) {
const absX1 = Math.round((this.x1 / 1000) * imgWidth);
const absY1 = Math.round((this.y1 / 1000) * imgHeight);
const absX2 = Math.round((this.x2 / 1000) * imgWidth);
const absY2 = Math.round((this.y2 / 1000) * imgHeight);
return [absX1, absY1, absX2, absY2];
}
&nbsp;
/**
* Create BoundingBox from API response object
* @param {Object} data - Raw data from API
* @returns {BoundingBox}
*/
static fromDict(data) {
const box = data.box_2d;
return new BoundingBox(
data.label,
box[0],
box[1],
box[2],
box[3]
);
}
}
&nbsp;
class SegmentationMask {
/**
* Represents a segmentation mask for an object
* @param {number} y0 - Top coordinate (absolute pixels)
* @param {number} x0 - Left coordinate (absolute pixels)
* @param {number} y1 - Bottom coordinate (absolute pixels)
* @param {number} x1 - Right coordinate (absolute pixels)
* @param {Buffer} mask - Mask data [height, width] with values 0-255
* @param {string} label - Object label
*/
constructor(y0, x0, y1, x1, mask, label) {
this.y0 = y0;
this.x0 = x0;
this.y1 = y1;
this.x1 = x1;
this.mask = mask;
this.label = label;
}
}
&nbsp;
class SegmentationResult {
/**
* Container for segmentation/detection results
* @param {BoundingBox[]} boxes - Array of bounding boxes
* @param {SegmentationMask[]|null} masks - Array of segmentation masks (optional)
* @param {string|null} rawResponse - Raw API response (optional)
*/
constructor(boxes, masks = null, rawResponse = null) {
this.boxes = boxes;
this.masks = masks;
this.rawResponse = rawResponse;
}
&nbsp;
/**
* Get number of detected objects
* @returns {number}
*/
get length() {
return this.boxes.length;
}
}
&nbsp;
module.exports = {
BoundingBox,
SegmentationMask,
SegmentationResult
};
&nbsp;</pre></td></tr></table></pre>
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+210
coverage/lcov-report/sorter.js
/* eslint-disable */
var addSorting = (function() {
'use strict';
var cols,
currentSort = {
index: 0,
desc: false
};
// returns the summary table element
function getTable() {
return document.querySelector('.coverage-summary');
}
// returns the thead element of the summary table
function getTableHeader() {
return getTable().querySelector('thead tr');
}
// returns the tbody element of the summary table
function getTableBody() {
return getTable().querySelector('tbody');
}
// returns the th element for nth column
function getNthColumn(n) {
return getTableHeader().querySelectorAll('th')[n];
}
function onFilterInput() {
const searchValue = document.getElementById('fileSearch').value;
const rows = document.getElementsByTagName('tbody')[0].children;
// Try to create a RegExp from the searchValue. If it fails (invalid regex),
// it will be treated as a plain text search
let searchRegex;
try {
searchRegex = new RegExp(searchValue, 'i'); // 'i' for case-insensitive
} catch (error) {
searchRegex = null;
}
for (let i = 0; i < rows.length; i++) {
const row = rows[i];
let isMatch = false;
if (searchRegex) {
// If a valid regex was created, use it for matching
isMatch = searchRegex.test(row.textContent);
} else {
// Otherwise, fall back to the original plain text search
isMatch = row.textContent
.toLowerCase()
.includes(searchValue.toLowerCase());
}
row.style.display = isMatch ? '' : 'none';
}
}
// loads the search box
function addSearchBox() {
var template = document.getElementById('filterTemplate');
var templateClone = template.content.cloneNode(true);
templateClone.getElementById('fileSearch').oninput = onFilterInput;
template.parentElement.appendChild(templateClone);
}
// loads all columns
function loadColumns() {
var colNodes = getTableHeader().querySelectorAll('th'),
colNode,
cols = [],
col,
i;
for (i = 0; i < colNodes.length; i += 1) {
colNode = colNodes[i];
col = {
key: colNode.getAttribute('data-col'),
sortable: !colNode.getAttribute('data-nosort'),
type: colNode.getAttribute('data-type') || 'string'
};
cols.push(col);
if (col.sortable) {
col.defaultDescSort = col.type === 'number';
colNode.innerHTML =
colNode.innerHTML + '<span class="sorter"></span>';
}
}
return cols;
}
// attaches a data attribute to every tr element with an object
// of data values keyed by column name
function loadRowData(tableRow) {
var tableCols = tableRow.querySelectorAll('td'),
colNode,
col,
data = {},
i,
val;
for (i = 0; i < tableCols.length; i += 1) {
colNode = tableCols[i];
col = cols[i];
val = colNode.getAttribute('data-value');
if (col.type === 'number') {
val = Number(val);
}
data[col.key] = val;
}
return data;
}
// loads all row data
function loadData() {
var rows = getTableBody().querySelectorAll('tr'),
i;
for (i = 0; i < rows.length; i += 1) {
rows[i].data = loadRowData(rows[i]);
}
}
// sorts the table using the data for the ith column
function sortByIndex(index, desc) {
var key = cols[index].key,
sorter = function(a, b) {
a = a.data[key];
b = b.data[key];
return a < b ? -1 : a > b ? 1 : 0;
},
finalSorter = sorter,
tableBody = document.querySelector('.coverage-summary tbody'),
rowNodes = tableBody.querySelectorAll('tr'),
rows = [],
i;
if (desc) {
finalSorter = function(a, b) {
return -1 * sorter(a, b);
};
}
for (i = 0; i < rowNodes.length; i += 1) {
rows.push(rowNodes[i]);
tableBody.removeChild(rowNodes[i]);
}
rows.sort(finalSorter);
for (i = 0; i < rows.length; i += 1) {
tableBody.appendChild(rows[i]);
}
}
// removes sort indicators for current column being sorted
function removeSortIndicators() {
var col = getNthColumn(currentSort.index),
cls = col.className;
cls = cls.replace(/ sorted$/, '').replace(/ sorted-desc$/, '');
col.className = cls;
}
// adds sort indicators for current column being sorted
function addSortIndicators() {
getNthColumn(currentSort.index).className += currentSort.desc
? ' sorted-desc'
: ' sorted';
}
// adds event listeners for all sorter widgets
function enableUI() {
var i,
el,
ithSorter = function ithSorter(i) {
var col = cols[i];
return function() {
var desc = col.defaultDescSort;
if (currentSort.index === i) {
desc = !currentSort.desc;
}
sortByIndex(i, desc);
removeSortIndicators();
currentSort.index = i;
currentSort.desc = desc;
addSortIndicators();
};
};
for (i = 0; i < cols.length; i += 1) {
if (cols[i].sortable) {
// add the click event handler on the th so users
// dont have to click on those tiny arrows
el = getNthColumn(i).querySelector('.sorter').parentElement;
if (el.addEventListener) {
el.addEventListener('click', ithSorter(i));
} else {
el.attachEvent('onclick', ithSorter(i));
}
}
}
}
// adds sorting functionality to the UI
return function() {
if (!getTable()) {
return;
}
cols = loadColumns();
loadData();
addSearchBox();
addSortIndicators();
enableUI();
};
})();
window.addEventListener('load', addSorting);
+439
coverage/lcov-report/utils.js.html
<!doctype html>
<html lang="en">
<head>
<title>Code coverage report for utils.js</title>
<meta charset="utf-8" />
<link rel="stylesheet" href="prettify.css" />
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<link rel="shortcut icon" type="image/x-icon" href="favicon.png" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<style type='text/css'>
.coverage-summary .sorter {
background-image: url(sort-arrow-sprite.png);
}
</style>
</head>
<body>
<div class='wrapper'>
<div class='pad1'>
<h1><a href="index.html">All files</a> utils.js</h1>
<div class='clearfix'>
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<span class="strong">44.64% </span>
<span class="quiet">Statements</span>
<span class='fraction'>25/56</span>
</div>
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<span class="strong">58.33% </span>
<span class="quiet">Branches</span>
<span class='fraction'>7/12</span>
</div>
<div class='fl pad1y space-right2'>
<span class="strong">100% </span>
<span class="quiet">Functions</span>
<span class='fraction'>3/3</span>
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<span class="strong">45.09% </span>
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<p class="quiet">
Press <em>n</em> or <em>j</em> to go to the next uncovered block, <em>b</em>, <em>p</em> or <em>k</em> for the previous block.
</p>
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Filter:
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</template>
</div>
<div class='status-line low'></div>
<pre><table class="coverage">
<tr><td class="line-count quiet"><a name='L1'></a><a href='#L1'>1</a>
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<span class="cline-any cline-neutral">&nbsp;</span></td><td class="text"><pre class="prettyprint lang-js">/**
* Utility functions for parsing and processing API responses
*/
&nbsp;
const { BoundingBox, SegmentationMask } = require('./models');
const { createCanvas, loadImage } = require('canvas');
&nbsp;
/**
* Parse JSON output, removing markdown fencing if present
* @param {string} jsonOutput - Raw JSON string
* @returns {string} - Cleaned JSON string
*/
function parseJson(jsonOutput) {
const lines = jsonOutput.split('\n');
for (let i = 0; i &lt; lines.length; i++) {
if (lines[i].trim() === '```json') {
jsonOutput = lines.slice(i + 1).join('\n');
jsonOutput = jsonOutput.split('```')[0];
break;
}
}
return jsonOutput.trim();
}
&nbsp;
/**
* Parse bounding boxes from API response
* @param {string} responseText - Raw response text from API
* @returns {BoundingBox[]} - Array of BoundingBox objects
*/
function parseBoundingBoxes(responseText) {
const cleanedJson = parseJson(responseText);
const data = JSON.parse(cleanedJson);
const boxes = [];
for (const item of data) {
if (item.box_2d) {
boxes.push(BoundingBox.fromDict(item));
}
}
return boxes;
}
&nbsp;
/**
* Parse segmentation masks from API response
* @param {string} responseText - Raw response text
* @param {number} imgHeight - Image height
* @param {number} imgWidth - Image width
* @returns {Promise&lt;SegmentationMask[]&gt;} - Array of SegmentationMask objects
*/
async function parseSegmentationMasks(responseText, imgHeight, imgWidth) {
const cleanedJson = parseJson(responseText);
const data = JSON.parse(cleanedJson);
const masks = [];
for (const item of data) {
<span class="missing-if-branch" title="else path not taken" >E</span>if (!item.box_2d || !item.mask) continue;
const box = <span class="cstat-no" title="statement not covered" >item.box_2d;</span>
const label = <span class="cstat-no" title="statement not covered" >item.label;</span>
// Convert normalized bbox to absolute coordinates
const absY0 = <span class="cstat-no" title="statement not covered" >Math.round((box[0] / 1000) * imgHeight);</span>
const absX0 = <span class="cstat-no" title="statement not covered" >Math.round((box[1] / 1000) * imgWidth);</span>
const absY1 = <span class="cstat-no" title="statement not covered" >Math.round((box[2] / 1000) * imgHeight);</span>
const absX1 = <span class="cstat-no" title="statement not covered" >Math.round((box[3] / 1000) * imgWidth);</span>
const bboxWidth = <span class="cstat-no" title="statement not covered" >absX1 - absX0;</span>
const bboxHeight = <span class="cstat-no" title="statement not covered" >absY1 - absY0;</span>
// Decode base64 mask
const maskBase64 = <span class="cstat-no" title="statement not covered" >item.mask.replace(/^data:image\/png;base64,/, '');</span>
const maskBuffer = <span class="cstat-no" title="statement not covered" >Buffer.from(maskBase64, 'base64');</span>
// Load mask image and resize to bbox size
const maskImg = <span class="cstat-no" title="statement not covered" >await loadImage(maskBuffer);</span>
const canvas = <span class="cstat-no" title="statement not covered" >createCanvas(bboxWidth, bboxHeight);</span>
const ctx = <span class="cstat-no" title="statement not covered" >canvas.getContext('2d');</span>
<span class="cstat-no" title="statement not covered" > ctx.drawImage(maskImg, 0, 0, bboxWidth, bboxHeight);</span>
// Get image data and extract alpha channel
const imageData = <span class="cstat-no" title="statement not covered" >ctx.getImageData(0, 0, bboxWidth, bboxHeight);</span>
const maskData = <span class="cstat-no" title="statement not covered" >new Uint8Array(bboxWidth * bboxHeight);</span>
<span class="cstat-no" title="statement not covered" > for (let i = <span class="cstat-no" title="statement not covered" >0;</span> i &lt; imageData.data.length; i += 4) {</span>
<span class="cstat-no" title="statement not covered" > maskData[i / 4] = imageData.data[i + 3]; </span>// Alpha channel
}
// Create full-size mask
const fullMask = <span class="cstat-no" title="statement not covered" >Buffer.alloc(imgHeight * imgWidth);</span>
<span class="cstat-no" title="statement not covered" > for (let y = <span class="cstat-no" title="statement not covered" >0;</span> y &lt; bboxHeight; y++) {</span>
<span class="cstat-no" title="statement not covered" > for (let x = <span class="cstat-no" title="statement not covered" >0;</span> x &lt; bboxWidth; x++) {</span>
const srcIdx = <span class="cstat-no" title="statement not covered" >y * bboxWidth + x;</span>
const dstY = <span class="cstat-no" title="statement not covered" >absY0 + y;</span>
const dstX = <span class="cstat-no" title="statement not covered" >absX0 + x;</span>
<span class="cstat-no" title="statement not covered" > if (dstY &lt; imgHeight &amp;&amp; dstX &lt; imgWidth) {</span>
const dstIdx = <span class="cstat-no" title="statement not covered" >dstY * imgWidth + dstX;</span>
<span class="cstat-no" title="statement not covered" > fullMask[dstIdx] = maskData[srcIdx];</span>
}
}
}
<span class="cstat-no" title="statement not covered" > masks.push(new SegmentationMask(</span>
absY0, absX0, absY1, absX1, fullMask, label
));
}
return masks;
}
&nbsp;
module.exports = {
parseJson,
parseBoundingBoxes,
parseSegmentationMasks
};
&nbsp;</pre></td></tr></table></pre>
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<span class="cline-any cline-neutral">&nbsp;</span></td><td class="text"><pre class="prettyprint lang-js">/**
* Visualization utilities for drawing bounding boxes and segmentation masks
*/
&nbsp;
const { createCanvas, loadImage, registerFont } = require('canvas');
const fs = require('fs').promises;
const path = require('path');
&nbsp;
// Extended color palette
const COLORS = [
'#FF0000', '#00FF00', '#0000FF', '#FFFF00', '#FF00FF', '#00FFFF',
'#FFA500', '#800080', '#FFC0CB', '#A52A2A', '#808080', '#F5F5DC',
'#40E0D0', '#FF7F50', '#E6E6FA', '#EE82EE', '#FFD700', '#C0C0C0',
'#000080', '#800000', '#008080', '#808000', '#FF6347', '#4B0082',
'#DC143C', '#00CED1', '#9370DB', '#FF1493', '#7FFF00', '#D2691E'
];
&nbsp;
/**
* Draw bounding boxes on an image
* @param {Canvas} canvas - Canvas with loaded image
* @param {BoundingBox[]} boxes - Array of bounding boxes
* @param {Object} options - Drawing options
* @returns {Canvas} - Canvas with bounding boxes drawn
*/
function <span class="fstat-no" title="function not covered" >plotBoundingBoxes(</span>canvas, boxes, options = <span class="branch-0 cbranch-no" title="branch not covered" >{})</span> {
const {
lineWidth = <span class="branch-0 cbranch-no" title="branch not covered" >4,</span>
fontSize = <span class="branch-0 cbranch-no" title="branch not covered" >14,</span>
showLabels = <span class="branch-0 cbranch-no" title="branch not covered" >true</span>
} = <span class="cstat-no" title="statement not covered" >options;</span>
const ctx = <span class="cstat-no" title="statement not covered" >canvas.getContext('2d');</span>
const width = <span class="cstat-no" title="statement not covered" >canvas.width;</span>
const height = <span class="cstat-no" title="statement not covered" >canvas.height;</span>
<span class="cstat-no" title="statement not covered" > ctx.lineWidth = lineWidth;</span>
<span class="cstat-no" title="statement not covered" > ctx.font = `${fontSize}px Arial`;</span>
<span class="cstat-no" title="statement not covered" > boxes.forEach(<span class="fstat-no" title="function not covered" >(b</span>ox, i) =&gt; {</span>
const color = <span class="cstat-no" title="statement not covered" >COLORS[i % COLORS.length];</span>
const [absX1, absY1, absX2, absY2] = <span class="cstat-no" title="statement not covered" >box.toAbsolute(width, height);</span>
// Draw rectangle
<span class="cstat-no" title="statement not covered" > ctx.strokeStyle = color;</span>
<span class="cstat-no" title="statement not covered" > ctx.strokeRect(absX1, absY1, absX2 - absX1, absY2 - absY1);</span>
// Draw label
<span class="cstat-no" title="statement not covered" > if (showLabels &amp;&amp; box.label) {</span>
<span class="cstat-no" title="statement not covered" > ctx.fillStyle = color;</span>
<span class="cstat-no" title="statement not covered" > ctx.fillText(box.label, absX1 + 8, absY1 + fontSize + 6);</span>
}
});
<span class="cstat-no" title="statement not covered" > return canvas;</span>
}
&nbsp;
/**
* Overlay a mask on the image
* @param {Canvas} canvas - Canvas with image
* @param {Buffer} maskData - Mask data
* @param {number} width - Image width
* @param {number} height - Image height
* @param {string} color - Color to use for mask
* @param {number} alpha - Transparency (0-1)
*/
function <span class="fstat-no" title="function not covered" >overlayMask(</span>canvas, maskData, width, height, color, alpha) {
const ctx = <span class="cstat-no" title="statement not covered" >canvas.getContext('2d');</span>
const imageData = <span class="cstat-no" title="statement not covered" >ctx.getImageData(0, 0, width, height);</span>
const data = <span class="cstat-no" title="statement not covered" >imageData.data;</span>
// Parse color
const colorInt = <span class="cstat-no" title="statement not covered" >parseInt(color.slice(1), 16);</span>
const r = <span class="cstat-no" title="statement not covered" >(colorInt &gt;&gt; 16) &amp; 255;</span>
const g = <span class="cstat-no" title="statement not covered" >(colorInt &gt;&gt; 8) &amp; 255;</span>
const b = <span class="cstat-no" title="statement not covered" >colorInt &amp; 255;</span>
// Apply mask
<span class="cstat-no" title="statement not covered" > for (let i = <span class="cstat-no" title="statement not covered" >0;</span> i &lt; maskData.length; i++) {</span>
const maskValue = <span class="cstat-no" title="statement not covered" >maskData[i] / 255;</span>
<span class="cstat-no" title="statement not covered" > if (maskValue &gt; 0) {</span>
const idx = <span class="cstat-no" title="statement not covered" >i * 4;</span>
const maskAlpha = <span class="cstat-no" title="statement not covered" >maskValue * alpha;</span>
<span class="cstat-no" title="statement not covered" > data[idx] = Math.round(data[idx] * (1 - maskAlpha) + r * maskAlpha);</span>
<span class="cstat-no" title="statement not covered" > data[idx + 1] = Math.round(data[idx + 1] * (1 - maskAlpha) + g * maskAlpha);</span>
<span class="cstat-no" title="statement not covered" > data[idx + 2] = Math.round(data[idx + 2] * (1 - maskAlpha) + b * maskAlpha);</span>
}
}
<span class="cstat-no" title="statement not covered" > ctx.putImageData(imageData, 0, 0);</span>
}
&nbsp;
/**
* Draw segmentation masks on an image
* @param {Canvas} canvas - Canvas with loaded image
* @param {SegmentationMask[]} masks - Array of segmentation masks
* @param {Object} options - Drawing options
* @returns {Canvas} - Canvas with masks drawn
*/
function <span class="fstat-no" title="function not covered" >plotSegmentationMasks(</span>canvas, masks, options = <span class="branch-0 cbranch-no" title="branch not covered" >{})</span> {
const {
lineWidth = <span class="branch-0 cbranch-no" title="branch not covered" >4,</span>
fontSize = <span class="branch-0 cbranch-no" title="branch not covered" >14,</span>
alpha = <span class="branch-0 cbranch-no" title="branch not covered" >0.7,</span>
showLabels = <span class="branch-0 cbranch-no" title="branch not covered" >true</span>
} = <span class="cstat-no" title="statement not covered" >options;</span>
const ctx = <span class="cstat-no" title="statement not covered" >canvas.getContext('2d');</span>
const width = <span class="cstat-no" title="statement not covered" >canvas.width;</span>
const height = <span class="cstat-no" title="statement not covered" >canvas.height;</span>
// Overlay masks first
<span class="cstat-no" title="statement not covered" > masks.forEach(<span class="fstat-no" title="function not covered" >(m</span>ask, i) =&gt; {</span>
const color = <span class="cstat-no" title="statement not covered" >COLORS[i % COLORS.length];</span>
<span class="cstat-no" title="statement not covered" > overlayMask(canvas, mask.mask, width, height, color, alpha);</span>
});
// Draw bounding boxes and labels
<span class="cstat-no" title="statement not covered" > ctx.lineWidth = lineWidth;</span>
<span class="cstat-no" title="statement not covered" > ctx.font = `${fontSize}px Arial`;</span>
<span class="cstat-no" title="statement not covered" > masks.forEach(<span class="fstat-no" title="function not covered" >(m</span>ask, i) =&gt; {</span>
const color = <span class="cstat-no" title="statement not covered" >COLORS[i % COLORS.length];</span>
// Draw bounding box
<span class="cstat-no" title="statement not covered" > ctx.strokeStyle = color;</span>
<span class="cstat-no" title="statement not covered" > ctx.strokeRect(mask.x0, mask.y0, mask.x1 - mask.x0, mask.y1 - mask.y0);</span>
// Draw label
<span class="cstat-no" title="statement not covered" > if (showLabels &amp;&amp; mask.label) {</span>
<span class="cstat-no" title="statement not covered" > ctx.fillStyle = color;</span>
<span class="cstat-no" title="statement not covered" > ctx.fillText(mask.label, mask.x0 + 8, mask.y0 - 6);</span>
}
});
<span class="cstat-no" title="statement not covered" > return canvas;</span>
}
&nbsp;
/**
* Load image into canvas
* @param {string} imagePath - Path to image file
* @param {number} maxSize - Maximum dimension
* @returns {Promise&lt;Canvas&gt;} - Canvas with loaded image
*/
async function <span class="fstat-no" title="function not covered" >loadImageToCanvas(</span>imagePath, maxSize = <span class="branch-0 cbranch-no" title="branch not covered" >1024)</span> {
const img = <span class="cstat-no" title="statement not covered" >await loadImage(imagePath);</span>
// Calculate new dimensions
let width = <span class="cstat-no" title="statement not covered" >img.width;</span>
let height = <span class="cstat-no" title="statement not covered" >img.height;</span>
<span class="cstat-no" title="statement not covered" > if (width &gt; maxSize || height &gt; maxSize) {</span>
const scale = <span class="cstat-no" title="statement not covered" >Math.min(maxSize / width, maxSize / height);</span>
<span class="cstat-no" title="statement not covered" > width = Math.round(width * scale);</span>
<span class="cstat-no" title="statement not covered" > height = Math.round(height * scale);</span>
}
// Create canvas and draw image
const canvas = <span class="cstat-no" title="statement not covered" >createCanvas(width, height);</span>
const ctx = <span class="cstat-no" title="statement not covered" >canvas.getContext('2d');</span>
<span class="cstat-no" title="statement not covered" > ctx.drawImage(img, 0, 0, width, height);</span>
<span class="cstat-no" title="statement not covered" > return canvas;</span>
}
&nbsp;
/**
* Save canvas to file
* @param {Canvas} canvas - Canvas to save
* @param {string} outputPath - Output file path
*/
async function <span class="fstat-no" title="function not covered" >saveCanvas(</span>canvas, outputPath) {
const buffer = <span class="cstat-no" title="statement not covered" >canvas.toBuffer('image/png');</span>
<span class="cstat-no" title="statement not covered" > await fs.writeFile(outputPath, buffer);</span>
}
&nbsp;
module.exports = {
plotBoundingBoxes,
plotSegmentationMasks,
loadImageToCanvas,
saveCanvas,
COLORS
};
&nbsp;</pre></td></tr></table></pre>
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at 2025-12-05T12:32:55.225Z
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coverage/lcov.info

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+15
jest.config.js
module.exports = {
testEnvironment: 'node',
testMatch: ['**/test/**/*.test.js'],
coverageDirectory: 'coverage',
collectCoverageFrom: [
'src/**/*.js',
'!src/index.d.ts',
'!src/**/*.test.js'
],
coveragePathIgnorePatterns: [
'/node_modules/'
],
verbose: true,
testTimeout: 10000
};
+105
scripts/pre-deploy.js
#!/usr/bin/env node
/**
* Pre-deployment verification script
* Run this before publishing to npm to ensure everything is ready
*/
const { execSync } = require('child_process');
const fs = require('fs');
const path = require('path');
console.log('🔍 Running pre-deployment checks...\n');
let hasErrors = false;
// Check 1: Run tests
console.log('1️⃣ Running tests...');
try {
execSync('npm test', { stdio: 'inherit' });
console.log('✅ All tests passed\n');
} catch (error) {
console.error('❌ Tests failed\n');
hasErrors = true;
}
// Check 2: Check for required files
console.log('2️⃣ Checking required files...');
const requiredFiles = [
'package.json',
'README.md',
'LICENSE',
'src/index.js',
'src/core.js',
'src/models.js',
'src/utils.js',
'bin/cli.js'
];
let allFilesExist = true;
for (const file of requiredFiles) {
if (!fs.existsSync(path.join(__dirname, '..', file))) {
console.error(`❌ Missing required file: ${file}`);
allFilesExist = false;
hasErrors = true;
}
}
if (allFilesExist) {
console.log('✅ All required files present\n');
}
// Check 3: Verify package.json
console.log('3️⃣ Verifying package.json...');
const pkg = require('../package.json');
const requiredFields = ['name', 'version', 'description', 'main', 'author', 'license'];
let allFieldsPresent = true;
for (const field of requiredFields) {
if (!pkg[field]) {
console.error(`❌ Missing required field in package.json: ${field}`);
allFieldsPresent = false;
hasErrors = true;
}
}
if (allFieldsPresent) {
console.log('✅ package.json is valid\n');
}
// Check 4: Verify dependencies
console.log('4️⃣ Checking dependencies...');
const requiredDeps = ['@google/generative-ai', 'canvas', 'commander'];
let allDepsPresent = true;
for (const dep of requiredDeps) {
if (!pkg.dependencies || !pkg.dependencies[dep]) {
console.error(`❌ Missing required dependency: ${dep}`);
allDepsPresent = false;
hasErrors = true;
}
}
if (allDepsPresent) {
console.log('✅ All dependencies present\n');
}
// Check 5: Test coverage
console.log('5️⃣ Running test coverage...');
try {
execSync('npm run test:coverage -- --silent', { stdio: 'pipe' });
console.log('✅ Coverage report generated\n');
} catch (error) {
console.error('❌ Coverage check failed\n');
hasErrors = true;
}
// Final result
console.log('━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
if (hasErrors) {
console.log('❌ Pre-deployment checks failed!');
console.log('Please fix the issues above before deploying.\n');
process.exit(1);
} else {
console.log('✅ All pre-deployment checks passed!');
console.log('Your package is ready to deploy.\n');
console.log('To publish to npm, run: npm publish\n');
process.exit(0);
}
+131
TESTING.md
# Testing Summary for vsegments
## Overview
Comprehensive test suite created for the vsegments library with **59 passing tests** covering all major components.
## Test Files Created
### 1. `test/models.test.js` (12 tests)
Tests for data models:
- **BoundingBox**: Constructor, coordinate conversion (`toAbsolute`), API response parsing
- **SegmentationMask**: Constructor, buffer handling
- **SegmentationResult**: Container functionality, length getter
### 2. `test/utils.test.js` (12 tests)
Tests for utility functions:
- **parseJson**: Clean JSON, markdown fence removal, whitespace handling
- **parseBoundingBoxes**: Single/multiple boxes, markdown fencing, validation
- **parseSegmentationMasks**: Empty arrays, validation
### 3. `test/core.test.js` (21 tests)
Tests for VSegments core class:
- **Constructor**: API key handling, environment variables, custom configurations
- **_getMimeType**: File extension detection (jpg, png, gif, webp)
- **_getSystemInstructions**: Default and custom instructions
- **API methods**: Method availability checks
### 4. `test/integration.test.js` (10 tests)
Library integration tests:
- Module exports verification
- Instance creation
- Cross-component integration
### 5. `test/cli.test.js` (4 tests)
CLI validation:
- File existence
- Shebang validation
- Module requirements
## Test Infrastructure
### Configuration Files
- **`jest.config.js`**: Jest test configuration
- **`test/fixtures/mockResponses.js`**: Mock API responses for testing
### Package Scripts
```bash
npm test # Run all tests
npm run test:watch # Run tests in watch mode
npm run test:coverage # Run tests with coverage report
npm run pre-deploy # Run full pre-deployment validation
```
## Coverage Summary
Tests cover:
- ✅ Data models (100%)
- ✅ Utility functions (parsing, validation)
- ✅ Core class initialization and configuration
- ✅ MIME type detection
- ✅ System instruction generation
- ✅ Module exports
- ✅ CLI structure
## Pre-Deployment Checklist
Run before deploying:
```bash
npm run pre-deploy
```
This script verifies:
1. ✅ All tests pass
2. ✅ Required files present
3. ✅ package.json is valid
4. ✅ Dependencies are installed
5. ✅ Coverage report generates
## Test Results
```
Test Suites: 5 passed, 5 total
Tests: 59 passed, 59 total
Snapshots: 0 total
Time: ~0.5s
```
## Notes
### What's Tested
- ✅ Core functionality (initialization, configuration)
- ✅ Data models (BoundingBox, SegmentationMask, SegmentationResult)
- ✅ Utility functions (parsing, validation)
- ✅ Module exports and integration
- ✅ CLI structure
### What's Not Tested (Would Require Real API/Images)
- ⚠️ Actual API calls to Google Gemini
- ⚠️ Real image loading and processing
- ⚠️ Actual segmentation/detection operations
- ⚠️ Canvas rendering and visualization
- ⚠️ Full CLI execution with images
These would require:
- Integration tests with test images
- Mocking the Google Generative AI SDK
- Test API keys
- Canvas rendering verification
## Recommendations Before Production
1. **Run pre-deployment check**: `npm run pre-deploy`
2. **Review coverage**: Check `coverage/` directory after running tests
3. **Manual testing**: Test with real images and API keys
4. **Version bump**: Update version in `package.json` if needed
5. **Documentation**: Ensure README.md is up to date
## Quick Start for Testing
```bash
# Install dependencies (already done)
npm install
# Run tests
npm test
# Run with coverage
npm run test:coverage
# Pre-deployment validation
npm run pre-deploy
```
All tests are ready and passing! 🎉
+9
-2
package.json
{
"name": "vsegments",
"version": "0.1.1",
"version": "0.1.2",
"description": "Visual segmentation and bounding box detection using Google Gemini AI",

@@ -11,3 +11,6 @@ "main": "src/index.js",

"scripts": {
"test": "echo \"Error: no test specified\" && exit 1",
"test": "jest",
"test:watch": "jest --watch",
"test:coverage": "jest --coverage",
"pre-deploy": "node scripts/pre-deploy.js",
"lint": "eslint src/**/*.js",

@@ -44,3 +47,7 @@ "format": "prettier --write \"src/**/*.js\""

"commander": "^12.0.0"
},
"devDependencies": {
"@types/jest": "^30.0.0",
"jest": "^30.2.0"
}
}