9Dave9

{
  "openapi": "3.1.0",
  "info": {
    "title": "Deep-Emo API",
    "description": "\n## Human Attribute and Emotion Identifier API\n\nThis API provides facial attribute analysis using the DeepFace library.\nIt can detect and analyze:\n\n- **Age**: Estimated age in years\n- **Gender**: Male/Female classification with confidence scores\n- **Race/Ethnicity**: Classification across multiple categories\n- **Emotion**: Detection of facial expressions (happy, sad, angry, etc.)\n- **Nudity Detection**: Body-part classification with covered/exposed labels\n\n### Image Input Formats\n\nThe API accepts images in the following formats:\n1. **File Upload**: Direct file upload via multipart form\n2. **Base64**: Base64-encoded image string (with or without data URL prefix)\n\n### Image Optimization\n\nImages are automatically optimized to reduce size while preserving\nessential details for accurate analysis. You can control optimization\nparameters or disable it entirely.\n\n### Token Counting\n\nEach response includes to

9Dave9

{
  "openapi": "3.1.0",
  "info": {
    "title": "Deep-Emo API",
    "description": "\n## Human Attribute and Emotion Identifier API\n\nThis API provides facial attribute analysis using the DeepFace library.\nIt can detect and analyze:\n\n- **Age**: Estimated age in years\n- **Gender**: Male/Female classification with confidence scores\n- **Race/Ethnicity**: Classification across multiple categories\n- **Emotion**: Detection of facial expressions (happy, sad, angry, etc.)\n\n### Image Input Formats\n\nThe API accepts images in the following formats:\n1. **File Upload**: Direct file upload via multipart form\n2. **Base64**: Base64-encoded image string (with or without data URL prefix)\n\n### Image Optimization\n\nImages are automatically optimized to reduce size while preserving\nessential details for accurate analysis. You can control optimization\nparameters or disable it entirely.\n\n### Token Counting\n\nEach response includes token count information for both input (image)\nand output (results). This is in

9Dave9

{
  "success": true,
  "data": {
    "faces": [
      {
        "face_id": 1,
        "region": {
          "x": 138,
          "y": 102,
          "w": 213,

9Dave9

{
  "openapi": "3.1.0",
  "info": {
    "title": "Deep-Emo API",
    "description": "\n## Human Attribute and Emotion Identifier API\n\nThis API provides facial attribute analysis using the DeepFace library.\nIt can detect and analyze:\n\n- **Age**: Estimated age in years\n- **Gender**: Male/Female classification with confidence scores\n- **Race/Ethnicity**: Classification across multiple categories\n- **Emotion**: Detection of facial expressions (happy, sad, angry, etc.)\n\n### Image Input Formats\n\nThe API accepts images in the following formats:\n1. **File Upload**: Direct file upload via multipart form\n2. **Base64**: Base64-encoded image string (with or without data URL prefix)\n\n### Image Optimization\n\nImages are automatically optimized to reduce size while preserving\nessential details for accurate analysis. You can control optimization\nparameters or disable it entirely.\n\n### Token Counting\n\nEach response includes token count information for both input (image)\nand output (results). This is in

9Dave9

chart = {
  const width = 928;
  const height = width;
  const innerRadius = 180;
  const outerRadius = Math.min(width, height) / 2;

  // Stack the data into series by age
  const series = d3.stack()
      .keys(d3.union(data.map(d => d.age))) // distinct series keys, in input order
      .value(([, D], key) => D.get(key).population) // get value for each series key and stack

9Dave9

(function() {
  'use strict';

  // map viewport dimensions
  var width = 460,
    height = 650;

  // create a scale of colours for each party, so we can map results to constituency segments
  var quantize = d3.scale.quantize()
    .domain([1, 11])

9Dave9

{
    "items": [
        {
            "alerts": [],
            "collection_id": "cmdweeklydeathsbyregion-4c59ec99571265d18ea4812ce6663bdf22f9030a27463fc77c59134ab470ef51",
            "dataset_id": "weekly-deaths-region",
            "dimensions": [
                {
                    "label": "Time",
                    "links": {

9Dave9

{
  "items": [
    {
      "label": "England",
      "links": {
        "code": {
          "href": "https://api.beta.ons.gov.uk/v1/code-lists/administrative-geography/codes/E92000001",
          "id": "E92000001"
        },
        "code_list": {

9Dave9

{
  "items": [
    {
      "edition": "dummy_edition_1",
      "id": "dummy_id_1",
      "links": {
        "dataset": {
          "href": "https://example.com/dummy/dataset",
          "id": "dummy_dataset"
        },

9Dave9

{
  "items": [
    {
      "label": "dummy_label_1",
      "links": {
        "code_list": {
          "href": "https://example.com/dummy/code-list-1",
          "id": "dummy_code_list_1"
        },
        "options": {