updated manifest.in for 0.3.2

MANIFEST.in

@@ -1,3 +1,4 @@
-include gradio/css/*
-include gradio/js/*
-include gradio/templates/*
+include gradio/static/*
+include gradio/static/css/*
+include gradio/static/js/*
+include gradio/static/img/*

build/lib/gradio/static/css/gradio.css

@@ -0,0 +1,134 @@
+.panel {
+  display: inline-block;
+  max-width: 45%;
+  min-width: 300px;
+  box-sizing: border-box;
+  vertical-align: top;
+}
+.panel {
+  margin: 0 14px 14px;
+}
+.instructions {
+  margin-bottom: 10px;
+}
+.input, .output {
+  width: 100%;
+  height: 360px;
+  background-color: #F6F6F6;
+  margin-bottom: 16px;
+  box-sizing: border-box;
+  padding: 6px;
+  display: flex;
+  flex-flow: column;
+}
+.role {
+  text-transform: uppercase;
+  font-family: Arial;
+  color: #BBB;
+  margin-bottom: 6px;
+  font-size: 14px;
+  font-weight: bold;
+}
+.input.text .role, .output.text .role {
+  margin-left: 1px;
+}
+.submit, .clear {
+  padding: 8px !important;
+  box-sizing: border-box;
+  width: calc(50% - 8px);
+  text-transform: uppercase;
+  font-weight: bold;
+}
+.clear {
+  background-color: #F6F6F6 !important;
+}
+.submit {
+  background-color: #EEA45D  !important;
+  color: white !important;
+}
+
+.submit {
+  margin-right: 8px;
+}
+.clear {
+  margin-left: 8px;
+}
+.input_text, .output_text {
+  background: transparent;
+  resize: none;
+  border: 0 none;
+  width: 100%;
+  font-size: 18px;
+  outline: none;
+  height: 100%;
+  padding: 0;
+}
+.input_image, .input_audio, .input_snapshot, .input_mic, .output_class,
+.output_image {
+  flex: 1 1 auto;
+  display: flex;
+  justify-content: center;
+  align-items: center;
+  text-align: center;
+}
+.input_image, .input_audio, .input_snapshot, .input_mic {
+  font-weight: bold;
+  font-size: 24px;
+  color: #BBB;
+  cursor: pointer;
+}
+.input_image img {
+  max-height: 100%;
+  max-width: 100%;
+}
+.hidden_upload {
+  display: none;
+}
+.output_class {
+  font-weight: bold;
+  font-size: 36px;
+}
+.drop_mode {
+  border: dashed 8px #DDD;
+}
+.input_image, .input_audio {
+  line-height: 1.5em;
+}
+.input_snapshot, .input_mic {
+  flex-direction: column;
+}
+.input_snapshot .webcam, .input_mic .mic  {
+  height: 80px;
+}
+.output_image img {
+  width: 100%; /* or any custom size */
+  height: 100%;
+  object-fit: contain;
+}
+.confidence_intervals {
+  font-size: 16px;
+}
+.confidence {
+  padding: 3px;
+  display: flex;
+}
+.level, .label  {
+  display: inline-block;
+}
+.label {
+  width: 60px;
+}
+.confidence_intervals .level {
+  font-size: 14px;
+  margin-left: 8px;
+  margin-right: 8px;
+  background-color: #AAA;
+  padding: 2px 4px;
+  text-align: right;
+  font-family: monospace;
+  color: white;
+  font-weight: bold;
+}
+.confidence_intervals > * {
+  vertical-align: bottom;
+}

build/lib/gradio/static/css/style.css

@@ -0,0 +1,37 @@
+body {
+  font-family: 'Open Sans', sans-serif;
+  font-size: 12px;
+  margin: 0;
+}
+button, input[type="submit"], input[type="reset"] {
+	background: none;
+	color: inherit;
+	border: none;
+	padding: 0;
+	font: inherit;
+	cursor: pointer;
+	outline: inherit;
+}
+body > div, body > nav {
+  margin-left: 60px;
+  margin-right: 60px;
+}
+nav {
+  text-align: center;
+  padding: 16px 0 8px;
+}
+nav img {
+  margin-right: auto;
+  height: 32px;
+}
+#panels {
+  display: flex;
+  flex-flow: row;
+  flex-wrap: wrap;
+  justify-content: center;
+}
+.panel {
+  min-width: 300px;
+  margin: 40px 0 0;
+  flex-grow: 1; 
+}

build/lib/gradio/static/js/all-io.js

@@ -0,0 +1,28 @@
+var NGROK_URL = "ws://0f9bffb5.ngrok.io"
+var SOCKET_PORT = 9200
+
+try {
+  var origin = window.location.origin;
+  if (origin.includes("ngrok")){
+      var ws = new WebSocket(NGROK_URL)
+  } else {
+      var ws = new WebSocket("ws://127.0.0.1:" + SOCKET_PORT + "/")
+  }
+  ws.onerror = function(evt) {
+    console.log(evt)
+  };
+  ws.onclose = function(event) {
+    console.log("WebSocket is closed now.");
+    var model_status = $('#model-status')
+    model_status.html('Model: closed');
+    model_status.css('color', '#e23e44');
+    $('#overlay').css('visibility','visible')
+};
+
+} catch (e) {
+  console.log(e)
+}
+
+const sleep = (milliseconds) => {
+  return new Promise(resolve => setTimeout(resolve, milliseconds))
+}

build/lib/gradio/static/js/audio-input.js

@@ -0,0 +1,255 @@
+import InlineWorker from 'inline-worker';
+
+export class Recorder {
+    config = {
+        bufferLen: 4096,
+        numChannels: 2,
+        mimeType: 'audio/wav'
+    };
+
+    recording = false;
+
+    callbacks = {
+        getBuffer: [],
+        exportWAV: []
+    };
+
+    constructor(source, cfg) {
+        Object.assign(this.config, cfg);
+        this.context = source.context;
+        this.node = (this.context.createScriptProcessor ||
+        this.context.createJavaScriptNode).call(this.context,
+            this.config.bufferLen, this.config.numChannels, this.config.numChannels);
+
+        this.node.onaudioprocess = (e) => {
+            if (!this.recording) return;
+
+            var buffer = [];
+            for (var channel = 0; channel < this.config.numChannels; channel++) {
+                buffer.push(e.inputBuffer.getChannelData(channel));
+            }
+            this.worker.postMessage({
+                command: 'record',
+                buffer: buffer
+            });
+        };
+
+        source.connect(this.node);
+        this.node.connect(this.context.destination);    //this should not be necessary
+
+        let self = {};
+        this.worker = new InlineWorker(function () {
+            let recLength = 0,
+                recBuffers = [],
+                sampleRate,
+                numChannels;
+
+            this.onmessage = function (e) {
+                switch (e.data.command) {
+                    case 'init':
+                        init(e.data.config);
+                        break;
+                    case 'record':
+                        record(e.data.buffer);
+                        break;
+                    case 'exportWAV':
+                        exportWAV(e.data.type);
+                        break;
+                    case 'getBuffer':
+                        getBuffer();
+                        break;
+                    case 'clear':
+                        clear();
+                        break;
+                }
+            };
+
+            function init(config) {
+                sampleRate = config.sampleRate;
+                numChannels = config.numChannels;
+                initBuffers();
+            }
+
+            function record(inputBuffer) {
+                for (var channel = 0; channel < numChannels; channel++) {
+                    recBuffers[channel].push(inputBuffer[channel]);
+                }
+                recLength += inputBuffer[0].length;
+            }
+
+            function exportWAV(type) {
+                let buffers = [];
+                for (let channel = 0; channel < numChannels; channel++) {
+                    buffers.push(mergeBuffers(recBuffers[channel], recLength));
+                }
+                let interleaved;
+                if (numChannels === 2) {
+                    interleaved = interleave(buffers[0], buffers[1]);
+                } else {
+                    interleaved = buffers[0];
+                }
+                let dataview = encodeWAV(interleaved);
+                let audioBlob = new Blob([dataview], {type: type});
+
+                this.postMessage({command: 'exportWAV', data: audioBlob});
+            }
+
+            function getBuffer() {
+                let buffers = [];
+                for (let channel = 0; channel < numChannels; channel++) {
+                    buffers.push(mergeBuffers(recBuffers[channel], recLength));
+                }
+                this.postMessage({command: 'getBuffer', data: buffers});
+            }
+
+            function clear() {
+                recLength = 0;
+                recBuffers = [];
+                initBuffers();
+            }
+
+            function initBuffers() {
+                for (let channel = 0; channel < numChannels; channel++) {
+                    recBuffers[channel] = [];
+                }
+            }
+
+            function mergeBuffers(recBuffers, recLength) {
+                let result = new Float32Array(recLength);
+                let offset = 0;
+                for (let i = 0; i < recBuffers.length; i++) {
+                    result.set(recBuffers[i], offset);
+                    offset += recBuffers[i].length;
+                }
+                return result;
+            }
+
+            function interleave(inputL, inputR) {
+                let length = inputL.length + inputR.length;
+                let result = new Float32Array(length);
+
+                let index = 0,
+                    inputIndex = 0;
+
+                while (index < length) {
+                    result[index++] = inputL[inputIndex];
+                    result[index++] = inputR[inputIndex];
+                    inputIndex++;
+                }
+                return result;
+            }
+
+            function floatTo16BitPCM(output, offset, input) {
+                for (let i = 0; i < input.length; i++, offset += 2) {
+                    let s = Math.max(-1, Math.min(1, input[i]));
+                    output.setInt16(offset, s < 0 ? s * 0x8000 : s * 0x7FFF, true);
+                }
+            }
+
+            function writeString(view, offset, string) {
+                for (let i = 0; i < string.length; i++) {
+                    view.setUint8(offset + i, string.charCodeAt(i));
+                }
+            }
+
+            function encodeWAV(samples) {
+                let buffer = new ArrayBuffer(44 + samples.length * 2);
+                let view = new DataView(buffer);
+
+                /* RIFF identifier */
+                writeString(view, 0, 'RIFF');
+                /* RIFF chunk length */
+                view.setUint32(4, 36 + samples.length * 2, true);
+                /* RIFF type */
+                writeString(view, 8, 'WAVE');
+                /* format chunk identifier */
+                writeString(view, 12, 'fmt ');
+                /* format chunk length */
+                view.setUint32(16, 16, true);
+                /* sample format (raw) */
+                view.setUint16(20, 1, true);
+                /* channel count */
+                view.setUint16(22, numChannels, true);
+                /* sample rate */
+                view.setUint32(24, sampleRate, true);
+                /* byte rate (sample rate * block align) */
+                view.setUint32(28, sampleRate * 4, true);
+                /* block align (channel count * bytes per sample) */
+                view.setUint16(32, numChannels * 2, true);
+                /* bits per sample */
+                view.setUint16(34, 16, true);
+                /* data chunk identifier */
+                writeString(view, 36, 'data');
+                /* data chunk length */
+                view.setUint32(40, samples.length * 2, true);
+
+                floatTo16BitPCM(view, 44, samples);
+
+                return view;
+            }
+        }, self);
+
+        this.worker.postMessage({
+            command: 'init',
+            config: {
+                sampleRate: this.context.sampleRate,
+                numChannels: this.config.numChannels
+            }
+        });
+
+        this.worker.onmessage = (e) => {
+            let cb = this.callbacks[e.data.command].pop();
+            if (typeof cb == 'function') {
+                cb(e.data.data);
+            }
+        };
+    }
+
+
+    record() {
+        this.recording = true;
+    }
+
+    stop() {
+        this.recording = false;
+    }
+
+    clear() {
+        this.worker.postMessage({command: 'clear'});
+    }
+
+    getBuffer(cb) {
+        cb = cb || this.config.callback;
+        if (!cb) throw new Error('Callback not set');
+
+        this.callbacks.getBuffer.push(cb);
+
+        this.worker.postMessage({command: 'getBuffer'});
+    }
+
+    exportWAV(cb, mimeType) {
+        mimeType = mimeType || this.config.mimeType;
+        cb = cb || this.config.callback;
+        if (!cb) throw new Error('Callback not set');
+
+        this.callbacks.exportWAV.push(cb);
+
+        this.worker.postMessage({
+            command: 'exportWAV',
+            type: mimeType
+        });
+    }
+
+    static
+    forceDownload(blob, filename) {
+        let url = (window.URL || window.webkitURL).createObjectURL(blob);
+        let link = window.document.createElement('a');
+        link.href = url;
+        link.download = filename || 'output.wav';
+        let click = document.createEvent("Event");
+        click.initEvent("click", true, true);
+        link.dispatchEvent(click);
+    }
+}
+
+export default Recorder;

build/lib/gradio/static/js/class-output.js

@@ -0,0 +1,63 @@
+function notifyError(error) {
+      $.notify({
+          // options
+          message: 'Not able to communicate with model (is python code still running?)'
+      },{
+          // settings
+          type: 'danger',
+          animate: {
+              enter: 'animated fadeInDown',
+              exit: 'animated fadeOutUp'
+          },
+          placement: {
+              from: "bottom",
+              align: "right"
+          },
+          delay: 5000
+
+      });
+ }
+
+try {
+  ws.onerror = function(evt) {
+    notifyError(evt)
+  };
+
+  ws.onmessage = function (event) {
+    sleep(300).then(() => {
+//      $(".output_class").text(event.data);
+      var data = JSON.parse(event.data)
+      // data = {
+      //   label: "happy",
+      //   confidences : [
+      //    {
+      //     label : "happy",
+      //     confidence: 0.7
+      //    },
+      //    {
+      //     label : "sad",
+      //     confidence: 0.3
+      //    },
+      //   ]
+      //   }
+      $(".output_class").text(data["label"])
+      $(".confidence_intervals").empty()
+      if ("confidences" in data) {
+        data["confidences"].forEach(function (c) {
+          var confidence = c["confidence"]
+          $(".confidence_intervals").append(`<div class="confidence"><div class=
+              "label">${c["label"]}</div><div class="level" style="flex-grow:
+                ${confidence}">${Math.round(confidence * 100)}%</div></div>`)
+        })
+      }
+    })
+
+  }
+} catch (e) {
+  notifyError(e)
+}
+
+$('body').on('click', '.clear', function(e) {
+  $(".output_class").text("")
+  $(".confidence_intervals").empty()
+})

build/lib/gradio/static/js/draw-a-digit.js

@@ -0,0 +1,128 @@
+var canvas = document.getElementById('canvas');
+context = canvas.getContext("2d");
+context.fillStyle = "black";
+context.fillRect(0, 0, 400, 400);
+
+var predict_canvas = document.getElementById("predict_canvas");
+var ctx = predict_canvas.getContext("2d");
+
+const sleep = (milliseconds) => {
+  return new Promise(resolve => setTimeout(resolve, milliseconds))
+}
+
+function notifyError(error) {
+      $.notify({
+          // options
+          message: 'Not able to communicate with model (is python code still running?)'
+      },{
+          // settings
+          type: 'danger',
+          animate: {
+              enter: 'animated fadeInDown',
+              exit: 'animated fadeOutUp'
+          },
+          placement: {
+              from: "bottom",
+              align: "right"
+          },
+          delay: 5000
+
+      });
+ }
+
+try {
+  var ws = new WebSocket("ws://127.0.0.1:5679/")
+  ws.onerror = function(evt) {
+    notifyError(evt)
+  };
+
+  ws.onmessage = function (event) {
+    console.log(event.data);
+    ctx.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+    ctx.font = "330px Arial";
+    ctx.fillStyle = "white";
+    sleep(300).then(() => {
+      ctx.fillText(event.data, 110, 310);
+    })
+
+  }
+} catch (e) {
+  notifyError(e)
+}
+
+
+
+
+$('#canvas').mousedown(function(e){
+  var mouseX = e.pageX - this.getBoundingClientRect().left + document.documentElement.scrollLeft;
+  var mouseY = e.pageY - this.getBoundingClientRect().top + document.documentElement.scrollTop
+;
+
+  paint = true;
+  addClick(mouseX, mouseY);
+  redraw();
+});
+$('#canvas').mousemove(function(e){
+  if(paint){
+    addClick(e.pageX - this.getBoundingClientRect().left + document.documentElement.scrollLeft, e.pageY - this.getBoundingClientRect().top + document.documentElement.scrollTop, true);
+    redraw();
+  }
+});
+$('#canvas').mouseup(function(e){
+  paint = false;
+});
+$('#canvas').mouseleave(function(e){
+  paint = false;
+});
+var clickX = new Array();
+var clickY = new Array();
+var clickDrag = new Array();
+var paint;
+
+function addClick(x, y, dragging)
+{
+  clickX.push(x);
+  clickY.push(y);
+  clickDrag.push(dragging);
+}
+function redraw(){
+  context.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+  context.fillStyle = "black";
+  context.fillRect(0, 0, 400, 400);
+
+  context.strokeStyle = "#FFF";
+  context.lineJoin = "round";
+  context.lineWidth = 25;
+
+  for(var i=0; i < clickX.length; i++) {
+    context.beginPath();
+    if(clickDrag[i] && i){
+      context.moveTo(clickX[i-1], clickY[i-1]);
+     }else{
+       context.moveTo(clickX[i]-1, clickY[i]);
+     }
+     context.lineTo(clickX[i], clickY[i]);
+     context.closePath();
+     context.stroke();
+  }
+}
+
+$('#clear-button').click(function(e){
+    context.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+    clickX = new Array();
+    clickY = new Array();
+    clickDrag = new Array();
+    context.fillStyle = "black";
+    context.fillRect(0, 0, 400, 400);
+    ctx.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+})
+
+
+$('#submit-button').click(function(e){
+    var dataURL = canvas.toDataURL("image/png");
+    ws.send(dataURL, function(e){
+      notifyError(e)
+    });
+
+})
+

build/lib/gradio/static/js/emotion-detector.js

@@ -0,0 +1,180 @@
+videoWidth = 400;
+videoHeight = 400;
+
+function isAndroid() {
+  return /Android/i.test(navigator.userAgent);
+}
+
+function isiOS() {
+  return /iPhone|iPad|iPod/i.test(navigator.userAgent);
+}
+
+function isMobile() {
+  return isAndroid() || isiOS();
+}
+
+var predict_canvas = document.getElementById("predict_canvas");
+var predict_ctx = predict_canvas.getContext("2d");
+var canvas = document.getElementById("canvas");
+var ctx = canvas.getContext("2d");
+
+
+const sleep = (milliseconds) => {
+  return new Promise(resolve => setTimeout(resolve, milliseconds))
+}
+
+async function setupCamera() {
+  if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
+    throw new Error(
+        'Browser API navigator.mediaDevices.getUserMedia not available');
+  }
+  
+  const video = document.getElementById('video');
+  video.width = videoWidth;
+  video.height = videoHeight;
+  
+
+  const mobile = isMobile();
+  const stream = await navigator.mediaDevices.getUserMedia({
+  'audio': false,
+  'video': {
+    facingMode: 'user',
+    width: mobile ? undefined : videoWidth,
+    height: mobile ? undefined : videoHeight,
+  },
+  });
+  
+  video.srcObject = stream;
+
+  return new Promise((resolve) => {
+  video.onloadedmetadata = () => {
+    resolve(video);
+  };
+  });
+
+}
+
+async function loadVideo() {
+  const video = await setupCamera();
+  video.play();
+
+  return video;
+}
+
+function detectPoseInRealTime(video) {
+  const flipHorizontal = true;
+  async function poseDetectionFrame() {
+
+    ctx.clearRect(0, 0, videoWidth, videoHeight);
+
+    ctx.save();
+    ctx.scale(-1, 1);
+    ctx.translate(-videoWidth, 0);
+    ctx.drawImage(video, 0, 0, videoWidth, videoHeight);
+    ctx.restore();
+ 
+    requestAnimationFrame(poseDetectionFrame);
+
+  }
+
+  poseDetectionFrame();
+}
+
+async function bindPage() {
+
+  let video;
+
+  try {
+    video = await loadVideo();
+  } catch (e) {
+    let info = document.getElementById('info');
+    info.textContent = 'this browser does not support video capture,' +
+        'or this device does not have a camera';
+    info.style.display = 'block';
+    throw e;
+  }
+
+  detectPoseInRealTime(video);
+
+}
+
+navigator.getUserMedia = navigator.getUserMedia ||
+    navigator.webkitGetUserMedia || navigator.mozGetUserMedia;
+// kick off the demo
+bindPage();
+
+
+function notifyError(error) {
+      $.notify({
+          // options
+          message: 'Not able to communicate with model (is python code still running?)'
+      },{
+          // settings
+          type: 'danger',
+          animate: {
+              enter: 'animated fadeInDown',
+              exit: 'animated fadeOutUp'
+          },
+          placement: {
+              from: "bottom",
+              align: "right"
+          },
+          delay: 5000
+
+      });
+ }
+
+try {
+  var ws = new WebSocket("ws://127.0.0.1:5679/")
+  ws.onerror = function(evt) {
+    notifyError(evt)
+  };
+
+  ws.onmessage = function (event) {
+    var emotion_dict = {0: "Angry", 1: "Disgust", 2: "Fear", 3: "Happy", 4: "Sad", 5: "Surprise", 6: "Neutral"}
+    console.log(event.data);
+    predict_ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height); // Clears the canvas
+    predict_ctx.font = "60px Arial";
+    predict_ctx.fillStyle = "white";
+    sleep(300).then(() => {
+      // predict_ctx.fillText(emotion_dict[event.data], 110, 310);
+      predict_ctx.textAlign = "center";
+      predict_ctx.fillText(emotion_dict[event.data], 200, 200);
+    })
+
+  }
+} catch (e) {
+  notifyError(e)
+}
+
+$('#clear-button').click(function(e){
+    context.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+    clickX = new Array();
+    clickY = new Array();
+    clickDrag = new Array();
+    context.fillStyle = "black";
+    context.fillRect(0, 0, 400, 400);
+    ctx.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+})
+
+
+$('#submit-button').click(function(e){
+    var dataURL = canvas.toDataURL("image/png");
+    ws.send(dataURL, function(e){
+      notifyError(e)
+    });
+
+})
+
+$('#capture-button').click(function(e){  
+    ctx.clearRect(0, 0, videoWidth, videoHeight);
+    ctx.save();
+    ctx.scale(-1, 1);
+    ctx.translate(-videoWidth, 0);
+    ctx.drawImage(video, 0, 0, videoWidth, videoHeight);
+    ctx.restore();
+      var dataURL = canvas.toDataURL("image/png");
+      ws.send(dataURL, function(e){
+        notifyError(e)
+      });
+})

build/lib/gradio/static/js/image-upload-input.js

@@ -0,0 +1,60 @@
+// var cropper;
+
+$('body').on('click', ".input_image.drop_mode", function (e) {
+  $(this).parent().find(".hidden_upload").click();
+})
+
+$('body').on('drag dragstart dragend dragover dragenter dragleave drop', ".input_image.drop_mode", function(e) {
+  e.preventDefault();
+  e.stopPropagation();
+})
+
+function loadPreviewFromFiles(files) {
+  var ReaderObj = new FileReader()
+  ReaderObj.readAsDataURL(files[0])
+  ReaderObj.onloadend = function() {
+    $(".input_caption").hide()
+    $(".input_image").removeClass("drop_mode")
+    var image = $(".input_image img")
+    image.attr("src", this.result)
+    // image.cropper({aspectRatio : 1.0});
+    // if (!cropper) {
+    //   cropper = image.data('cropper');
+    // }
+  }
+}
+
+$(".input_image").on('drop', function(e) {
+  files = e.originalEvent.dataTransfer.files;
+  loadPreviewFromFiles(files)
+});
+
+$(".hidden_upload").on("change", function() {
+  var files = !!this.files ? this.files : []
+  if (!files.length || !window.FileReader) {
+    return
+  }
+  if (/^image/.test(files[0].type)) {
+    loadPreviewFromFiles(files)
+  } else {
+    alert("Invalid input")
+  }
+})
+
+$('body').on('click', '.submit', function(e) {
+  var src = $('.input_image img').attr('src');
+  src = resizeImage(src)
+  ws.send(src, function(e) {
+    notifyError(e)
+  })
+})
+
+$('body').on('click', '.clear', function(e) {
+  // if (cropper) {
+  //   cropper.destroy();
+  //   cropper = null
+  // }
+  $(".input_caption").show()
+  $(".input_image img").removeAttr("src");
+  $(".input_image").addClass("drop_mode")
+})

build/lib/gradio/static/js/sketchpad-input.js

@@ -0,0 +1,100 @@
+var canvas = document.getElementById('canvas');
+context = canvas.getContext("2d");
+context.fillStyle = "black";
+context.fillRect(0, 0, 400, 400);
+
+
+function notifyError(error) {
+      $.notify({
+          // options
+          message: 'Not able to communicate with model (is python code still running?)'
+      },{
+          // settings
+          type: 'danger',
+          animate: {
+              enter: 'animated fadeInDown',
+              exit: 'animated fadeOutUp'
+          },
+          placement: {
+              from: "bottom",
+              align: "right"
+          },
+          delay: 5000
+
+      });
+ }
+
+
+$('#canvas').mousedown(function(e){
+  var mouseX = e.pageX - this.getBoundingClientRect().left + document.documentElement.scrollLeft;
+  var mouseY = e.pageY - this.getBoundingClientRect().top + document.documentElement.scrollTop
+;
+
+  paint = true;
+  addClick(mouseX, mouseY);
+  redraw();
+});
+$('#canvas').mousemove(function(e){
+  if(paint){
+    addClick(e.pageX - this.getBoundingClientRect().left + document.documentElement.scrollLeft, e.pageY - this.getBoundingClientRect().top + document.documentElement.scrollTop, true);
+    redraw();
+  }
+});
+$('#canvas').mouseup(function(e){
+  paint = false;
+});
+$('#canvas').mouseleave(function(e){
+  paint = false;
+});
+var clickX = new Array();
+var clickY = new Array();
+var clickDrag = new Array();
+var paint;
+
+function addClick(x, y, dragging)
+{
+  clickX.push(x);
+  clickY.push(y);
+  clickDrag.push(dragging);
+}
+function redraw(){
+  context.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+  context.fillStyle = "black";
+  context.fillRect(0, 0, 400, 400);
+
+  context.strokeStyle = "#FFF";
+  context.lineJoin = "round";
+  context.lineWidth = 25;
+
+  for(var i=0; i < clickX.length; i++) {
+    context.beginPath();
+    if(clickDrag[i] && i){
+      context.moveTo(clickX[i-1], clickY[i-1]);
+     }else{
+       context.moveTo(clickX[i]-1, clickY[i]);
+     }
+     context.lineTo(clickX[i], clickY[i]);
+     context.closePath();
+     context.stroke();
+  }
+}
+
+$('#clear-button').click(function(e){
+    context.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+    clickX = new Array();
+    clickY = new Array();
+    clickDrag = new Array();
+    context.fillStyle = "black";
+    context.fillRect(0, 0, 400, 400);
+    ctx.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+})
+
+
+$('#submit-button').click(function(e){
+    var dataURL = canvas.toDataURL("image/png");
+    ws.send(dataURL, function(e){
+      notifyError(e)  
+    });
+
+})
+

build/lib/gradio/static/js/textbox-input.js

@@ -0,0 +1,18 @@
+var text = $("#textbox-input").val();
+
+
+
+$('#clear-button').click(function(e){
+    document.getElementById("textbox-input").value="";
+})
+
+
+$('#submit-button').click(function(e){
+    // var dataURL = canvas.toDataURL("image/png");
+    var text = $("#textbox-input").val();
+    console.log(text);
+    ws.send(text, function(e){
+      notifyError(e)
+    });
+
+})

build/lib/gradio/static/js/textbox-output.js

@@ -0,0 +1,36 @@
+
+function notifyError(error) {
+      $.notify({
+          // options
+          message: 'Not able to communicate with model (is python code still running?)'
+      },{
+          // settings
+          type: 'danger',
+          animate: {
+              enter: 'animated fadeInDown',
+              exit: 'animated fadeOutUp'
+          },
+          placement: {
+              from: "bottom",
+              align: "right"
+          },
+          delay: 5000
+
+      });
+ }
+
+try {
+  ws.onerror = function(evt) {
+    notifyError(evt)
+  };
+
+  ws.onmessage = function (event) {
+    console.log(event.data);
+    sleep(300).then(() => {
+   	$("#textbox-output").val(event.data);
+    })
+
+  }
+} catch (e) {
+  notifyError(e)
+}

build/lib/gradio/static/js/utils.js

@@ -0,0 +1,27 @@
+function resizeImage(base64Str) {
+
+    var img = new Image();
+    img.src = base64Str;
+    var canvas = document.createElement('canvas');
+    var MAX_WIDTH = 360;
+    var MAX_HEIGHT = 360;
+    var width = img.width;
+    var height = img.height;
+
+    if (width > height) {
+      if (width > MAX_WIDTH) {
+        height *= MAX_WIDTH / width;
+        width = MAX_WIDTH;
+      }
+    } else {
+      if (height > MAX_HEIGHT) {
+        width *= MAX_HEIGHT / height;
+        height = MAX_HEIGHT;
+      }
+    }
+    canvas.width = width;
+    canvas.height = height;
+    var ctx = canvas.getContext('2d');
+    ctx.drawImage(img, 0, 0, width, height);
+    return canvas.toDataURL();
+  }

build/lib/gradio/static/js/webcam-input.js

@@ -0,0 +1,152 @@
+videoWidth = 400;
+videoHeight = 400;
+
+function isAndroid() {
+  return /Android/i.test(navigator.userAgent);
+}
+
+function isiOS() {
+  return /iPhone|iPad|iPod/i.test(navigator.userAgent);
+}
+
+function isMobile() {
+  return isAndroid() || isiOS();
+}
+
+var canvas = document.getElementById("canvas");
+var ctx = canvas.getContext("2d");
+
+
+async function setupCamera() {
+  if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
+    throw new Error(
+        'Browser API navigator.mediaDevices.getUserMedia not available');
+  }
+  
+  const video = document.getElementById('video');
+  video.width = videoWidth;
+  video.height = videoHeight;
+  
+
+  const mobile = isMobile();
+  const stream = await navigator.mediaDevices.getUserMedia({
+  'audio': false,
+  'video': {
+    facingMode: 'user',
+    width: mobile ? undefined : videoWidth,
+    height: mobile ? undefined : videoHeight,
+  },
+  });
+  
+  video.srcObject = stream;
+
+  return new Promise((resolve) => {
+  video.onloadedmetadata = () => {
+    resolve(video);
+  };
+  });
+
+}
+
+async function loadVideo() {
+  const video = await setupCamera();
+  video.play();
+
+  return video;
+}
+
+function detectPoseInRealTime(video) {
+  const flipHorizontal = true;
+  async function poseDetectionFrame() {
+
+    ctx.clearRect(0, 0, videoWidth, videoHeight);
+
+    ctx.save();
+    ctx.scale(-1, 1);
+    ctx.translate(-videoWidth, 0);
+    ctx.drawImage(video, 0, 0, videoWidth, videoHeight);
+    ctx.restore();
+ 
+    requestAnimationFrame(poseDetectionFrame);
+
+  }
+
+  poseDetectionFrame();
+}
+
+async function bindPage() {
+
+  let video;
+
+  try {
+    video = await loadVideo();
+  } catch (e) {
+    let info = document.getElementById('info');
+    info.textContent = 'this browser does not support video capture,' +
+        'or this device does not have a camera';
+    info.style.display = 'block';
+    throw e;
+  }
+
+  detectPoseInRealTime(video);
+
+}
+
+navigator.getUserMedia = navigator.getUserMedia ||
+    navigator.webkitGetUserMedia || navigator.mozGetUserMedia;
+// kick off the demo
+bindPage();
+
+
+function notifyError(error) {
+      $.notify({
+          // options
+          message: 'Not able to communicate with model (is python code still running?)'
+      },{
+          // settings
+          type: 'danger',
+          animate: {
+              enter: 'animated fadeInDown',
+              exit: 'animated fadeOutUp'
+          },
+          placement: {
+              from: "bottom",
+              align: "right"
+          },
+          delay: 5000
+
+      });
+ }
+
+
+$('#clear-button').click(function(e){
+    context.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+    clickX = new Array();
+    clickY = new Array();
+    clickDrag = new Array();
+    context.fillStyle = "black";
+    context.fillRect(0, 0, 400, 400);
+    ctx.clearRect(0, 0, context.canvas.width, context.canvas.height); // Clears the canvas
+})
+
+
+$('#submit-button').click(function(e){
+    var dataURL = canvas.toDataURL("image/png");
+    ws.send(dataURL, function(e){
+      notifyError(e)
+    });
+
+})
+
+$('#capture-button').click(function(e){  
+    ctx.clearRect(0, 0, videoWidth, videoHeight);
+    ctx.save();
+    ctx.scale(-1, 1);
+    ctx.translate(-videoWidth, 0);
+    ctx.drawImage(video, 0, 0, videoWidth, videoHeight);
+    ctx.restore();
+    var dataURL = canvas.toDataURL("image/png");
+    ws.send(dataURL, function(e){
+      notifyError(e)
+    });
+})

examples/.ipynb_checkpoints/Emotional Detector (ImageUpload)-checkpoint.ipynb

@@ -68,25 +68,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "KeyError",
-     "evalue": "'label'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
-      "\u001b[1;32m<ipython-input-5-63a258f2163d>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0miface\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgradio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInterface\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'imageupload'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'label'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmodel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmodel_type\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'keras'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mpostprocessing_fn\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mpost_p\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0miface\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlaunch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshare_link\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\gradio\\__init__.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, input, output, model, model_type, preprocessing_fn, postprocessing_fn)\u001b[0m\n\u001b[0;32m     38\u001b[0m         \"\"\"\n\u001b[0;32m     39\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minput_interface\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minputs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mregistry\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpreprocessing_fn\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 40\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moutput_interface\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0moutputs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mregistry\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0moutput\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpostprocessing_fn\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     41\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmodel_type\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmodel_type\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     42\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmodel_obj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
-      "\u001b[1;31mKeyError\u001b[0m: 'label'"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
-    "iface = gradio.Interface(input='imageupload', output='label', model=model, model_type='keras',postprocessing_fn=post_p)\n",
-    "iface.launch(share_link=False)"
+    "iface = gradio.Interface(inputs='imageupload', outputs='label', model=model, model_type='keras',postprocessing_fn=post_p)\n",
+    "iface.launch(share=False)"
    ]
   }
  ],
@@ -106,7 +93,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.0"
   }
  },
  "nbformat": 4,

examples/Emotional Detector (ImageUpload).ipynb

@@ -32,32 +32,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "WARNING:tensorflow:From C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\tensorflow\\python\\framework\\op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "Colocations handled automatically by placer.\n",
-      "WARNING:tensorflow:From C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n",
-      "WARNING:tensorflow:From C:\\Users\\ALI\\Anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
-      "Instructions for updating:\n",
-      "Use tf.cast instead.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "model = load_model('../.models/emotion.h5')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -68,20 +52,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "DistutilsFileError",
+     "evalue": "cannot copy tree 'C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\gradio\\static\\': not a directory",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mDistutilsFileError\u001b[0m                        Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-5-7682ebc4c24c>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0miface\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgradio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mInterface\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'imageupload'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutputs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'label'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmodel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmodel_type\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'keras'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0miface\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlaunch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshare\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;32m~\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\gradio\\interface.py\u001b[0m in \u001b[0;36mlaunch\u001b[1;34m(self, inline, browser, share)\u001b[0m\n\u001b[0;32m    136\u001b[0m         \u001b[0mserver_port\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnetworking\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart_simple_server\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput_directory\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    137\u001b[0m         \u001b[0mpath_to_server\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'http://localhost:{}/'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mserver_port\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 138\u001b[1;33m         \u001b[0mnetworking\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbuild_template\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput_directory\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minput_interface\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moutput_interface\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    139\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    140\u001b[0m         \u001b[1;31m# Set up a port to serve a websocket that sets up the communication between the front-end and model.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m~\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\gradio\\networking.py\u001b[0m in \u001b[0;36mbuild_template\u001b[1;34m(temp_dir, input_interface, output_interface)\u001b[0m\n\u001b[0;32m     67\u001b[0m     \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mall_io_soup\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     68\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 69\u001b[1;33m     \u001b[0mcopy_files\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mSTATIC_PATH_LIB\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtemp_dir\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mSTATIC_PATH_TEMP\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     70\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     71\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m~\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\gradio\\networking.py\u001b[0m in \u001b[0;36mcopy_files\u001b[1;34m(src_dir, dest_dir)\u001b[0m\n\u001b[0;32m     76\u001b[0m     \u001b[1;33m:\u001b[0m\u001b[0mparam\u001b[0m \u001b[0mdest_dir\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstring\u001b[0m \u001b[0mpath\u001b[0m \u001b[0mto\u001b[0m \u001b[0mdestination\u001b[0m \u001b[0mdirectory\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     77\u001b[0m     \"\"\"\n\u001b[1;32m---> 78\u001b[1;33m     \u001b[0mdir_util\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcopy_tree\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msrc_dir\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdest_dir\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     79\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     80\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;32m~\\Anaconda3\\envs\\tensorflow\\lib\\distutils\\dir_util.py\u001b[0m in \u001b[0;36mcopy_tree\u001b[1;34m(src, dst, preserve_mode, preserve_times, preserve_symlinks, update, verbose, dry_run)\u001b[0m\n\u001b[0;32m    122\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mdry_run\u001b[0m \u001b[1;32mand\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0misdir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    123\u001b[0m         raise DistutilsFileError(\n\u001b[1;32m--> 124\u001b[1;33m               \"cannot copy tree '%s': not a directory\" % src)\n\u001b[0m\u001b[0;32m    125\u001b[0m     \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    126\u001b[0m         \u001b[0mnames\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlistdir\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mDistutilsFileError\u001b[0m: cannot copy tree 'C:\\Users\\islam\\Anaconda3\\envs\\tensorflow\\lib\\site-packages\\gradio\\static\\': not a directory"
+     ]
+    }
+   ],
    "source": [
-    "iface = gradio.Interface(input='imageupload', output='class', model=model, model_type='keras',postprocessing_fn=post_p)\n",
-    "iface.launch(share_link=False)"
+    "iface = gradio.Interface(inputs='imageupload', outputs='label', model=model, model_type='keras')\n",
+    "iface.launch(share=False)"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3.6 (tensorflow)",
    "language": "python",
-   "name": "python3"
+   "name": "tensorflow"
   },
   "language_info": {
    "codemirror_mode": {
@@ -93,7 +93,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.6.7"
   }
  },
  "nbformat": 4,

gradio.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 1.0
 Name: gradio
-Version: 0.3.1
+Version: 0.3.2
 Summary: Python library for easily interacting with trained machine learning models
 Home-page: https://github.com/abidlabs/gradio
 Author: Abubakar Abid

gradio.egg-info/SOURCES.txt

@@ -13,6 +13,25 @@ gradio.egg-info/SOURCES.txt
 gradio.egg-info/dependency_links.txt
 gradio.egg-info/requires.txt
 gradio.egg-info/top_level.txt
+gradio/static/css/.DS_Store
+gradio/static/css/gradio.css
+gradio/static/css/style.css
+gradio/static/img/logo.png
+gradio/static/img/logo_inline.png
+gradio/static/img/mic.png
+gradio/static/img/webcam.png
+gradio/static/js/all-io.js
+gradio/static/js/audio-input.js
+gradio/static/js/class-output.js
+gradio/static/js/draw-a-digit.js
+gradio/static/js/emotion-detector.js
+gradio/static/js/image-upload-input.js
+gradio/static/js/jquery-3.3.1.min.js
+gradio/static/js/sketchpad-input.js
+gradio/static/js/textbox-input.js
+gradio/static/js/textbox-output.js
+gradio/static/js/utils.js
+gradio/static/js/webcam-input.js
 gradio/templates/base_template.html
 gradio/templates/image_upload_input.html
 gradio/templates/label_output.html

setup.py

@@ -5,7 +5,7 @@ except ImportError:
 
 setup(
     name='gradio',
-    version='0.3.1',
+    version='0.3.2',
     include_package_data=True,
     description='Python library for easily interacting with trained machine learning models',
     author='Abubakar Abid',