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deepai - npm Package Compare versions
Comparing version 1.0.6 to 1.0.7
@@ -95,3 +95,4 @@ 'use strict'; | ||
| DeepAI.prototype.renderResultIntoElement = resultRendering.renderResultIntoElement; | ||
| DeepAI.prototype.renderAnnotatedResultIntoElement = resultRendering.renderAnnotatedResultIntoElement; | ||
| module.exports = DeepAI; |
| 'use strict'; | ||
| const apiBaseUrl = require('./apiBaseUrl').baseUrl; | ||
| var WAD_COLORS = [ | ||
| "rgb(173, 35, 35)", // Red | ||
| "rgb(42, 75, 215)", // Blue | ||
| "rgb(87, 87, 87)", // Dark Gray | ||
| "rgb(29, 105, 20)", // Green | ||
| "rgb(129, 74, 25)", // Brown | ||
| "rgb(129, 38, 192)", // Purple | ||
| "rgb(160, 160, 160)", // Lt Gray | ||
| "rgb(129, 197, 122)", // Lt green | ||
| "rgb(157, 175, 255)", // Lt blue | ||
| "rgb(41, 208, 208)", // Cyan | ||
| "rgb(255, 146, 51)", // Orange | ||
| "rgb(199, 183, 0)", // Yellow | ||
| "rgb(233, 222, 187)", // Tan | ||
| "rgb(255, 205, 243)", // Pink | ||
| // "rgb(255, 255, 255)", // White | ||
| //"rgb(0, 0, 0)", // Black | ||
| "rgb(173, 35, 35)", // Red | ||
| "rgb(42, 75, 215)", // Blue | ||
| "rgb(87, 87, 87)", // Dark Gray | ||
| "rgb(29, 105, 20)", // Green | ||
| "rgb(129, 74, 25)", // Brown | ||
| "rgb(129, 38, 192)", // Purple | ||
| "rgb(160, 160, 160)", // Lt Gray | ||
| "rgb(129, 197, 122)", // Lt green | ||
| "rgb(157, 175, 255)", // Lt blue | ||
| "rgb(41, 208, 208)", // Cyan | ||
| "rgb(255, 146, 51)", // Orange | ||
| "rgb(199, 183, 0)", // Yellow | ||
| "rgb(233, 222, 187)", // Tan | ||
| "rgb(255, 205, 243)", // Pink | ||
| // "rgb(255, 255, 255)", // White | ||
| //"rgb(0, 0, 0)", // Black | ||
| ]; | ||
| var isAbsolute = new RegExp('^([a-z]+://|//)', 'i'); | ||
| var isDataOrBlob = new RegExp('^(data|blob):', 'i'); | ||
| async function renderResultIntoElement(result, element){ | ||
| function prependApiBaseIfNeeded(url) { | ||
| if(isAbsolute.test(url) || isDataOrBlob.test(url)) { | ||
| return url; // already absolute | ||
| } else { | ||
| return apiBaseUrl + url; // turn relative into absolute | ||
| } | ||
| } | ||
| /* | ||
| Data structures basic info... | ||
| result | ||
| { | ||
| output_url: | ||
| output: | ||
| id: | ||
| err: | ||
| } | ||
| resultPageData | ||
| { | ||
| result_data: { | ||
| inputs:[ | ||
| { | ||
| is_img: true, | ||
| url: (relative or absolute) | ||
| } | ||
| ], | ||
| visualizer_data: { | ||
| list_key: 'Objects' | ||
| label_key: 'Object' | ||
| }, | ||
| scale_applied: 1.333 | ||
| } | ||
| } | ||
| annotatedResult - this is basically the merging of the 2 above | ||
| { err: | ||
| output_url: | ||
| output: | ||
| id: | ||
| inputs:[ | ||
| { | ||
| is_img: true, | ||
| url: (relative or absolute) | ||
| } | ||
| ], | ||
| visualizer_data: { | ||
| list_key: 'Objects' | ||
| label_key: 'Object' | ||
| }, | ||
| scale_applied: 1.333 | ||
| } | ||
| */ | ||
| // Take a result object from API call, and fetch additional data, and return the additional data merged in. | ||
| async function getAnnotatedResultFromResult(result) { | ||
| if(result.err) { | ||
| console.log('cannot get result page data for error result'); | ||
| return result; | ||
| } | ||
| var resultPageData = await fetch(apiBaseUrl + '/get_standard_api_result_data/' + result.id, { | ||
| credentials: 'include' | ||
| }); | ||
| resultPageData = await resultPageData.json(); | ||
| var result_data = resultPageData.result_data; | ||
| // make merging of all the properties manually... | ||
| return { | ||
| err: result.err, | ||
| output: result.output, | ||
| output_url: result.output_url, | ||
| id: result.id, | ||
| inputs: result_data.inputs, | ||
| visualizer_data: result_data.visualizer_data, | ||
| scale_applied: result_data.scale_applied | ||
| }; | ||
| } | ||
| async function renderResultIntoElement(result, element) { | ||
| console.log('getting result page data'); | ||
| var annotatedResult = await getAnnotatedResultFromResult(result); | ||
| console.log('got result page data'); | ||
| return renderAnnotatedResultIntoElement(annotatedResult, element); | ||
| } | ||
| function renderAnnotatedResultIntoElement(annotatedResult, element) { | ||
| element.innerHTML = ''; // remove everything to start | ||
| if(result.err){ | ||
| if(annotatedResult.err) { | ||
| element.innerHTML = err; | ||
| return false; | ||
| } | ||
| if(result.output){ | ||
| if(annotatedResult.output) { | ||
| // JSON or text output. | ||
| console.log('got json or text output'); | ||
| console.log('getting result page data'); | ||
| var resultPageData = await fetch(apiBaseUrl + '/get_standard_api_result_data/'+result.id, { | ||
| credentials: 'include' | ||
| }); | ||
| resultPageData = await resultPageData.json(); | ||
| console.log('got result page data'); | ||
| if(typeof result.output === 'string'){ | ||
| if(typeof annotatedResult.output === 'string') { | ||
| var scroller = document.createElement("div"); | ||
@@ -51,15 +131,12 @@ scroller.style.width = '100%'; | ||
| element.appendChild(scroller); | ||
| var pre = document.createElement("pre"); | ||
| pre.textContent = result.output; | ||
| pre.textContent = annotatedResult.output; | ||
| pre.style.whiteSpace = "pre-wrap"; | ||
| pre.style.margin = '0px'; | ||
| scroller.appendChild(pre); | ||
| // Append inputs | ||
| for(var input of resultPageData.result_data.inputs){ | ||
| if(input.is_img){ | ||
| for(var input of annotatedResult.inputs) { | ||
| if(input.is_img) { | ||
| var img_tag = document.createElement('img'); | ||
| img_tag.src = apiBaseUrl + input.url; | ||
| img_tag.src = prependApiBaseIfNeeded(input.url); | ||
| img_tag.style.position = 'relative'; | ||
@@ -72,25 +149,15 @@ img_tag.style.width = '100%'; | ||
| } | ||
| return true; | ||
| }else if(typeof result.output === 'object'){ | ||
| } else if(typeof annotatedResult.output === 'object') { | ||
| // If we uploaded an image, then we may be able to render the image with boxes on top | ||
| if( resultPageData.result_data.inputs.length == 1 | ||
| && resultPageData.result_data.inputs[0].is_img | ||
| && resultPageData.result_data.visualizer_data | ||
| ){ | ||
| if(annotatedResult.inputs.length == 1 && | ||
| annotatedResult.inputs[0].is_img && | ||
| annotatedResult.visualizer_data | ||
| ) { | ||
| // single image input and we know how to visualize it. | ||
| console.log('have visualizer for result JSON'); | ||
| var resultscaler = document.createElement('iframe'); | ||
| // Set up a handler for when the frame loads - we need to handle this event | ||
| resultscaler.onload = function() { | ||
| // Firefox doesnt allow inner iframe manip until the iframe is loaded... | ||
| var innerDoc = resultscaler.contentDocument.body; | ||
@@ -102,75 +169,55 @@ innerDoc.style.margin = '0px'; | ||
| bbox_container.style.opacity = '0.001'; // the result are hidden until the iframe reflows - which is first when the img loads | ||
| innerDoc.appendChild(bbox_container); | ||
| var img_tag = document.createElement('img'); | ||
| img_tag.src = apiBaseUrl + resultPageData.result_data.inputs[0].url; | ||
| img_tag.src = prependApiBaseIfNeeded(annotatedResult.inputs[0].url); | ||
| img_tag.style.position = 'absolute'; | ||
| bbox_container.appendChild(img_tag); | ||
| var iframe_reflow = function(){ | ||
| var iframe_reflow = function() { | ||
| console.log('iframe resize'); | ||
| resultscaler.contentDocument.body.style.transform = null; | ||
| var bodyWidth = resultscaler.contentDocument.body.scrollWidth; | ||
| var bodyHeight = resultscaler.contentDocument.body.scrollHeight; | ||
| var imgWidth = img_tag.offsetWidth; | ||
| var imgHeight = img_tag.offsetHeight; | ||
| var containerWidth = resultscaler.offsetWidth; | ||
| var containerHeight = resultscaler.offsetHeight; | ||
| var wExcess=0; | ||
| var hExcess=0; | ||
| if(imgWidth < bodyWidth && imgHeight < bodyHeight){ | ||
| var wExcess = 0; | ||
| var hExcess = 0; | ||
| if(imgWidth < bodyWidth && imgHeight < bodyHeight) { | ||
| var wScale = containerWidth / imgWidth; | ||
| var hScale = containerHeight / imgHeight; | ||
| var minScale = Math.min(wScale, hScale); | ||
| wExcess = containerWidth - imgWidth*minScale; | ||
| hExcess = containerHeight - imgHeight*minScale; | ||
| }else{ | ||
| wExcess = containerWidth - imgWidth * minScale; | ||
| hExcess = containerHeight - imgHeight * minScale; | ||
| } else { | ||
| var wScale = containerWidth / bodyWidth; | ||
| var hScale = containerHeight / bodyHeight; | ||
| var minScale = Math.min(wScale, hScale); | ||
| wExcess = containerWidth - bodyWidth*minScale; | ||
| hExcess = containerHeight - bodyHeight*minScale; | ||
| wExcess = containerWidth - bodyWidth * minScale; | ||
| hExcess = containerHeight - bodyHeight * minScale; | ||
| } | ||
| wExcess = wExcess/minScale; | ||
| hExcess = hExcess/minScale; | ||
| wExcess = wExcess / minScale; | ||
| hExcess = hExcess / minScale; | ||
| resultscaler.contentDocument.body.style.transformOrigin = 'top left'; | ||
| resultscaler.contentDocument.body.style.transform = 'scale('+minScale+')'; | ||
| bbox_container.style.setProperty('--fontscale', (100/minScale)+ "%"); | ||
| bbox_container.style.left = (wExcess/2)+"px"; | ||
| bbox_container.style.top = (hExcess/2)+"px"; | ||
| resultscaler.contentDocument.body.style.transform = 'scale(' + minScale + ')'; | ||
| bbox_container.style.setProperty('--fontscale', (100 / minScale) + "%"); | ||
| bbox_container.style.left = (wExcess / 2) + "px"; | ||
| bbox_container.style.top = (hExcess / 2) + "px"; | ||
| bbox_container.style.opacity = '1'; | ||
| }; | ||
| resultscaler.contentWindow.onresize = iframe_reflow; | ||
| img_tag.onload = iframe_reflow; | ||
| var processed_annotations = process_annotations(result.output, resultPageData.result_data.visualizer_data, resultPageData.result_data.scale_applied); | ||
| var processed_annotations = process_annotations(annotatedResult.output, annotatedResult.visualizer_data, annotatedResult.scale_applied); | ||
| console.log('processed annotations', processed_annotations); | ||
| var i = 0; | ||
| for(var annotation of processed_annotations){ | ||
| for(var annotation of processed_annotations) { | ||
| var bbox = document.createElement('boundingbox'); | ||
| bbox.style.position = 'absolute'; | ||
| bbox.style.left = annotation.bounding_box[0]+'px'; | ||
| bbox.style.top = annotation.bounding_box[1]+'px'; | ||
| bbox.style.width = annotation.bounding_box[2]+'px'; | ||
| bbox.style.height = annotation.bounding_box[3]+'px'; | ||
| bbox.style.left = annotation.bounding_box[0] + 'px'; | ||
| bbox.style.top = annotation.bounding_box[1] + 'px'; | ||
| bbox.style.width = annotation.bounding_box[2] + 'px'; | ||
| bbox.style.height = annotation.bounding_box[3] + 'px'; | ||
| var color = WAD_COLORS[i++ % WAD_COLORS.length]; | ||
| bbox.style.border = '2px solid '+color; | ||
| bbox.style.border = '2px solid ' + color; | ||
| bbox_container.appendChild(bbox); | ||
| var bbox_label = document.createElement('boundingboxlabel'); | ||
@@ -184,7 +231,5 @@ bbox_label.textContent = annotation.caption; | ||
| } | ||
| } | ||
| // Set the src which will end up triggering the onload event in all browsers. | ||
| resultscaler.src='about:blank'; | ||
| resultscaler.src = 'about:blank'; | ||
| resultscaler.style.border = 'none'; | ||
@@ -195,5 +240,3 @@ resultscaler.style.width = '100%'; | ||
| return true; | ||
| }else{ | ||
| } else { | ||
| // not single image - perhaps multi image or text input. | ||
@@ -209,15 +252,12 @@ // or no visualizer | ||
| scroller.style.flexDirection = 'column'; | ||
| element.appendChild(scroller); | ||
| var pre = document.createElement("pre"); | ||
| pre.style.margin = '0px'; | ||
| pre.textContent = JSON.stringify(result.output, null, 4); | ||
| pre.textContent = JSON.stringify(annotatedResult.output, null, 4); | ||
| scroller.appendChild(pre); | ||
| // Append inputs | ||
| for(var input of resultPageData.result_data.inputs){ | ||
| if(input.is_img){ | ||
| for(var input of annotatedResult.inputs) { | ||
| if(input.is_img) { | ||
| var img_tag = document.createElement('img'); | ||
| img_tag.src = apiBaseUrl + input.url; | ||
| img_tag.src = prependApiBaseIfNeeded(input.url); | ||
| img_tag.style.width = '100%'; | ||
@@ -229,22 +269,15 @@ img_tag.style.height = '79%'; | ||
| } | ||
| return true; | ||
| // We got JSON output for a multi image or text input ... don't bother showing the input right now | ||
| } | ||
| }else{ | ||
| } else { | ||
| element.innerHTML = "Model returned an unknown data type."; | ||
| return false; | ||
| } | ||
| }else if(result.output_url){ | ||
| } else if(annotatedResult.output_url) { | ||
| // Image output. | ||
| console.log('got image output'); | ||
| // Just show the image. | ||
| var img_tag = document.createElement('img'); | ||
| img_tag.src = result.output_url; | ||
| img_tag.src = annotatedResult.output_url; | ||
| img_tag.style.position = 'relative'; | ||
@@ -256,4 +289,3 @@ img_tag.style.width = '100%'; | ||
| return true; | ||
| }else{ | ||
| } else { | ||
| element.innerHTML = "Model did not return an output or an error."; | ||
@@ -264,3 +296,2 @@ return false; | ||
| function capitalizeFirstLetter(string) { | ||
@@ -271,11 +302,11 @@ return string.charAt(0).toUpperCase() + string.slice(1); | ||
| function toTitleCase(str) { | ||
| return str.replace( | ||
| /\w\S*/g, | ||
| function(txt) { | ||
| return txt.charAt(0).toUpperCase() + txt.substr(1).toLowerCase(); | ||
| } | ||
| ); | ||
| return str.replace( | ||
| /\w\S*/g, | ||
| function(txt) { | ||
| return txt.charAt(0).toUpperCase() + txt.substr(1).toLowerCase(); | ||
| } | ||
| ); | ||
| } | ||
| function process_annotations(input_struct, visualizer_data, scale_applied){ | ||
| function process_annotations(input_struct, visualizer_data, scale_applied) { | ||
| input_struct = JSON.parse(JSON.stringify(input_struct)); // cheap deep clone | ||
@@ -286,37 +317,34 @@ var detections = input_struct[visualizer_data.list_key]; | ||
| }); | ||
| var count = Math.min(15, detections.length); | ||
| var processed_annotations = []; | ||
| for (var i = 0; i < count; i++) { | ||
| for(var i = 0; i < count; i++) { | ||
| var detection = detections[i]; | ||
| var caption; | ||
| if(visualizer_data.label_key=='demographic'){ | ||
| if(detection[visualizer_data.label_key]){ | ||
| caption = detection[visualizer_data.label_key]; // backwards compatible demog format | ||
| }else{ | ||
| //"White Male, 30-40" | ||
| caption = detection['cultural_appearance']+' '+detection['gender']+', '+detection['age_range'][0]+'-'+detection['age_range'][1] | ||
| } | ||
| }else if(visualizer_data.label_key=='people'){ | ||
| //produces "Sad, White Male, 30-40, Ted Cruz" | ||
| var parts = []; | ||
| if(detection['facial-expression-recognition'] && detection['facial-expression-recognition']['emotion'] != null){ | ||
| parts.push( capitalizeFirstLetter(detection['facial-expression-recognition']['emotion']) ); | ||
| } | ||
| if(detection['demographic-recognition'] && detection['demographic-recognition']['cultural_appearance'] != null){ | ||
| parts.push( detection['demographic-recognition']['cultural_appearance']+' '+detection['demographic-recognition']['gender']+', '+detection['demographic-recognition']['age_range'][0]+'-'+detection['demographic-recognition']['age_range'][1]); | ||
| } | ||
| if(detection['celebrity-recognition'] && detection['celebrity-recognition']['name'] != null && detection['celebrity-recognition']['name'] != 'unknown'){ | ||
| parts.push( toTitleCase(detection['celebrity-recognition']['name']) ); | ||
| } | ||
| if(parts.length > 0){ | ||
| caption = parts.join(', '); | ||
| }else{ | ||
| caption = "Face"; | ||
| } | ||
| }else{ | ||
| caption = detection[visualizer_data.label_key]; // non demographic mode | ||
| if(visualizer_data.label_key == 'demographic') { | ||
| if(detection[visualizer_data.label_key]) { | ||
| caption = detection[visualizer_data.label_key]; // backwards compatible demog format | ||
| } else { | ||
| //"White Male, 30-40" | ||
| caption = detection['cultural_appearance'] + ' ' + detection['gender'] + ', ' + detection['age_range'][0] + '-' + detection['age_range'][1] | ||
| } | ||
| } else if(visualizer_data.label_key == 'people') { | ||
| //produces "Sad, White Male, 30-40, Ted Cruz" | ||
| var parts = []; | ||
| if(detection['facial-expression-recognition'] && detection['facial-expression-recognition']['emotion'] != null) { | ||
| parts.push(capitalizeFirstLetter(detection['facial-expression-recognition']['emotion'])); | ||
| } | ||
| if(detection['demographic-recognition'] && detection['demographic-recognition']['cultural_appearance'] != null) { | ||
| parts.push(detection['demographic-recognition']['cultural_appearance'] + ' ' + detection['demographic-recognition']['gender'] + ', ' + detection['demographic-recognition']['age_range'][0] + '-' + detection['demographic-recognition']['age_range'][1]); | ||
| } | ||
| if(detection['celebrity-recognition'] && detection['celebrity-recognition']['name'] != null && detection['celebrity-recognition']['name'] != 'unknown') { | ||
| parts.push(toTitleCase(detection['celebrity-recognition']['name'])); | ||
| } | ||
| if(parts.length > 0) { | ||
| caption = parts.join(', '); | ||
| } else { | ||
| caption = "Face"; | ||
| } | ||
| } else { | ||
| caption = detection[visualizer_data.label_key]; // non demographic mode | ||
| } | ||
| detection.bounding_box[0] *= scale_applied; | ||
@@ -326,3 +354,2 @@ detection.bounding_box[1] *= scale_applied; | ||
| detection.bounding_box[3] *= scale_applied; | ||
| processed_annotations.push({ | ||
@@ -337,3 +364,4 @@ bounding_box: detection.bounding_box, | ||
| module.exports = { | ||
| renderResultIntoElement: renderResultIntoElement | ||
| renderResultIntoElement: renderResultIntoElement, | ||
| renderAnnotatedResultIntoElement: renderAnnotatedResultIntoElement | ||
| }; |
| { | ||
| "name": "deepai", | ||
| "version": "1.0.6", | ||
| "version": "1.0.7", | ||
| "license": "BSD-2-Clause", | ||
@@ -11,22 +11,23 @@ "repository": { | ||
| "dependencies": { | ||
| "axios": "0.18.0", | ||
| "form-data": "2.3.3" | ||
| "axios": "0.19.0", | ||
| "form-data": "2.5.0" | ||
| }, | ||
| "devDependencies": { | ||
| "babel-core": "^6.26.3", | ||
| "babel-loader": "^6.2.2", | ||
| "babel-plugin-transform-async-to-generator": "^6.5.0", | ||
| "babel-polyfill": "^6.5.0", | ||
| "babel-preset-es2015": "^6.5.0", | ||
| "es6-promise": "^4.2.4", | ||
| "grunt": "^1.0.2", | ||
| "@babel/polyfill": "^7.4.4", | ||
| "@babel/core": "^7.5.0", | ||
| "@babel/plugin-transform-async-to-generator": "^7.5.0", | ||
| "@babel/preset-env": "^7.5.2", | ||
| "babel-loader": "^8.0.6", | ||
| "es6-promise": "4.2.8", | ||
| "grunt": "1.0.4", | ||
| "grunt-banner": "^0.6.0", | ||
| "grunt-cli": "^1.2.0", | ||
| "grunt-contrib-clean": "^1.1.0", | ||
| "grunt-contrib-clean": "2.0.0", | ||
| "grunt-contrib-watch": "^1.0.0", | ||
| "grunt-eslint": "^20.1.0", | ||
| "grunt-webpack": "^1.0.18", | ||
| "load-grunt-tasks": "^3.5.2", | ||
| "webpack": "^1.13.1", | ||
| "webpack-dev-server": "^1.14.1" | ||
| "grunt-eslint": "22.0.0", | ||
| "grunt-webpack": "3.1.3", | ||
| "load-grunt-tasks": "5.0.0", | ||
| "uglifyjs-webpack-plugin": "^2.1.3", | ||
| "webpack": "4.35.3", | ||
| "webpack-dev-server": "3.7.2" | ||
| }, | ||
@@ -33,0 +34,0 @@ "scripts": { |
@@ -80,2 +80,30 @@ # DeepAI JS Client | ||
| ##### Rendering a result without an extra network request: | ||
| The function renderAnnotatedResultIntoElement is for advanced users only. | ||
| ```js | ||
| var resultAnnotated = { | ||
| output_url: <Pass URL of the model output> | ||
| output: <Pass the model output directly in case of JSON or text output> | ||
| id: "fa616aa1-c762-4c98-b44e-75781627974a" <pass your job ID> | ||
| inputs:[ | ||
| { | ||
| is_img: true, | ||
| url: (relative or absolute img url, annotations will be rendered on top of this result url.) | ||
| } | ||
| ], | ||
| visualizer_data: { | ||
| list_key: 'Objects', (Name of the list property containing annotations) | ||
| label_key: 'Object' (Name of the value property to label annotations with) | ||
| }, | ||
| scale_applied: 1.333 (Scale to multiply all detection x y coordinates by before rendering) | ||
| }; | ||
| deepai.renderAnnotatedResultIntoElement(resultAnnotated, document.getElementById('yourResultContainerId')); | ||
| ``` | ||
| #### Node.js | ||
@@ -82,0 +110,0 @@ |
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Found 1 instance in 1 package
Fixed alerts
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Improved metrics
- Number of lines in readme file
- increased by23.33%
148
Worsened metrics
- Total package byte prevSize
- decreased by-23.35%
1904516
- Dev dependency count
- increased by6.25%
17
- Lines of code
- decreased by-3.11%
12711
Dependency changes
+ Addedaxios@0.19.0(transitive)
+ Addedfollow-redirects@1.5.10(transitive)
+ Addedform-data@2.5.0(transitive)
+ Addedis-buffer@2.0.5(transitive)
- Removedaxios@0.18.0(transitive)
- Removedfollow-redirects@1.15.9(transitive)
- Removedform-data@2.3.3(transitive)
- Removedis-buffer@1.1.6(transitive)
Updatedaxios@0.19.0
Updatedform-data@2.5.0