├── .eslintignore ├── .eslintrc.json ├── .gitignore ├── .prettier.json ├── LICENSE ├── README.md ├── package.json ├── public ├── index.html └── models │ ├── ssd_mobilenetv1_model-weights_manifest.json │ └── ssd_mobilenetv1_model.bin ├── src ├── App.tsx ├── components │ └── Canvas.tsx └── index.tsx └── tsconfig.json /.eslintignore: -------------------------------------------------------------------------------- 1 | node_modules/ 2 | **/node_modules/** 3 | 4 | .husky/ 5 | 6 | **/*.ts 7 | -------------------------------------------------------------------------------- /.eslintrc.json: -------------------------------------------------------------------------------- 1 | { 2 | "env": { 3 | "browser": true, 4 | "commonjs": true, 5 | "es2021": true 6 | }, 7 | "root": true, 8 | "parser": "@typescript-eslint/parser", 9 | "parserOptions": { 10 | "ecmaFeatures": { 11 | "jsx": true 12 | }, 13 | "ecmaVersion": 12 14 | }, 15 | "plugins": [ 16 | "@typescript-eslint", 17 | "react", 18 | "react-hooks" 19 | ], 20 | "extends": [ 21 | "airbnb", 22 | "plugin:react/recommended", 23 | "plugin:@typescript-eslint/eslint-recommended", 24 | "plugin:@typescript-eslint/recommended" 25 | ], 26 | "ignorePatterns": [ 27 | "**/node_modules/**" 28 | ], 29 | "settings": { 30 | "import/resolver": { 31 | "node": { 32 | "extensions": [ 33 | ".js", 34 | ".jsx", 35 | ".ts", 36 | ".tsx" 37 | ] 38 | } 39 | } 40 | }, 41 | "rules": { 42 | "max-len": ["warn", { "code": 120 }], 43 | "@typescript-eslint/no-var-requires": "off", 44 | "comma-dangle": "off", 45 | "Missing file extension": "off", 46 | "no-use-before-define": "off", 47 | "react/react-in-jsx-scope": "off", 48 | "quotes": "off", 49 | "@typescript-eslint/ban-ts-comment": "off", 50 | "@typescript-eslint/no-non-null-assertion": "off", 51 | "@typescript-eslint/explicit-module-boundary-types": "off", 52 | "@typescript-eslint/no-explicit-any": "off", 53 | "object-curly-newline": "off", 54 | "spaced-comment": "off", 55 | "react/jsx-filename-extension": [ 56 | 2, 57 | { 58 | "extensions": [ 59 | ".tsx" 60 | ] 61 | } 62 | ], 63 | "import/extensions": [ 64 | "error", 65 | "ignorePackages", 66 | { 67 | "js": "never", 68 | "jsx": "never", 69 | "ts": "never", 70 | "tsx": "never" 71 | } 72 | ] 73 | } 74 | } 75 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # See https://help.github.com/articles/ignoring-files/ for more about ignoring files. 2 | 3 | # dependencies 4 | /node_modules 5 | /.pnp 6 | .pnp.js 7 | 8 | # testing 9 | /coverage 10 | 11 | # production 12 | /build 13 | 14 | # misc 15 | .DS_Store 16 | .env.local 17 | .env.development.local 18 | .env.test.local 19 | .env.production.local 20 | 21 | npm-debug.log* 22 | yarn-debug.log* 23 | yarn-error.log* 24 | /package-lock.json 25 | 26 | .idea/ 27 | /src/react-app-env.d.ts 28 | -------------------------------------------------------------------------------- /.prettier.json: -------------------------------------------------------------------------------- 1 | { 2 | "trailingComma":"all", 3 | "tabWidth": 2, 4 | "semi": true, 5 | "singleQuote": false, 6 | "printWidth": 120, 7 | "jsxSingleQuote": false 8 | } 9 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. Definitions. 8 | 9 | "License" shall mean the terms and conditions for use, reproduction, 10 | and distribution as defined by Sections 1 through 9 of this document. 11 | 12 | "Licensor" shall mean the copyright owner or entity authorized by 13 | the copyright owner that is granting the License. 14 | 15 | "Legal Entity" shall mean the union of the acting entity and all 16 | other entities that control, are controlled by, or are under common 17 | control with that entity. For the purposes of this definition, 18 | "control" means (i) the power, direct or indirect, to cause the 19 | direction or management of such entity, whether by contract or 20 | otherwise, or (ii) ownership of fifty percent (50%) or more of the 21 | outstanding shares, or (iii) beneficial ownership of such entity. 22 | 23 | "You" (or "Your") shall mean an individual or Legal Entity 24 | exercising permissions granted by this License. 25 | 26 | "Source" form shall mean the preferred form for making modifications, 27 | including but not limited to software source code, documentation 28 | source, and configuration files. 29 | 30 | "Object" form shall mean any form resulting from mechanical 31 | transformation or translation of a Source form, including but 32 | not limited to compiled object code, generated documentation, 33 | and conversions to other media types. 34 | 35 | "Work" shall mean the work of authorship, whether in Source or 36 | Object form, made available under the License, as indicated by a 37 | copyright notice that is included in or attached to the work 38 | (an example is provided in the Appendix below). 39 | 40 | "Derivative Works" shall mean any work, whether in Source or Object 41 | form, that is based on (or derived from) the Work and for which the 42 | editorial revisions, annotations, elaborations, or other modifications 43 | represent, as a whole, an original work of authorship. For the purposes 44 | of this License, Derivative Works shall not include works that remain 45 | separable from, or merely link (or bind by name) to the interfaces of, 46 | the Work and Derivative Works thereof. 47 | 48 | "Contribution" shall mean any work of authorship, including 49 | the original version of the Work and any modifications or additions 50 | to that Work or Derivative Works thereof, that is intentionally 51 | submitted to Licensor for inclusion in the Work by the copyright owner 52 | or by an individual or Legal Entity authorized to submit on behalf of 53 | the copyright owner. For the purposes of this definition, "submitted" 54 | means any form of electronic, verbal, or written communication sent 55 | to the Licensor or its representatives, including but not limited to 56 | communication on electronic mailing lists, source code control systems, 57 | and issue tracking systems that are managed by, or on behalf of, the 58 | Licensor for the purpose of discussing and improving the Work, but 59 | excluding communication that is conspicuously marked or otherwise 60 | designated in writing by the copyright owner as "Not a Contribution." 61 | 62 | "Contributor" shall mean Licensor and any individual or Legal Entity 63 | on behalf of whom a Contribution has been received by Licensor and 64 | subsequently incorporated within the Work. 65 | 66 | 2. Grant of Copyright License. Subject to the terms and conditions of 67 | this License, each Contributor hereby grants to You a perpetual, 68 | worldwide, non-exclusive, no-charge, royalty-free, irrevocable 69 | copyright license to reproduce, prepare Derivative Works of, 70 | publicly display, publicly perform, sublicense, and distribute the 71 | Work and such Derivative Works in Source or Object form. 72 | 73 | 3. Grant of Patent License. Subject to the terms and conditions of 74 | this License, each Contributor hereby grants to You a perpetual, 75 | worldwide, non-exclusive, no-charge, royalty-free, irrevocable 76 | (except as stated in this section) patent license to make, have made, 77 | use, offer to sell, sell, import, and otherwise transfer the Work, 78 | where such license applies only to those patent claims licensable 79 | by such Contributor that are necessarily infringed by their 80 | Contribution(s) alone or by combination of their Contribution(s) 81 | with the Work to which such Contribution(s) was submitted. If You 82 | institute patent litigation against any entity (including a 83 | cross-claim or counterclaim in a lawsuit) alleging that the Work 84 | or a Contribution incorporated within the Work constitutes direct 85 | or contributory patent infringement, then any patent licenses 86 | granted to You under this License for that Work shall terminate 87 | as of the date such litigation is filed. 88 | 89 | 4. Redistribution. You may reproduce and distribute copies of the 90 | Work or Derivative Works thereof in any medium, with or without 91 | modifications, and in Source or Object form, provided that You 92 | meet the following conditions: 93 | 94 | (a) You must give any other recipients of the Work or 95 | Derivative Works a copy of this License; and 96 | 97 | (b) You must cause any modified files to carry prominent notices 98 | stating that You changed the files; and 99 | 100 | (c) You must retain, in the Source form of any Derivative Works 101 | that You distribute, all copyright, patent, trademark, and 102 | attribution notices from the Source form of the Work, 103 | excluding those notices that do not pertain to any part of 104 | the Derivative Works; and 105 | 106 | (d) If the Work includes a "NOTICE" text file as part of its 107 | distribution, then any Derivative Works that You distribute must 108 | include a readable copy of the attribution notices contained 109 | within such NOTICE file, excluding those notices that do not 110 | pertain to any part of the Derivative Works, in at least one 111 | of the following places: within a NOTICE text file distributed 112 | as part of the Derivative Works; within the Source form or 113 | documentation, if provided along with the Derivative Works; or, 114 | within a display generated by the Derivative Works, if and 115 | wherever such third-party notices normally appear. The contents 116 | of the NOTICE file are for informational purposes only and 117 | do not modify the License. You may add Your own attribution 118 | notices within Derivative Works that You distribute, alongside 119 | or as an addendum to the NOTICE text from the Work, provided 120 | that such additional attribution notices cannot be construed 121 | as modifying the License. 122 | 123 | You may add Your own copyright statement to Your modifications and 124 | may provide additional or different license terms and conditions 125 | for use, reproduction, or distribution of Your modifications, or 126 | for any such Derivative Works as a whole, provided Your use, 127 | reproduction, and distribution of the Work otherwise complies with 128 | the conditions stated in this License. 129 | 130 | 5. Submission of Contributions. Unless You explicitly state otherwise, 131 | any Contribution intentionally submitted for inclusion in the Work 132 | by You to the Licensor shall be under the terms and conditions of 133 | this License, without any additional terms or conditions. 134 | Notwithstanding the above, nothing herein shall supersede or modify 135 | the terms of any separate license agreement you may have executed 136 | with Licensor regarding such Contributions. 137 | 138 | 6. Trademarks. This License does not grant permission to use the trade 139 | names, trademarks, service marks, or product names of the Licensor, 140 | except as required for reasonable and customary use in describing the 141 | origin of the Work and reproducing the content of the NOTICE file. 142 | 143 | 7. Disclaimer of Warranty. Unless required by applicable law or 144 | agreed to in writing, Licensor provides the Work (and each 145 | Contributor provides its Contributions) on an "AS IS" BASIS, 146 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or 147 | implied, including, without limitation, any warranties or conditions 148 | of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A 149 | PARTICULAR PURPOSE. You are solely responsible for determining the 150 | appropriateness of using or redistributing the Work and assume any 151 | risks associated with Your exercise of permissions under this License. 152 | 153 | 8. Limitation of Liability. In no event and under no legal theory, 154 | whether in tort (including negligence), contract, or otherwise, 155 | unless required by applicable law (such as deliberate and grossly 156 | negligent acts) or agreed to in writing, shall any Contributor be 157 | liable to You for damages, including any direct, indirect, special, 158 | incidental, or consequential damages of any character arising as a 159 | result of this License or out of the use or inability to use the 160 | Work (including but not limited to damages for loss of goodwill, 161 | work stoppage, computer failure or malfunction, or any and all 162 | other commercial damages or losses), even if such Contributor 163 | has been advised of the possibility of such damages. 164 | 165 | 9. Accepting Warranty or Additional Liability. While redistributing 166 | the Work or Derivative Works thereof, You may choose to offer, 167 | and charge a fee for, acceptance of support, warranty, indemnity, 168 | or other liability obligations and/or rights consistent with this 169 | License. However, in accepting such obligations, You may act only 170 | on Your own behalf and on Your sole responsibility, not on behalf 171 | of any other Contributor, and only if You agree to indemnify, 172 | defend, and hold each Contributor harmless for any liability 173 | incurred by, or claims asserted against, such Contributor by reason 174 | of your accepting any such warranty or additional liability. 175 | 176 | END OF TERMS AND CONDITIONS 177 | 178 | APPENDIX: How to apply the Apache License to your work. 179 | 180 | To apply the Apache License to your work, attach the following 181 | boilerplate notice, with the fields enclosed by brackets "[]" 182 | replaced with your own identifying information. (Don't include 183 | the brackets!) The text should be enclosed in the appropriate 184 | comment syntax for the file format. We also recommend that a 185 | file or class name and description of purpose be included on the 186 | same "printed page" as the copyright notice for easier 187 | identification within third-party archives. 188 | 189 | Copyright [yyyy] [name of copyright owner] 190 | 191 | Licensed under the Apache License, Version 2.0 (the "License"); 192 | you may not use this file except in compliance with the License. 193 | You may obtain a copy of the License at 194 | 195 | http://www.apache.org/licenses/LICENSE-2.0 196 | 197 | Unless required by applicable law or agreed to in writing, software 198 | distributed under the License is distributed on an "AS IS" BASIS, 199 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 200 | See the License for the specific language governing permissions and 201 | limitations under the License. 202 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Face Detector with React and Tensorflow.js 2 | 3 | Demo at [https://react-face-detector.netlify.app/](https://react-face-detector.netlify.app/) 4 | 5 | ![](https://habrastorage.org/webt/rs/bv/jt/rsbvjtkakpnlda69bhdbo35lfty.png) 6 | 7 | It was challenging to find online an example of: 8 | 9 | 1. React 10 | 2. Typescript 11 | 3. Tensorflow.js 12 | 4. Drawing the result on Canvas 13 | 14 | in one place. Hence, I created this repo for future reference. 15 | 16 | ## Install 17 | 18 | ``` 19 | npm install 20 | ``` 21 | 22 | ## Start in development mode 23 | 24 | ``` 25 | npm start 26 | ``` 27 | -------------------------------------------------------------------------------- /package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "react_face_detection", 3 | "version": "0.1.0", 4 | "private": true, 5 | "dependencies": { 6 | "@tensorflow/tfjs": "^3.9.0", 7 | "@vladmandic/face-api": "^1.5.3", 8 | "bootstrap": "^5.1.0", 9 | "react": "^17.0.2", 10 | "react-bootstrap": "^2.0.0-beta.6", 11 | "react-dom": "^17.0.2", 12 | "react-scripts": "^4.0.3" 13 | }, 14 | "scripts": { 15 | "start": "react-scripts start", 16 | "build": "GENERATE_SOURCEMAP=false react-scripts build", 17 | "test": "react-scripts test", 18 | "eject": "react-scripts eject" 19 | }, 20 | "eslintConfig": { 21 | "extends": [ 22 | "react-app", 23 | "react-app/jest" 24 | ] 25 | }, 26 | "browserslist": { 27 | "production": [ 28 | ">0.2%", 29 | "not dead", 30 | "not op_mini all" 31 | ], 32 | "development": [ 33 | "last 1 chrome version", 34 | "last 1 firefox version", 35 | "last 1 safari version" 36 | ] 37 | }, 38 | "devDependencies": { 39 | "@testing-library/jest-dom": "^5.14.1", 40 | "@testing-library/react": "^12.1.0", 41 | "@testing-library/user-event": "^13.2.1", 42 | "@types/node": "^16.9.6", 43 | "@types/react": "^17.0.24", 44 | "@types/react-dom": "^17.0.9", 45 | "@typescript-eslint/eslint-plugin": "^4.31.2", 46 | "@typescript-eslint/parser": "^4.31.2", 47 | "eslint": "^7.32.0", 48 | "eslint-config-airbnb": "^18.2.1", 49 | "eslint-import-resolver-typescript": "^2.5.0", 50 | "eslint-plugin-import": "^2.24.2", 51 | "eslint-plugin-prettier": "4.0.0", 52 | "prettier": "2.4.1", 53 | "typescript": "^4.4.3" 54 | } 55 | } 56 | -------------------------------------------------------------------------------- /public/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 11 | 20 | React App 21 | 22 | 23 | 24 |
25 | 35 | 36 | 37 | -------------------------------------------------------------------------------- /public/models/ssd_mobilenetv1_model-weights_manifest.json: -------------------------------------------------------------------------------- 1 | [ 2 | { 3 | "weights": 4 | [ 5 | {"dtype":"float32","shape":[1,1,512,9],"quantization":{"scale":0.0026856216729856004,"min":-0.34107395246917127,"dtype":"uint8"},"name":"Prediction/BoxPredictor_0/ClassPredictor/weights"}, 6 | {"dtype":"float32","shape":[9],"quantization":{"scale":0.00198518248165355,"min":-0.32159956202787515,"dtype":"uint8"},"name":"Prediction/BoxPredictor_0/ClassPredictor/biases"}, 7 | {"dtype":"float32","shape":[1,1,1024,18],"quantization":{"scale":0.003060340296988394,"min":-0.489654447518143,"dtype":"uint8"},"name":"Prediction/BoxPredictor_1/ClassPredictor/weights"}, 8 | {"dtype":"float32","shape":[18],"quantization":{"scale":0.0008040678851744708,"min":-0.12221831854651957,"dtype":"uint8"},"name":"Prediction/BoxPredictor_1/ClassPredictor/biases"}, 9 | {"dtype":"float32","shape":[1,1,512,18],"quantization":{"scale":0.0012513800578958848,"min":-0.16017664741067325,"dtype":"uint8"},"name":"Prediction/BoxPredictor_2/ClassPredictor/weights"}, 10 | {"dtype":"float32","shape":[18],"quantization":{"scale":0.000338070518245884,"min":-0.05510549447407909,"dtype":"uint8"},"name":"Prediction/BoxPredictor_2/ClassPredictor/biases"}, 11 | {"dtype":"float32","shape":[1,1,256,18],"quantization":{"scale":0.0011819932975021064,"min":-0.1453851755927591,"dtype":"uint8"},"name":"Prediction/BoxPredictor_3/ClassPredictor/weights"}, 12 | {"dtype":"float32","shape":[18],"quantization":{"scale":0.00015985782386041154,"min":-0.026536398760828316,"dtype":"uint8"},"name":"Prediction/BoxPredictor_3/ClassPredictor/biases"}, 13 | {"dtype":"float32","shape":[1,1,256,18],"quantization":{"scale":0.0007035591438704846,"min":-0.08513065640832863,"dtype":"uint8"},"name":"Prediction/BoxPredictor_4/ClassPredictor/weights"}, 14 | {"dtype":"float32","shape":[18],"quantization":{"scale":0.00008793946574716008,"min":-0.013190919862074012,"dtype":"uint8"},"name":"Prediction/BoxPredictor_4/ClassPredictor/biases"}, 15 | {"dtype":"float32","shape":[1,1,128,18],"quantization":{"scale":0.00081320781918133,"min":-0.11059626340866088,"dtype":"uint8"},"name":"Prediction/BoxPredictor_5/ClassPredictor/weights"}, 16 | {"dtype":"float32","shape":[18],"quantization":{"scale":0.0000980533805547976,"min":-0.014609953702664841,"dtype":"uint8"},"name":"Prediction/BoxPredictor_5/ClassPredictor/biases"}, 17 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":3,"dtype":"uint8"},"name":"Prediction/BoxPredictor_0/stack_1/2"}, 18 | {"dtype":"int32","shape":[3],"quantization":{"scale":0.00392156862745098,"min":0,"dtype":"uint8"},"name":"Postprocessor/Slice/begin"}, 19 | {"dtype":"int32","shape":[3],"quantization":{"scale":1,"min":-1,"dtype":"uint8"},"name":"Postprocessor/Slice/size"}, 20 | {"dtype":"float32","shape":[1,1,512,12],"quantization":{"scale":0.003730384859384275,"min":-0.4327246436885759,"dtype":"uint8"},"name":"Prediction/BoxPredictor_0/BoxEncodingPredictor/weights"}, 21 | {"dtype":"float32","shape":[12],"quantization":{"scale":0.0018744708568442102,"min":-0.3917644090804399,"dtype":"uint8"},"name":"Prediction/BoxPredictor_0/BoxEncodingPredictor/biases"}, 22 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":3072,"dtype":"uint8"},"name":"Prediction/BoxPredictor_0/stack_1/1"}, 23 | {"dtype":"float32","shape":[1,1,1024,24],"quantization":{"scale":0.00157488017689948,"min":-0.20000978246623397,"dtype":"uint8"},"name":"Prediction/BoxPredictor_1/BoxEncodingPredictor/weights"}, 24 | {"dtype":"float32","shape":[24],"quantization":{"scale":0.0002823906713256649,"min":-0.043488163384152394,"dtype":"uint8"},"name":"Prediction/BoxPredictor_1/BoxEncodingPredictor/biases"}, 25 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":1536,"dtype":"uint8"},"name":"Prediction/BoxPredictor_1/stack_1/1"}, 26 | {"dtype":"float32","shape":[1,1,512,24],"quantization":{"scale":0.0007974451663447361,"min":-0.11004743295557358,"dtype":"uint8"},"name":"Prediction/BoxPredictor_2/BoxEncodingPredictor/weights"}, 27 | {"dtype":"float32","shape":[24],"quantization":{"scale":0.0001350417988849621,"min":-0.02039131163162928,"dtype":"uint8"},"name":"Prediction/BoxPredictor_2/BoxEncodingPredictor/biases"}, 28 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":384,"dtype":"uint8"},"name":"Prediction/BoxPredictor_2/stack_1/1"}, 29 | {"dtype":"float32","shape":[1,1,256,24],"quantization":{"scale":0.0007113990246080885,"min":-0.0860792819775787,"dtype":"uint8"},"name":"Prediction/BoxPredictor_3/BoxEncodingPredictor/weights"}, 30 | {"dtype":"float32","shape":[24],"quantization":{"scale":0.000050115815418608046,"min":-0.007617603943628423,"dtype":"uint8"},"name":"Prediction/BoxPredictor_3/BoxEncodingPredictor/biases"}, 31 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":96,"dtype":"uint8"},"name":"Prediction/BoxPredictor_3/stack_1/1"}, 32 | {"dtype":"float32","shape":[1,1,256,24],"quantization":{"scale":0.000590049314732645,"min":-0.06903576982371946,"dtype":"uint8"},"name":"Prediction/BoxPredictor_4/BoxEncodingPredictor/weights"}, 33 | {"dtype":"float32","shape":[24],"quantization":{"scale":0.00003513663861097074,"min":-0.006359731588585704,"dtype":"uint8"},"name":"Prediction/BoxPredictor_4/BoxEncodingPredictor/biases"}, 34 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":24,"dtype":"uint8"},"name":"Prediction/BoxPredictor_4/stack_1/1"}, 35 | {"dtype":"float32","shape":[1,1,128,24],"quantization":{"scale":0.0005990567744946948,"min":-0.07907549423329971,"dtype":"uint8"},"name":"Prediction/BoxPredictor_5/BoxEncodingPredictor/weights"}, 36 | {"dtype":"float32","shape":[24],"quantization":{"scale":0.00003392884288640583,"min":-0.006039334033780238,"dtype":"uint8"},"name":"Prediction/BoxPredictor_5/BoxEncodingPredictor/biases"}, 37 | {"dtype":"float32","shape":[],"quantization":{"scale":1,"min":0.007843137718737125,"dtype":"uint8"},"name":"Preprocessor/mul/x"}, 38 | {"dtype":"int32","shape":[2],"quantization":{"scale":1,"min":512,"dtype":"uint8"},"name":"Preprocessor/ResizeImage/size"}, 39 | {"dtype":"float32","shape":[],"quantization":{"scale":1,"min":1,"dtype":"uint8"},"name":"Preprocessor/sub/y"}, 40 | {"dtype":"float32","shape":[3,3,3,32],"quantization":{"scale":0.03948551065781537,"min":-5.014659853542552,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_0_pointwise/weights"}, 41 | {"dtype":"float32","shape":[32],"quantization":{"scale":0.0498106133704092,"min":-7.371970778820562,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_0_pointwise/convolution_bn_offset"}, 42 | {"dtype":"float32","shape":[3,3,32,1],"quantization":{"scale":0.036833542468501075,"min":-4.714693435968138,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_1_depthwise/depthwise_weights"}, 43 | {"dtype":"float32","shape":[32],"quantization":{"scale":0.012173276705046495,"min":-0.012173276705046495,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_1_depthwise/BatchNorm/gamma"}, 44 | {"dtype":"float32","shape":[32],"quantization":{"scale":0.032182769214405736,"min":-2.4780732295092416,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_1_depthwise/BatchNorm/beta"}, 45 | {"dtype":"float32","shape":[32],"quantization":{"scale":0.028287527607936486,"min":-3.366215785344442,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_1_depthwise/BatchNorm/moving_mean"}, 46 | {"dtype":"float32","shape":[32],"quantization":{"scale":0.04716738532571232,"min":3.9071404665769224e-36,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_1_depthwise/BatchNorm/moving_variance"}, 47 | {"dtype":"float32","shape":[1,1,32,64],"quantization":{"scale":0.04010109433940812,"min":-4.290817094316669,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_1_pointwise/weights"}, 48 | {"dtype":"float32","shape":[64],"quantization":{"scale":0.2212210038129021,"min":-34.51047659481273,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_1_pointwise/convolution_bn_offset"}, 49 | {"dtype":"float32","shape":[3,3,64,1],"quantization":{"scale":0.010024750933927648,"min":-1.343316625146305,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_2_depthwise/depthwise_weights"}, 50 | {"dtype":"float32","shape":[64],"quantization":{"scale":0.006120916675118839,"min":0.5227176547050476,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_2_depthwise/BatchNorm/gamma"}, 51 | {"dtype":"float32","shape":[64],"quantization":{"scale":0.02317035385206634,"min":-0.7646216771181892,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_2_depthwise/BatchNorm/beta"}, 52 | {"dtype":"float32","shape":[64],"quantization":{"scale":0.04980821422502106,"min":-5.8275610643274645,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_2_depthwise/BatchNorm/moving_mean"}, 53 | {"dtype":"float32","shape":[64],"quantization":{"scale":0.051751047022202436,"min":3.916113799002297e-36,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_2_depthwise/BatchNorm/moving_variance"}, 54 | {"dtype":"float32","shape":[1,1,64,128],"quantization":{"scale":0.021979344124887504,"min":-2.1319963801140878,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_2_pointwise/weights"}, 55 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.09958663267247816,"min":-11.054116226645077,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_2_pointwise/convolution_bn_offset"}, 56 | {"dtype":"float32","shape":[3,3,128,1],"quantization":{"scale":0.01943492702409333,"min":-2.6237151482525993,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_3_depthwise/depthwise_weights"}, 57 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.017852897737540452,"min":0.40204083919525146,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_3_depthwise/BatchNorm/gamma"}, 58 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.029888209174661076,"min":-1.972621805527631,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_3_depthwise/BatchNorm/beta"}, 59 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.029319268581913967,"min":-5.130872001834945,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_3_depthwise/BatchNorm/moving_mean"}, 60 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.014018708584355373,"min":3.9083178263362604e-36,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_3_depthwise/BatchNorm/moving_variance"}, 61 | {"dtype":"float32","shape":[1,1,128,128],"quantization":{"scale":0.020776657964669022,"min":-2.5347522716896207,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_3_pointwise/weights"}, 62 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.14383157094319662,"min":-9.636715253194174,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_3_pointwise/convolution_bn_offset"}, 63 | {"dtype":"float32","shape":[3,3,128,1],"quantization":{"scale":0.004463558571011412,"min":-0.5981168485155293,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_4_depthwise/depthwise_weights"}, 64 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.006487431245691636,"min":0.47910428047180176,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_4_depthwise/BatchNorm/gamma"}, 65 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.026542164297664865,"min":-1.2209395576925839,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_4_depthwise/BatchNorm/beta"}, 66 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.05119945675719018,"min":-8.60150873520795,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_4_depthwise/BatchNorm/moving_mean"}, 67 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.03081628388049556,"min":3.911508751095344e-36,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_4_depthwise/BatchNorm/moving_variance"}, 68 | {"dtype":"float32","shape":[1,1,128,256],"quantization":{"scale":0.010758659886378868,"min":-1.0328313490923713,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_4_pointwise/weights"}, 69 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.08058219610476026,"min":-9.34753474815219,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_4_pointwise/convolution_bn_offset"}, 70 | {"dtype":"float32","shape":[3,3,256,1],"quantization":{"scale":0.01145936741548426,"min":-1.3292866201961742,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_5_depthwise/depthwise_weights"}, 71 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.0083988838336047,"min":0.36280909180641174,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_5_depthwise/BatchNorm/gamma"}, 72 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.02858148649627087,"min":-3.6584302715226715,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_5_depthwise/BatchNorm/beta"}, 73 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.03988401375564874,"min":-7.099354448505476,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_5_depthwise/BatchNorm/moving_mean"}, 74 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.009090481683904049,"min":0.020878996700048447,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_5_depthwise/BatchNorm/moving_variance"}, 75 | {"dtype":"float32","shape":[1,1,256,256],"quantization":{"scale":0.008951201625898773,"min":-1.1189002032373465,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_5_pointwise/weights"}, 76 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.051758006974762565,"min":-5.745138774198645,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_5_pointwise/convolution_bn_offset"}, 77 | {"dtype":"float32","shape":[3,3,256,1],"quantization":{"scale":0.004110433190476661,"min":-0.6042336790000691,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_6_depthwise/depthwise_weights"}, 78 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.013170199768216002,"min":0.3386639356613159,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_6_depthwise/BatchNorm/gamma"}, 79 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.03599378548416437,"min":-3.70735990486893,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_6_depthwise/BatchNorm/beta"}, 80 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.026967673208199296,"min":-3.748506575939702,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_6_depthwise/BatchNorm/moving_mean"}, 81 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.012615410486857097,"min":3.9111388979838637e-36,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_6_depthwise/BatchNorm/moving_variance"}, 82 | {"dtype":"float32","shape":[1,1,256,512],"quantization":{"scale":0.00822840648538926,"min":-1.1848905338960536,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_6_pointwise/weights"}, 83 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.06608965817619772,"min":-7.468131373910342,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_6_pointwise/convolution_bn_offset"}, 84 | {"dtype":"float32","shape":[3,3,512,1],"quantization":{"scale":0.008801074355256323,"min":-0.9593171047229393,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_7_depthwise/depthwise_weights"}, 85 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.030577416513480393,"min":0.3285980224609375,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_7_depthwise/BatchNorm/gamma"}, 86 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.04778536441279393,"min":-8.935863145192464,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_7_depthwise/BatchNorm/beta"}, 87 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.04331884945140165,"min":-9.660103427662568,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_7_depthwise/BatchNorm/moving_mean"}, 88 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.04126455444367785,"min":0.000604183878749609,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_7_depthwise/BatchNorm/moving_variance"}, 89 | {"dtype":"float32","shape":[1,1,512,512],"quantization":{"scale":0.009305818408143287,"min":-1.1446156642016243,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_7_pointwise/weights"}, 90 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.04640720217835669,"min":-4.733534622192383,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_7_pointwise/convolution_bn_offset"}, 91 | {"dtype":"float32","shape":[3,3,512,1],"quantization":{"scale":0.008138792655047248,"min":-0.9766551186056698,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_8_depthwise/depthwise_weights"}, 92 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.027351748358969596,"min":0.34030041098594666,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_8_depthwise/BatchNorm/gamma"}, 93 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.04415061053107767,"min":-7.019947074441349,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_8_depthwise/BatchNorm/beta"}, 94 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.02476683784933651,"min":-2.9224868662217083,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_8_depthwise/BatchNorm/moving_mean"}, 95 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.02547598832684076,"min":0.00026032101595774293,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_8_depthwise/BatchNorm/moving_variance"}, 96 | {"dtype":"float32","shape":[1,1,512,512],"quantization":{"scale":0.01083052625843123,"min":-1.2563410459780227,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_8_pointwise/weights"}, 97 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.06360894371481503,"min":-7.951117964351878,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_8_pointwise/convolution_bn_offset"}, 98 | {"dtype":"float32","shape":[3,3,512,1],"quantization":{"scale":0.006704086883395326,"min":-0.8648272079579971,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_9_depthwise/depthwise_weights"}, 99 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.015343831567203297,"min":0.2711026668548584,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_9_depthwise/BatchNorm/gamma"}, 100 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.03378283930759804,"min":-4.797163181678922,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_9_depthwise/BatchNorm/beta"}, 101 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.021910778213949763,"min":-3.987761634938857,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_9_depthwise/BatchNorm/moving_mean"}, 102 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.009284070410007296,"min":0.000021581046894425526,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_9_depthwise/BatchNorm/moving_variance"}, 103 | {"dtype":"float32","shape":[1,1,512,512],"quantization":{"scale":0.012783036979974485,"min":-1.9046725100161983,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_9_pointwise/weights"}, 104 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.07273082733154297,"min":-9.52773838043213,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_9_pointwise/convolution_bn_offset"}, 105 | {"dtype":"float32","shape":[3,3,512,1],"quantization":{"scale":0.006126228033327589,"min":-0.7351473639993107,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_10_depthwise/depthwise_weights"}, 106 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.029703759212119908,"min":0.28687000274658203,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_10_depthwise/BatchNorm/gamma"}, 107 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.04394429898729511,"min":-6.3279790541704966,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_10_depthwise/BatchNorm/beta"}, 108 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.016566915605582443,"min":-2.7501079905266854,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_10_depthwise/BatchNorm/moving_mean"}, 109 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.012152872833551145,"min":3.913338286370366e-36,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_10_depthwise/BatchNorm/moving_variance"}, 110 | {"dtype":"float32","shape":[1,1,512,512],"quantization":{"scale":0.01354524388032801,"min":-1.7473364605623134,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_10_pointwise/weights"}, 111 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.08566816367355047,"min":-9.937506986131854,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_10_pointwise/convolution_bn_offset"}, 112 | {"dtype":"float32","shape":[3,3,512,1],"quantization":{"scale":0.006012305558896532,"min":-0.7876120282154457,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_11_depthwise/depthwise_weights"}, 113 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.01469323155926723,"min":0.29223933815956116,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_11_depthwise/BatchNorm/gamma"}, 114 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.030889174517463234,"min":-3.2433633243336395,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_11_depthwise/BatchNorm/beta"}, 115 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.014836942448335536,"min":-2.047498057870304,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_11_depthwise/BatchNorm/moving_mean"}, 116 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.007234466105343445,"min":0.00013165915152058005,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_11_depthwise/BatchNorm/moving_variance"}, 117 | {"dtype":"float32","shape":[1,1,512,512],"quantization":{"scale":0.016261722527298274,"min":-1.4798167499841428,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_11_pointwise/weights"}, 118 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.091437328563017,"min":-14.172785927267636,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_11_pointwise/convolution_bn_offset"}, 119 | {"dtype":"float32","shape":[3,3,512,1],"quantization":{"scale":0.004750356487199372,"min":-0.650798838746314,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_12_depthwise/depthwise_weights"}, 120 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.008174965545242907,"min":0.3120670020580292,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_12_depthwise/BatchNorm/gamma"}, 121 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.030133422215779623,"min":-2.41067377726237,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_12_depthwise/BatchNorm/beta"}, 122 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.006088157261119169,"min":-0.7853722866843729,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_12_depthwise/BatchNorm/moving_mean"}, 123 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.003668997334498985,"min":3.9124486300013356e-36,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_12_depthwise/BatchNorm/moving_variance"}, 124 | {"dtype":"float32","shape":[1,1,512,1024],"quantization":{"scale":0.010959514449624454,"min":-1.4028178495519301,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_12_pointwise/weights"}, 125 | {"dtype":"float32","shape":[1024],"quantization":{"scale":0.10896045834410424,"min":-14.818622334798176,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_12_pointwise/convolution_bn_offset"}, 126 | {"dtype":"float32","shape":[3,3,1024,1],"quantization":{"scale":0.004633033509347953,"min":-0.5652300881404502,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_13_depthwise/depthwise_weights"}, 127 | {"dtype":"float32","shape":[1024],"quantization":{"scale":0.022285057224479377,"min":0.23505790531635284,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_13_depthwise/BatchNorm/gamma"}, 128 | {"dtype":"float32","shape":[1024],"quantization":{"scale":0.0324854850769043,"min":-3.9957146644592285,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_13_depthwise/BatchNorm/beta"}, 129 | {"dtype":"float32","shape":[1024],"quantization":{"scale":0.014760061806323482,"min":-2.125448900110581,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_13_depthwise/BatchNorm/moving_mean"}, 130 | {"dtype":"float32","shape":[1024],"quantization":{"scale":0.0036057423142825855,"min":3.9067056828997994e-36,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_13_depthwise/BatchNorm/moving_variance"}, 131 | {"dtype":"float32","shape":[1,1,1024,1024],"quantization":{"scale":0.017311988157384536,"min":-2.094750567043529,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_13_pointwise/weights"}, 132 | {"dtype":"float32","shape":[1024],"quantization":{"scale":0.16447528764313343,"min":-25.658144872328815,"dtype":"uint8"},"name":"MobilenetV1/Conv2d_13_pointwise/convolution_bn_offset"}, 133 | {"dtype":"float32","shape":[1,1,1024,256],"quantization":{"scale":0.0026493051472832175,"min":-0.36825341547236723,"dtype":"uint8"},"name":"Prediction/Conv2d_0_pointwise/weights"}, 134 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.012474596734140433,"min":-2.3078003958159803,"dtype":"uint8"},"name":"Prediction/Conv2d_0_pointwise/convolution_bn_offset"}, 135 | {"dtype":"float32","shape":[3,3,256,512],"quantization":{"scale":0.014533351449405445,"min":-1.8166689311756807,"dtype":"uint8"},"name":"Prediction/Conv2d_1_pointwise/weights"}, 136 | {"dtype":"float32","shape":[512],"quantization":{"scale":0.024268776762719248,"min":-2.4754152297973633,"dtype":"uint8"},"name":"Prediction/Conv2d_1_pointwise/convolution_bn_offset"}, 137 | {"dtype":"float32","shape":[1,1,512,128],"quantization":{"scale":0.002208403746287028,"min":-0.28709248701731366,"dtype":"uint8"},"name":"Prediction/Conv2d_2_pointwise/weights"}, 138 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.012451349052728392,"min":-1.5937726787492341,"dtype":"uint8"},"name":"Prediction/Conv2d_2_pointwise/convolution_bn_offset"}, 139 | {"dtype":"float32","shape":[3,3,128,256],"quantization":{"scale":0.026334229637594783,"min":-2.8967652601354263,"dtype":"uint8"},"name":"Prediction/Conv2d_3_pointwise/weights"}, 140 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.02509917792151956,"min":-1.4055539636050953,"dtype":"uint8"},"name":"Prediction/Conv2d_3_pointwise/convolution_bn_offset"}, 141 | {"dtype":"float32","shape":[1,1,256,128],"quantization":{"scale":0.004565340046789132,"min":-0.3971845840706545,"dtype":"uint8"},"name":"Prediction/Conv2d_4_pointwise/weights"}, 142 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.017302456556581983,"min":-2.5953684834872974,"dtype":"uint8"},"name":"Prediction/Conv2d_4_pointwise/convolution_bn_offset"}, 143 | {"dtype":"float32","shape":[3,3,128,256],"quantization":{"scale":0.025347338470758176,"min":-3.8527954475552426,"dtype":"uint8"},"name":"Prediction/Conv2d_5_pointwise/weights"}, 144 | {"dtype":"float32","shape":[256],"quantization":{"scale":0.033134659598855414,"min":-2.9158500446992766,"dtype":"uint8"},"name":"Prediction/Conv2d_5_pointwise/convolution_bn_offset"}, 145 | {"dtype":"float32","shape":[1,1,256,64],"quantization":{"scale":0.002493104397081861,"min":-0.2817207968702503,"dtype":"uint8"},"name":"Prediction/Conv2d_6_pointwise/weights"}, 146 | {"dtype":"float32","shape":[64],"quantization":{"scale":0.011383360974928912,"min":-1.2749364291920382,"dtype":"uint8"},"name":"Prediction/Conv2d_6_pointwise/convolution_bn_offset"}, 147 | {"dtype":"float32","shape":[3,3,64,128],"quantization":{"scale":0.020821522731407017,"min":-2.7484410005457263,"dtype":"uint8"},"name":"Prediction/Conv2d_7_pointwise/weights"}, 148 | {"dtype":"float32","shape":[128],"quantization":{"scale":0.052144218893612135,"min":-3.5979511036592373,"dtype":"uint8"},"name":"Prediction/Conv2d_7_pointwise/convolution_bn_offset"}, 149 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":6,"dtype":"uint8"},"name":"Prediction/BoxPredictor_5/stack_1/1"}, 150 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":1,"dtype":"uint8"},"name":"concat_1/axis"}, 151 | {"dtype":"int32","shape":[1],"quantization":{"scale":1,"min":0,"dtype":"uint8"},"name":"Prediction/BoxPredictor_0/strided_slice/stack"}, 152 | {"dtype":"int32","shape":[1],"quantization":{"scale":1,"min":1,"dtype":"uint8"},"name":"Prediction/BoxPredictor_0/strided_slice/stack_1"}, 153 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":5118,"dtype":"uint8"},"name":"Postprocessor/stack/1"}, 154 | {"dtype":"int32","shape":[],"quantization":{"scale":1,"min":4,"dtype":"uint8"},"name":"Prediction/BoxPredictor_0/stack/3"}, 155 | {"dtype":"float32","shape":[1,5118,4],"name":"Output/extra_dim"} 156 | ], 157 | "paths": 158 | [ 159 | "ssd_mobilenetv1_model.bin" 160 | ] 161 | } 162 | ] -------------------------------------------------------------------------------- /public/models/ssd_mobilenetv1_model.bin: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ternaus/react_face_detection/1e2c3908d6ce4bec8259370920719f460ce63742/public/models/ssd_mobilenetv1_model.bin -------------------------------------------------------------------------------- /src/App.tsx: -------------------------------------------------------------------------------- 1 | import { Card, Container, Form } from "react-bootstrap"; 2 | 3 | import React, { useEffect, useState } from "react"; 4 | 5 | import { 6 | detectAllFaces, 7 | FaceDetection, 8 | nets, 9 | SsdMobilenetv1Options, 10 | } from "@vladmandic/face-api"; 11 | 12 | import * as tf from "@tensorflow/tfjs"; 13 | import Canvas from "./components/Canvas"; 14 | 15 | const MODEL_URL = "/models"; 16 | 17 | const App = () => { 18 | const [imageFile, setImageFile] = useState(); 19 | const [predictions, setPredictions] = useState(); 20 | const [image, setImage] = useState(); 21 | 22 | const loadModel = async () => { 23 | await nets.ssdMobilenetv1.loadFromUri(MODEL_URL); 24 | }; 25 | 26 | useEffect(() => { 27 | tf.ready().then(() => { 28 | loadModel(); 29 | }); 30 | }, []); 31 | 32 | const imageFieldChangeHandler = ( 33 | event: React.ChangeEvent 34 | ) => { 35 | setImageFile((event.target as HTMLInputElement).files![0]); 36 | }; 37 | 38 | const detectFaces = () => { 39 | if (!imageFile) return; 40 | 41 | const reader = new FileReader(); 42 | reader.onload = (e: any) => { 43 | const im = new Image(); 44 | im.src = e.target.result; 45 | im.onload = async () => { 46 | setImage(im); 47 | setPredictions( 48 | await detectAllFaces( 49 | im, 50 | new SsdMobilenetv1Options({ minConfidence: 0.6 }) 51 | ) 52 | ); 53 | }; 54 | }; 55 | reader.readAsDataURL(imageFile); 56 | }; 57 | 58 | useEffect(() => detectFaces(), [imageFile]); 59 | 60 | return ( 61 | 62 | 63 | 64 |
65 | 66 | Upload an image 67 | 72 | 73 |
74 |
75 |
76 | {predictions && } 77 |
78 | ); 79 | }; 80 | 81 | export default App; 82 | -------------------------------------------------------------------------------- /src/components/Canvas.tsx: -------------------------------------------------------------------------------- 1 | import React, { useRef, useState } from "react"; 2 | import { FaceDetection } from "@vladmandic/face-api"; 3 | 4 | const MAX_SIZE_IMAGE = 1024; // In pixels 5 | 6 | const Canvas: React.FC<{ 7 | predictions: FaceDetection[]; 8 | image: HTMLImageElement; 9 | }> = (props) => { 10 | const { predictions, image } = props; 11 | 12 | const { height, width } = image; 13 | 14 | let ratio: number; 15 | 16 | let canvasScreenWidth: string; 17 | let canvasScreenHeight: string; 18 | 19 | if (width / window.innerWidth > height / window.innerHeight) { 20 | ratio = MAX_SIZE_IMAGE / width; 21 | canvasScreenWidth = "80vw"; 22 | canvasScreenHeight = "auto"; 23 | } else { 24 | ratio = MAX_SIZE_IMAGE / height; 25 | canvasScreenWidth = "auto"; 26 | canvasScreenHeight = "80vh"; 27 | } 28 | 29 | const [observed, setObserved] = useState(false); 30 | const canvasRef = useRef(null); 31 | 32 | if (observed) { 33 | const ctx = canvasRef.current!.getContext("2d"); 34 | 35 | ctx!.font = "18px serif"; 36 | ctx!.fillStyle = "#ff0000"; 37 | ctx!.strokeStyle = "#ff0000"; 38 | 39 | ctx!.drawImage(image, 0, 0, image.width * ratio, image.height * ratio); 40 | 41 | ctx!.beginPath(); 42 | 43 | predictions.forEach((element) => { 44 | ctx!.fillText( 45 | element.classScore.toFixed(2), 46 | element.box.x * ratio, 47 | element.box.y * ratio - 10 48 | ); 49 | 50 | ctx!.rect( 51 | element.box.x * ratio, 52 | element.box.y * ratio, 53 | element.box.width * ratio, 54 | element.box.height * ratio 55 | ); 56 | }); 57 | ctx!.stroke(); 58 | } 59 | 60 | return ( 61 | <> 62 |
63 | {predictions.length === 0 &&

No faces detected

} 64 |
65 |
66 | { 68 | if (!observed) { 69 | setObserved(true); 70 | } 71 | /* @ts-ignore*/ 72 | canvasRef.current = element; 73 | }} 74 | style={{ 75 | width: `${canvasScreenWidth}`, 76 | height: `${canvasScreenHeight}`, 77 | marginRight: "auto", 78 | marginLeft: "auto", 79 | }} 80 | width={width * ratio} 81 | height={height * ratio} 82 | /> 83 |
84 | 85 | ); 86 | }; 87 | 88 | export default Canvas; 89 | -------------------------------------------------------------------------------- /src/index.tsx: -------------------------------------------------------------------------------- 1 | import React from "react"; 2 | import ReactDOM from "react-dom"; 3 | import App from "./App"; 4 | import "bootstrap/dist/css/bootstrap.css"; 5 | 6 | ReactDOM.render( 7 | 8 | 9 | , 10 | document.getElementById("root") 11 | ); 12 | -------------------------------------------------------------------------------- /tsconfig.json: -------------------------------------------------------------------------------- 1 | { 2 | "compilerOptions": { 3 | "target": "es6", 4 | "lib": [ 5 | "dom", 6 | "dom.iterable", 7 | "esnext" 8 | ], 9 | "allowJs": true, 10 | "skipLibCheck": true, 11 | "esModuleInterop": true, 12 | "allowSyntheticDefaultImports": true, 13 | "strict": true, 14 | "forceConsistentCasingInFileNames": true, 15 | "noFallthroughCasesInSwitch": true, 16 | "module": "esnext", 17 | "moduleResolution": "node", 18 | "resolveJsonModule": true, 19 | "isolatedModules": true, 20 | "noEmit": true, 21 | "jsx": "react-jsx" 22 | }, 23 | "include": [ 24 | "src" 25 | ] 26 | } 27 | --------------------------------------------------------------------------------