Gathering detailed insights and metrics for @tensorflow-models/coco-ssd
Gathering detailed insights and metrics for @tensorflow-models/coco-ssd
Pretrained models for TensorFlow.js
Installations
npm install @tensorflow-models/coco-ssdDeveloper Guide
BETA
Typescript
Yes
Module System
CommonJS
Node Version
20.5.0
NPM Version
9.8.0
Releases
2
Languages
7
TypeScript
Jupyter Notebook
JavaScript
HTML
Shell
CSS
SCSS
TypeScript (58.24%)
Jupyter Notebook (22.78%)
JavaScript (16.39%)
HTML (1.92%)
Shell (0.39%)
CSS (0.15%)
SCSS (0.14%)
Developer
Download Statistics
Total Downloads
0
Last Day
0
Last Week
0
Last Month
0
Last Year
0
GitHub Statistics
Apache-2.0 License
14,555 Stars
932 Commits
4,396 Forks
277 Watchers
396 Branches
141 Contributors
Updated on Jul 10, 2025
Maintainers
9
Package Meta Information
Latest Version
2.2.3
Package Id
@tensorflow-models/coco-ssd@2.2.3
Unpacked Size
261.80 kB
Size
61.42 kB
File Count
22
NPM Version
9.8.0
Node Version
20.5.0
Published on
Aug 22, 2023
Total Downloads
Cumulative downloads
Total Downloads
NaN
Last Day
0%
NaN
Compared to previous day
Last Week
0%
NaN
Compared to previous week
Last Month
0%
NaN
Compared to previous month
Last Year
0%
NaN
Compared to previous year
Weekly Downloads
Monthly Downloads
Yearly Downloads
Peer Dependencies
2
Dev Dependencies
18
Object Detection (coco-ssd)
Object detection model that aims to localize and identify multiple objects in a single image.
This model is a TensorFlow.js port of the COCO-SSD model. For more information about Tensorflow object detection API, check out this readme in tensorflow/object_detection.
This model detects objects defined in the COCO dataset, which is a large-scale object detection, segmentation, and captioning dataset. You can find more information here. The model is capable of detecting 80 classes of objects. (SSD stands for Single Shot MultiBox Detection).
This TensorFlow.js model does not require you to know about machine learning.
It can take input as any browser-based image elements (<img>, <video>, <canvas>
elements, for example) and returns an array of bounding boxes with class name and confidence level.
Usage
There are two main ways to get this model in your JavaScript project: via script tags or by installing it from NPM and using a build tool like Parcel, WebPack, or Rollup.
via Script Tag
1<!-- Load TensorFlow.js. This is required to use coco-ssd model. --> 2<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs"> </script> 3<!-- Load the coco-ssd model. --> 4<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/coco-ssd"> </script> 5 6<!-- Replace this with your image. Make sure CORS settings allow reading the image! --> 7<img id="img" src="cat.jpg"/> 8 9<!-- Place your code in the script tag below. You can also use an external .js file --> 10<script> 11 // Notice there is no 'import' statement. 'cocoSsd' and 'tf' is 12 // available on the index-page because of the script tag above. 13 14 const img = document.getElementById('img'); 15 16 // Load the model. 17 cocoSsd.load().then(model => { 18 // detect objects in the image. 19 model.detect(img).then(predictions => { 20 console.log('Predictions: ', predictions); 21 }); 22 }); 23</script>
via NPM
Note: The following shows how to use coco-ssd npm to transpile for web deployment, not an example on how to use coco-ssd in the node env.
1// Note: Require the cpu and webgl backend and add them to package.json as peer dependencies. 2require('@tensorflow/tfjs-backend-cpu'); 3require('@tensorflow/tfjs-backend-webgl'); 4const cocoSsd = require('@tensorflow-models/coco-ssd'); 5 6(async () => { 7 const img = document.getElementById('img'); 8 9 // Load the model. 10 const model = await cocoSsd.load(); 11 12 // Classify the image. 13 const predictions = await model.detect(img); 14 15 console.log('Predictions: '); 16 console.log(predictions); 17})();
You can also take a look at the demo app.
API
Loading the model
coco-ssd is the module name, which is automatically included when you use the <script src> method. When using ES6 imports, coco-ssd is the module.
1export interface ModelConfig { 2 base?: ObjectDetectionBaseModel; 3 modelUrl?: string; 4} 5 6cocoSsd.load(config: ModelConfig = {});
Args: config Type of ModelConfig interface with following attributes:
-
base: Controls the base cnn model, can be 'mobilenet_v1', 'mobilenet_v2' or 'lite_mobilenet_v2'. Defaults to 'lite_mobilenet_v2'. lite_mobilenet_v2 is smallest in size, and fastest in inference speed. mobilenet_v2 has the highest classification accuracy.
-
modelUrl: An optional string that specifies custom url of the model. This is useful for area/countries that don't have access to the model hosted on GCP.
Returns a model object.
Detecting the objects
You can detect objects with the model without needing to create a Tensor.
model.detect takes an input image element and returns an array of bounding boxes with class name and confidence level.
This method exists on the model that is loaded from cocoSsd.load.
1model.detect( 2 img: tf.Tensor3D | ImageData | HTMLImageElement | 3 HTMLCanvasElement | HTMLVideoElement, maxNumBoxes: number, minScore: number 4)
Args:
- img: A Tensor or an image element to make a detection on.
- maxNumBoxes: The maximum number of bounding boxes of detected objects. There can be multiple objects of the same class, but at different locations. Defaults to 20.
- minScore: The minimum score of the returned bounding boxes of detected objects. Value between 0 and 1. Defaults to 0.5.
Returns an array of classes and probabilities that looks like:
1[{ 2 bbox: [x, y, width, height], 3 class: "person", 4 score: 0.8380282521247864 5}, { 6 bbox: [x, y, width, height], 7 class: "kite", 8 score: 0.74644153267145157 9}]
Technical details for advanced users
This model is based on the TensorFlow object detection API. You can download the original models from here. We applied the following optimizations to improve the performance for browser execution:
- Removed the post process graph from the original model.
- Used single class NonMaxSuppression instead of original multiple classes NonMaxSuppression for faster speed with similar accuracy.
- Executes NonMaxSuppression operations on CPU backend instead of WebGL to avoid delays on the texture downloads.
Here is the converter command for removing the post process graph.
1tensorflowjs_converter --input_format=tf_frozen_model \ 2 --output_format=tfjs_graph_model \ 3 --output_node_names='Postprocessor/ExpandDims_1,Postprocessor/Slice' \ 4 ./frozen_inference_graph.pb \ 5 ./web_model
No vulnerabilities found.
Reason
all changesets reviewed
Reason
no binaries found in the repo
Reason
license file detected
Details
- Info: project has a license file: LICENSE:0
- Info: FSF or OSI recognized license: Apache License 2.0: LICENSE:0
Reason
SAST tool is not run on all commits -- score normalized to 9
Details
- Warn: 28 commits out of 30 are checked with a SAST tool
Reason
0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Reason
no effort to earn an OpenSSF best practices badge detected
Reason
security policy file not detected
Details
- Warn: no security policy file detected
- Warn: no security file to analyze
- Warn: no security file to analyze
- Warn: no security file to analyze
Reason
project is not fuzzed
Details
- Warn: no fuzzer integrations found
Reason
dependency not pinned by hash detected -- score normalized to 0
Details
- Warn: pipCommand not pinned by hash: deeplab/scripts/convert_deeplab.sh:188
- Info: 0 out of 1 pipCommand dependencies pinned
Reason
113 existing vulnerabilities detected
Details
- Warn: Project is vulnerable to: GHSA-v88g-cgmw-v5xw
- Warn: Project is vulnerable to: GHSA-93q8-gq69-wqmw
- Warn: Project is vulnerable to: GHSA-v6h2-p8h4-qcjw
- Warn: Project is vulnerable to: GHSA-3xgq-45jj-v275
- Warn: Project is vulnerable to: GHSA-chwr-hf3w-c984
- Warn: Project is vulnerable to: GHSA-67mh-4wv8-2f99
- Warn: Project is vulnerable to: GHSA-x3cc-x39p-42qx
- Warn: Project is vulnerable to: GHSA-f8q6-p94x-37v3
- Warn: Project is vulnerable to: GHSA-xvch-5gv4-984h
- Warn: Project is vulnerable to: GHSA-r683-j2x4-v87g
- Warn: Project is vulnerable to: GHSA-c2qf-rxjj-qqgw
- Warn: Project is vulnerable to: GHSA-j8xg-fqg3-53r7
- Warn: Project is vulnerable to: GHSA-gcx4-mw62-g8wm
- Warn: Project is vulnerable to: GHSA-hj48-42vr-x3v9
- Warn: Project is vulnerable to: GHSA-968p-4wvh-cqc8
- Warn: Project is vulnerable to: GHSA-67hx-6x53-jw92
- Warn: Project is vulnerable to: GHSA-qwcr-r2fm-qrc7
- Warn: Project is vulnerable to: GHSA-grv7-fg5c-xmjg
- Warn: Project is vulnerable to: GHSA-x9w5-v3q2-3rhw
- Warn: Project is vulnerable to: GHSA-pxg6-pf52-xh8x
- Warn: Project is vulnerable to: GHSA-434g-2637-qmqr
- Warn: Project is vulnerable to: GHSA-49q7-c7j4-3p7m
- Warn: Project is vulnerable to: GHSA-977x-g7h5-7qgw
- Warn: Project is vulnerable to: GHSA-f7q4-pwc6-w24p
- Warn: Project is vulnerable to: GHSA-fc9h-whq2-v747
- Warn: Project is vulnerable to: GHSA-vjh7-7g9h-fjfh
- Warn: Project is vulnerable to: GHSA-q9mw-68c2-j6m5
- Warn: Project is vulnerable to: GHSA-jchw-25xp-jwwc
- Warn: Project is vulnerable to: GHSA-cxjh-pqwp-8mfp
- Warn: Project is vulnerable to: GHSA-h7cp-r72f-jxh6
- Warn: Project is vulnerable to: GHSA-v62p-rq8g-8h59
- Warn: Project is vulnerable to: GHSA-25hc-qcg6-38wj
- Warn: Project is vulnerable to: GHSA-cqmj-92xf-r6r9
- Warn: Project is vulnerable to: GHSA-3h5v-q93c-6h6q
- Warn: Project is vulnerable to: GHSA-w573-4hg7-7wgq
- Warn: Project is vulnerable to: GHSA-9c47-m6qq-7p4h
- Warn: Project is vulnerable to: GHSA-952p-6rrq-rcjv
- Warn: Project is vulnerable to: GHSA-5rrq-pxf6-6jx5
- Warn: Project is vulnerable to: GHSA-8fr3-hfg3-gpgp
- Warn: Project is vulnerable to: GHSA-gf8q-jrpm-jvxq
- Warn: Project is vulnerable to: GHSA-2r2c-g63r-vccr
- Warn: Project is vulnerable to: GHSA-cfm4-qjh2-4765
- Warn: Project is vulnerable to: GHSA-x4jg-mjrx-434g
- Warn: Project is vulnerable to: GHSA-rp65-9cf3-cjxr
- Warn: Project is vulnerable to: GHSA-566m-qj78-rww5
- Warn: Project is vulnerable to: GHSA-7fh5-64p2-3v2j
- Warn: Project is vulnerable to: GHSA-hwj9-h5mp-3pm3
- Warn: Project is vulnerable to: GHSA-hrpp-h998-j3pp
- Warn: Project is vulnerable to: GHSA-p8p7-x288-28g6
- Warn: Project is vulnerable to: GHSA-m6fv-jmcg-4jfg
- Warn: Project is vulnerable to: GHSA-cm22-4g7w-348p
- Warn: Project is vulnerable to: GHSA-4wf5-vphf-c2xc
- Warn: Project is vulnerable to: GHSA-fq6p-x6j3-cmmq
- Warn: Project is vulnerable to: GHSA-72xf-g2v4-qvf3
- Warn: Project is vulnerable to: GHSA-r7qp-cfhv-p84w
- Warn: Project is vulnerable to: GHSA-pw2r-vq6v-hr8c
- Warn: Project is vulnerable to: GHSA-7x7c-qm48-pq9c
- Warn: Project is vulnerable to: GHSA-rc3x-jf5g-xvc5
- Warn: Project is vulnerable to: GHSA-mwcw-c2x4-8c55
- Warn: Project is vulnerable to: GHSA-fhg7-m89q-25r3
- Warn: Project is vulnerable to: GHSA-w8qv-6jwh-64r5
- Warn: Project is vulnerable to: GHSA-896r-f27r-55mw
- Warn: Project is vulnerable to: GHSA-6fc8-4gx4-v693
- Warn: Project is vulnerable to: GHSA-fwr7-v2mv-hh25
- Warn: Project is vulnerable to: GHSA-whgm-jr23-g3j9
- Warn: Project is vulnerable to: GHSA-q8pj-2vqx-8ggc
- Warn: Project is vulnerable to: GHSA-273r-mgr4-v34f
- Warn: Project is vulnerable to: GHSA-6h5x-7c5m-7cr7
- Warn: Project is vulnerable to: GHSA-rv95-896h-c2vc
- Warn: Project is vulnerable to: GHSA-qw6h-vgh9-j6wx
- Warn: Project is vulnerable to: GHSA-74fj-2j2h-c42q
- Warn: Project is vulnerable to: GHSA-rc47-6667-2j5j
- Warn: Project is vulnerable to: GHSA-c7qv-q95q-8v27
- Warn: Project is vulnerable to: GHSA-78xj-cgh5-2h22
- Warn: Project is vulnerable to: GHSA-2p57-rm9w-gvfp
- Warn: Project is vulnerable to: GHSA-76p3-8jx3-jpfq
- Warn: Project is vulnerable to: GHSA-3rfm-jhwj-7488
- Warn: Project is vulnerable to: GHSA-hhq3-ff78-jv3g
- Warn: Project is vulnerable to: GHSA-82v2-mx6x-wq7q
- Warn: Project is vulnerable to: GHSA-qrpm-p2h7-hrv2
- Warn: Project is vulnerable to: GHSA-9wv6-86v2-598j
- Warn: Project is vulnerable to: GHSA-rhx6-c78j-4q9w
- Warn: Project is vulnerable to: GHSA-3jfq-g458-7qm9
- Warn: Project is vulnerable to: GHSA-r628-mhmh-qjhw
- Warn: Project is vulnerable to: GHSA-9r2w-394v-53qc
- Warn: Project is vulnerable to: GHSA-5955-9wpr-37jh
- Warn: Project is vulnerable to: GHSA-qq89-hq3f-393p
- Warn: Project is vulnerable to: GHSA-f5x3-32g6-xq36
- Warn: Project is vulnerable to: GHSA-hh27-ffr2-f2jc
- Warn: Project is vulnerable to: GHSA-rqff-837h-mm52
- Warn: Project is vulnerable to: GHSA-8v38-pw62-9cw2
- Warn: Project is vulnerable to: GHSA-hgjh-723h-mx2j
- Warn: Project is vulnerable to: GHSA-jf5r-8hm2-f872
- Warn: Project is vulnerable to: GHSA-hc6q-2mpp-qw7j
- Warn: Project is vulnerable to: GHSA-4vvj-4cpr-p986
- Warn: Project is vulnerable to: GHSA-wr3j-pwj9-hqq6
- Warn: Project is vulnerable to: GHSA-4v9v-hfq4-rm2v
- Warn: Project is vulnerable to: GHSA-9jgg-88mc-972h
- Warn: Project is vulnerable to: GHSA-pfrx-2q88-qq97
- Warn: Project is vulnerable to: GHSA-jf85-cpcp-j695
- Warn: Project is vulnerable to: GHSA-fvqr-27wr-82fm
- Warn: Project is vulnerable to: GHSA-4xc9-xhrj-v574
- Warn: Project is vulnerable to: GHSA-x5rq-j2xg-h7qm
- Warn: Project is vulnerable to: GHSA-p6mc-m468-83gw
- Warn: Project is vulnerable to: GHSA-29mw-wpgm-hmr9
- Warn: Project is vulnerable to: GHSA-35jh-r3h4-6jhm
- Warn: Project is vulnerable to: GHSA-hxcc-f52p-wc94
- Warn: Project is vulnerable to: GHSA-7r28-3m3f-r2pr
- Warn: Project is vulnerable to: GHSA-r8j5-h5cx-65gg
- Warn: Project is vulnerable to: GHSA-w7rc-rwvf-8q5r
- Warn: Project is vulnerable to: GHSA-36jr-mh4h-2g58
- Warn: Project is vulnerable to: GHSA-4rq4-32rv-6wp6
- Warn: Project is vulnerable to: GHSA-64g7-mvw6-v9qj
Score
4
/10
Last Scanned on 2025-06-30
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