Running real-time person and body part segmentation in the browser using TensorFlow.js is excellent!
Link: https://github.com/tensorflow/tfjs-models/tree/master/body-pix
How I can include numbers or letters for the different body parts segmentation instead of using different colors on the video overlay?
Thank you so much!
Related
I have used tensorflow.js to do person segmentation of live video in a web browser. Is there a similar tensorflowlite/mobile version of the same? Is there any android SDK available to do person/video segmentation on mobile clients? Any pointers would be very helpful.
thanks
Sowmya
Yes, TensorFlow Lite is available for Android. Click here for more.
You can use TensorFlow Lite's Segmentation Model. You can see an example GIF on the page also. The segmentation model ( DeepLab v3 ) can segment various objects in an image. Since we are concerned with person segmentation, DeepLabv3 can handle that too.
If you want to use BodyPix, which is a TensorFlow.js implementation, you need to find the model's frozen graph along with the input/output nodes. Only then you can get it into TensorFlow Lite. On investigating the repo, I found this file which contains the URLs for the model.
Else, we can use Real-Time Pose Estimation, which is also a TF JS implementation.
I'm putting my first steps in Machine Learning, I went through many TensorFlow.js tutorials already and I'm trying to achieve this: "Realtime Single Object Tracking/Detection"
Something like this -> input: webcam/video -> output: object bounding box
I know there are SSD and YOLO, and other libraries to predict & locate the objects. But the predicted time is very slow (in browser), I guessed it's because the Neural Network have to predict between so many objects.
https://github.com/ModelDepot/tfjs-yolo-tiny
https://github.com/tensorflow/models/tree/master/research/object_detection
What if I just want to track a single object? Would it be possible? Will the performance be better? Where should I start?
I've been thinking about extract the pre-trained class (object) from a SavedModel, then start training more from it. But there don't seems to be any instructions around Google.
I found some fantastic code by IBM, which I used in the video in this tweet: https://twitter.com/GantLaborde/status/1125735283343921152?s=20
I extracted that code to make a ReactJS component for detecting Rock/Paper/Scissors here: https://github.com/GantMan/rps_tfjs_demo/blob/master/src/AdvancedModel.js
If you'd like to play with the demo, it's at the bottom of this page: https://rps-tfjs.netlify.com/
All of this is open source and seems to work perfectly fast for detecting a single object in realtime.
Currently I am using a deep learing model which is called "Yolov2" for object detection, and I want to use it to extract text and use save it in disk, but i don't know how to do that, if anyone know more about that, please advice me
I use Tensorflow
Thanks
If you use the pretrained model, you would need to save those outputs and input the images into a character recognition network, if using neural net, or another approach.
What you are doing is "scene text recognition". You can check out the Reading Text in the Wild with Convolutional Neural Networks paper, here's a demo and homepage. Github user chongyangtao has a whole list of resources on the topic.
I have a similar question and I am making a digit detection model with svhn dataset. It is not a finished project yet, but it seems to work well. You can see the code at Yolo-digit-detector.
i am actually working on a deep learning program and i try to develop an convolutional neural network for image recognition, my problem is how can we identify in the input pictures the differents patterns that we try to extract?
Thanks
I'm trying to send image input over http to classify using tensorflow. I have looked in detail in the c++ code for https://www.tensorflow.org/versions/r0.9/tutorials/image_recognition/index.html
I have implemented the inception-v3 example model using C++ API. It takes image input in the following form:
bazel-bin/tensorflow/examples/label_image/label_image --image=my_image.png
However, I want to add the case of:
bazel-bin/tensorflow/examples/label_image/label_image --image=http://www.somewebsite.com/my_image.png
This is due to the fact that it only accepts local image files. I want to add the functionality to take file pointers from online images and classify it in memory. I'm currently working on this, but so far no luck. Can anyone offer some insight how I would go about implementing this?