Python code to test different Tensorflow models for our own datasets.
We want to take our tagged images and apply transfer learning to models to recognize the features that we tag in our images.
Input data:
Our images (jpg & png) and XML files (containing object tag information: labels and coordinates).
Functional requirements:
Apply the input data to Tensorflow models (CNN, Faster R-CNN, etc) to build functional neural nets that can localize the objects we train them on.
Able to compile on Mac and Ubuntu 16.04, 18.04.
Thanks
I have done similar project in freelancer. You can check my bio for that. In that project we have used deep learning(CNN) for doing the work with high accuracy. I could reuse the work and can do your work easily. I just need 2 to 3 days to complete the project efficiently. Contact me for more details. Price is negotiable.
I have experience in deep learning. I completed may project on tensorflow and computer vision.
I completed my deep learning spicalization from cousera and may more couse on python.
Hey, I have good experience with computer vision and reinforcement learning and most of my work is in tenaorflow. I think I can do this job real well.
Thanks
Object Detection In Preferable Level
The Coordinates Can Be X,Y, W, H or X_min, Y_min, X_max, Y_max
Model can be trained and deployed to you at earliest.
Relevant Skills and Experience
Tensorflow, Keras, GANs, Yolo, Object Localisation
Interesting work. I have experience in working in this type of project. Looking forward to work.
Currently working in deep learning image processing related projects.