Search Results for "pascal to python"

This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3...

Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train...

EVEAI is a Deep Learning Library based on python Keras and Tensorflow. EVEAI dll allows embedding inference images from keras models into user-written applications. Under Windows, the EVEAI training Tool provides services to train user specific image datasets and EVEAI dll provides services to existing Windows applications which support inference images. Please visit https://github.com/Hommoner/EVEAI for more information.

LabelImg is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Annotations are saved as XML files in PASCAL VOC format, the format used by ImageNet. Besides, it also supports YOLO and CreateML formats. Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8. However, Python 3 or above and PyQt5 are strongly recommended. Virtualenv can avoid a lot of the QT / Python version issues. Build and launch using the instructions...

In practice, a higher mAP value indicates a better performance of your neural net, given your ground truth and set of classes. The performance of your neural net will be judged using the mAP criteria defined in the PASCAL VOC 2012 competition. We simply adapted the official Matlab code into Python (in our tests they both give the same results). First, your neural net detection-results are sorted by decreasing confidence and are assigned to ground-truth objects. We have "a match" when they share...

This project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.