Python programmer with ClassificationBox knowledge
Tampa, Southwest Florida, USA
Job TitlePython programmer with ClassificationBox knowledge
We have a need for the development of an easy frontend program to allow a user to supply multiple folders locally on the device or via a URL, each of which is named for a specific class name for the images in the folder i.e. Cats, Dogs, Birds, then use the ClassificationBox API (Account details will be provided) to TRAIN the model on the folder's images. The resulting model will then be used in a second App (Android) that will allow the user to take a photo with the device's camera, submit the image to the (Trained ClassificationBox) model, and upon returning the classifications of the image, display the Class Name's on the screen along with a bounding box around the resulting class(es) found in the image and the percent of confidence scores for each class identified. The App shall have the ability to have the user input a single class name that will trigger a repeating sound and flashing of the screen when that class is found in the image taken and sent through the model. This will be used as a Demo for a potentially long term project and may lead to more work and opportunities for further development work.
- Telecommuting is OK
- No Agencies Please
Must be able to create a python program able to interface with the ClassificationBox API, have multiple file folders inputted by the end-user and train the model. Must be able to code an Android App using Python, and any other needed technology, interface with the ClassificationBox "Classify" API and return the results to the end-user as well as take a single input from the user to set off sounds and flashing screen on the device when that class is found in an image taken by the device camera. the resulting App shall be provided, source and APK, to the company at the end of the project. The source and any binaries shall be provided for the training program also.
About the Company
We are a fledgling startup working on various projects utilizing Machine Language models in end-user applications, specifically mobile Android and IOS devices. We are currently developing an App using ML's native to the devices using Tensorflow Lite instead of using server-based ML's, making our Apps lean and mean and standalone, thereby enabling them to operate independently of the Internet or Phone connections for use in the field.
These two applications will be the foundation for doing Demonstrations to potential investors and customers to show the effectiveness of using ML to solve issues of great importance to the customers as well as to the general public.