I just started to play around with eIQ toolkit, and have a question in regards to importing images from local disc drive and managing them afterwards. I was able to import few of them, however I have no idea how to manage the imported images. The questions are:
Thank you very much in advance for your support, I believe the tool is very promising!
thank you very much for your support!
In reference to 2., thank you very much for pointing me that out, it turned out really helpful. In addition to this, I have modified the original notebook Structured Folders Importer.ipynb and tailored it to read images from subfolders which names corresponds to labels and each subfolder contains whole bunch of images corresponding to particular label. Splitting imported images is done in the code, so no manual efforts are required to achieve train/test folders. You need to notice that installing scikit-learn in your virtual environment is required to use this splitting functionality:
pip install scikit-learn
Hope that might be helpful, please see attached. As .ipynb extension is not supported here, I am adding .zip archieve
Thanks for the feedback. Let me address your questions one by one:
1) Right now there is not a way to do that with the eIQ Portal tool but that is something we can implement in future update.
2) You can use the Jupytr notebook at C:\nxp\eIQ_Toolkit_v1.0.5\workspace\importer\Structured Folders Importer.ipynb to import images from a folder structure. There's a lab document that goes through step-by-step how to use that here: https://community.nxp.com/t5/eIQ-Machine-Learning-Software/eIQ-Portal-for-MCU-Getting-Started-Labs/t...
3) There are no constraints about importing files with the same name as some datasets may have them labeled as "1.jpg", "2.jpg" and separated by folder. Thanks for the feedback on that though.
4) Thanks for the feedback and we'll look at adding that in the next update.
5) We'll get that fixed in the next update.
6) You can see the number of images left unlabeled in this highlighted section:
7) We'll fix that in the next update.
Let us know if you have any more questions!