Hello,
I am a relative beginner, trying to get familiar with HTM (by reviewing various jupytr notebooks shared on the forum - using a docker image).
Looking forward to suggestions, directions, or leads.
In order to make the learning process more grounded, I am doing following:
- Collecting images of trees in my backyard.
- Creating a layered image (using paint) to mark stem, leaf, flower etc.
- Using chatgpt to trouble shoot when stuck.
What I anticipate, there are about 15 trees (such as: fig, guava, moringa etc), over the summer they will be having a growth spurt. In my limited understanding a model when given an input of image should “predict the tree” easily.
Similarly, when using a video as input - should be able to label / create a bounding box?!
With encoding spatial information of individual tree, i.e. where they are relatively located on a satellite image of backyard - should make it interesting?
Thus looking forward to thoughts, on what all should one consider. For example:
- Creating a data set?
- Structuring the encoder, pooler pipeline?
- How to make it functional / utilize it?
Thank You.
Example of Image and annotating stem layer.
