This is an implementation of Plant segmentation using deep learning fractal-net on Python 3. This code generates masking in every objects in one image.

The repository includes:

• Source code of plant segemtation using deep learning fractal net.
• using Spyder IDE to visualize important step.
• Example of training on your own dataset (training)
• Example how to test our dataset (testing)
• evaluate the result

• open colour load_model.py in the main page Is the easiest way to start. It shows an example of plant segmentation. (testing only)
• open main_1kelas.py in the main page, this codes for training (training)

just put dataset in your main path. Make sure u put the data and codes like my picture below! dataset : https://drive.google.com/file/d/1lEG74V3n4e59mIIGQHxKV3P8J9cg39fQ/view?usp=sharing

This example will explain which part u must change to train your own dataset.open code with name 1main_kelas.py just change how many epoch u want and make sure your path is right.

press F5.

just put dataset in your main path. Make sure u put the data and codes like my picture below!

dataset : https://drive.google.com/file/d/1zJHNGNyhGoO7oA3PEGDSjTz00eFRdor0/view?usp=sharing

open load model.py code, then make sure the path is right and name of the model too.

press F5

open evaluate_result.py, then make sure again about the label and predict path.

press F5