Implementation of TensorFlow Object Detection API on Windows 10 with fruit images without Anaconda Distribution.
No Anaconda Distribution. Use command prompt instead of Anaconda Prompt.
1)Don't use the below commands in 2d.
conda create -n tensorflow1 pip python=3.5
activate tensorflow1
2)Change the command below in 2d
conda install -c anaconda protobuf
to this
pip install protobuf --upgrade
3)Download protoc.exe from here . Copy protoc.exe(in bin folder) to C:\tensorflow1\models\research.
Then run 2f.
4)Before step6, open C:\tensorflow1\models\research\object_detection\utils\learning_schedules.py with a text editor.
Change the line 168 from
range(num_boundaries)
to
list(range(num_boundaries))
Data can be downloaded from here. 240 training images 60 test images. No problematic image.
3 different types of fruits: Apple, Banana, Orange.
.xml files in data have coordinates of objects.
I trained it on a GTX 1050 for 5 hours. Approximately 53000 iterations.
Faster R CNN inception v2 model.
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Credits go to EdgeElectronics. I just followed the steps in the tutorial.