Instructions_for_ml.txt

How to run succesfull machine learning V1.0 (#rahul)


0. Creating XML to CSV vs CSV to tfrecord
	
	i. Run code xml_to_csv.py - it will create test_labels.csv vs train_labels.csv
	
	ii. Run generate_tfrecord.py to create train.record and test.record
	    python3 generate_tfrecord.py --csv_input=data/train_labels.csv --output_path=data/train.record --image_dir=images/

           python3 generate_tfrecord.py --csv_input=data/test_labels.csv --output_path=data/test.record --image_dir=images/
		

1. Create enviorment
	install tensorflow or tensorflow-gpu (according to compatibility)
	
	#Install these three main packages
	 sudo apt-get install protobuf-compiler python-pil python-lxml
	 sudo pip install jupyter
	 sudo pip install matplotlib

2. Now download the official repo of github model
	
	i. https://github.com/tensorflow/models.git

	ii. extract the folder
	
	iii. (cd models) Go to model folder export the python libraries
	export PYTHONPATH=$PYTHONPATH:`pwd`:`pwd`/slim
	
	iv. (cd object_detection) export the protobuf compiler used for serializing structured data.
	protoc object_detection/protos/*.proto --python_out=.

3. Run the following command when you done system working fine
	
	python3 legacy/train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config

protobuf error solve
https://gist.github.com/diegopacheco/cd795d36e6ebcd2537cd18174865887b


Error and resolve