- Install python3 and virtualenv if it is not installed for your platform
For Ubuntu:
sudo apt-get install virtualenv
For OSX:
brew install virtualenv
- Clone this repository
git clone [email protected]:sahajsoft/aakaar.git
- Inside aakaar directory create a virtualenv with python3
cd aakaar/
virtualenv -p python3 venv
- Source virtualenv
`source venv/bin/activate~
- Install all required pip dependencies
pip install -r requirements.txt
- Outside aakaar directory clone tensorflow models repo
git clone https://github.com/tensorflow/models
- In your shell rc file import the path for the slim form models/research directory
vi ~/.bashrc
orvi ~/.zshrc
depending on the shell you are using Add line at the endexport PYTHONPATH=$PYTHONPATH:<Directory_To_Models_Parent_Folder>/models/research:<Directory_To_Models_Folder>/models/research/slim
- Git clone cocoapi and make
git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
make
- Copy pycoco tools to the models
cp -r pycocotools <Directory_To_Models_Parent_Folder>/models/research/
- Generate protobuf files from the config
Ensure that correct version of protobuf is installed. I had 3.5+ installed.
cd <Directory_To_Models_Parent_Folder>/models/research/
protoc object_detection/protos/*.proto --python_out=.
- Run simple tensorflow test to ensure everything is correctly installed
cd
<Directory_To_Models_Parent_Folder>/models/research
python object_detection/builders/model_builder_test.py
Local Machine
PIPELINE_CONFIG_PATH="/Users/priyank/Projects/aakaar/model/config"
MODEL_DIR="/Users/priyank/Projects/aakaar/model/"
NUM_TRAIN_STEPS=50000
SAMPLE_1_OF_N_EVAL_EXAMPLES=1
python object_detection/model_main.py \
--pipeline_config_path=${PIPELINE_CONFIG_PATH} \
--model_dir=${MODEL_DIR} \
--num_train_steps=${NUM_TRAIN_STEPS} \
--sample_1_of_n_eval_examples=$SAMPLE_1_OF_N_EVAL_EXAMPLES \
--alsologtostderr
AWS GPU Instance
PIPELINE_CONFIG_PATH="/home/ubuntu/projects/aakaar/model/config.server"
MODEL_DIR="/home/ubuntu/projects/aakaar/model/"
NUM_TRAIN_STEPS=50000
SAMPLE_1_OF_N_EVAL_EXAMPLES=1
python object_detection/model_main.py \
--pipeline_config_path=${PIPELINE_CONFIG_PATH} \
--model_dir=${MODEL_DIR} \
--num_train_steps=${NUM_TRAIN_STEPS} \
--sample_1_of_n_eval_examples=$SAMPLE_1_OF_N_EVAL_EXAMPLES \
--alsologtostderr
Exporting frozen reference graph
python /Users/priyank/PetProjects/models/research/object_detection/export_inference_graph.py --input_type image_tensor --pipeline_config_path ~/Projects/aakaar/model/config --trained_checkpoint_prefix ~/Projects/aakaar/model/model.ckpt-50000.data-00000-of-00001 --output_directory model_output