Heiko J Schick
76 lines
1.8 KiB
Makefile
76 lines
1.8 KiB
Makefile
.PHONY: help
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VENV_NAME?=env
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PYTHON=${VENV_NAME}/bin/python3
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LINT_FILES=linear_regression.py \
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lenet5.py \
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vgg16-prepare_train_model.py \
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vgg16-test_model.py \
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yolov3.py
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.DEFAULT: help
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help:
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@echo "make linear_regression"
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@echo " runs a linear regression example"
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@echo "make lenet5"
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@echo " runs a LeNet-5 character recognition example"
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@echo "make vgg16"
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@echo " runs a VGG16 object detection example"
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@echo "make yolov3"
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@echo " runs the YOLO v3 object detection example"
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@echo "make env"
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@echo " creates and prepares the environment"
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@echo "make data"
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@echo " downloads and unpacks the data"
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@echo "make lint"
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@echo " runs pylint"
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@echo "make clean"
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@echo " cleans the development environment"
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data: images
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images:
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wget https://s3.us-east-2.amazonaws.com/naturalimages02/images.tar.gz
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tar -xzf images.tar.gz
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env: $(VENV_NAME)/bin/activate
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$(VENV_NAME)/bin/activate:
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test -d $(VENV_NAME) || python3 -m venv $(VENV_NAME)
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${PYTHON} -m pip install -U pip
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${PYTHON} -m pip install --upgrade tensorflow
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${PYTHON} -m pip install keras
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${PYTHON} -m pip install matplotlib
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${PYTHON} -m pip install keras_vggface
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${PYTHON} -m pip install pylint
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${PYTHON} -m pip install mypy
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${PYTHON} -m pip install pandas
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${PYTHON} -m pip install sklearn
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touch $(VENV_NAME)/bin/activate
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linear_regression: env
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${PYTHON} linear_regression.py
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lenet5: env
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${PYTHON} lenet5.py
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vgg16_training: fine_tune.h5
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fine_tune.h5:
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${PYTHON} vgg16-prepare_train_model.py
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vgg16: env data vgg16_training
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${PYTHON} vgg16-test_model.py
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yolov3: env data
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${PYTHON} yolov3.py
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lint: env
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${PYTHON} -m pylint --rcfile=pylintrc $(LINT_FILES)
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clean:
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rm -rf $(VENV_NAME)
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rm -f data.csv
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rm -rf images
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rm -f images.tar.gz
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rm -f fine_tune.h5
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rm -rf yolov3.h5
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rm -rf lenet5.h5
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rm -rf .mypy_cache
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rm -rf *.gz
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