YOLO Algorithm Implementation with Keras & Tensorflow

The project implements Convolutional Deep Neural Network (ConvNet) You Only Look Once (YOLO) algorithm. It is based on a Keras + TensorFlow trained model.

Prerequisites

The project requires Keras + TensorFlow. There is also an HTTP Streaming version that displays annotated images in streaming mode. Thus it also requires Flask.

Installing

Clone the GitHub repository to install the project. It is possible to run the project on RasperryPi also. In this case, main file shall be updated to launch RaspberryPi camera.

Running the script

Run in console mode:

python main_cv2_drawing.py

Run in streaming mode:

python main_flask_server.py

Name		Name	Last commit message	Last commit date
Latest commit History 29 Commits
out		out
streaming		streaming
templates		templates
tools		tools
yolo_algo		yolo_algo
yolo_keras_tensorflow		yolo_keras_tensorflow
.ftpconfig		.ftpconfig
.gitignore		.gitignore
README.md		README.md
main_cv2_drawing.py		main_cv2_drawing.py
main_flask_server.py		main_flask_server.py
main_test.py		main_test.py
main_test_module_version.py		main_test_module_version.py
requirements.txt		requirements.txt
setup.py		setup.py

bbouffaut/yolo_tensorflow_objects_detection

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YOLO Algorithm Implementation with Keras & Tensorflow

Prerequisites

Installing

Running the script

Run in console mode:

Run in streaming mode:

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